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What Are Quantitative Survey Questions? Types and Examples

Table of contents: 

• Types of quantitative survey questions - with examples 
• Quantitative question formats
• How to write quantitative survey questions 
• Examples of quantitative survey questions 

Leveraging quantilope for your quantitative survey 

In a quantitative research study brands will gather numeric data for most of their questions through formats like numerical scale questions or ranking questions. However, brands can also include some non-quantitative questions throughout their quantitative study - like open-ended questions, where respondents will type in their own feedback to a question prompt. Even so, open-ended answers can be numerically coded to sift through feedback easily (e.g. anyone who writes in 'Pepsi' in a soda study would be assigned the number '1', to look at Pepsi feedback as a whole).  One of the biggest benefits of using a quantitative research approach is that insights around a research topic can undergo statistical analysis; the same can’t be said for qualitative data like focus group feedback or interviews. Another major difference between quantitative and qualitative research methods is that quantitative surveys require respondents to choose from a limited number of choices in a close-ended question - generating clear, actionable takeaways. However, these distinct quantitative takeaways often pair well with freeform qualitative responses - making quant and qual a great team to use together.  The rest of this article focuses on quantitative research, taking a closer look at quantitative survey question types and question formats/layouts. 

Back to table of contents 

Types of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions - with examples 

Quantitative questions come in many forms, each with different benefits depending on dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139784">your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research objectives. Below we’ll explore some of these dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139785">survey question dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139785" data-dropdown-placement-param="top" data-term-id="281139785"> types, which are commonly used together in a single survey to keep things interesting for dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents . The style of questioning used during dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139739">quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139750">data dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139750" data-dropdown-placement-param="top" data-term-id="281139750"> collection is important, as a good mix of the right types of questions will deliver rich data, limit dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent fatigue, and optimize the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139757">response rate . dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">Questionnaires should be enjoyable - and varying the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139755">types of dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139755" data-dropdown-placement-param="top" data-term-id="281139755">quantitative research dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139755"> questions used throughout your survey will help achieve that. 

Descriptive survey questions

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139763">Descriptive research questions (also known as usage and attitude, or, U&A questions) seek a general indication or prediction about how a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139773">group of people behaves or will behave, how that group is characterized, or how a group thinks.

For example, a business might want to know what portion of adult men shave, and how often they do so. To find this out, they will survey men (the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139743">target audience ) and ask descriptive questions about their frequency of shaving (e.g. daily, a few times a week, once per week, and so on.) Each of these frequencies get assigned a numerical ‘code’ so that it’s simple to chart and analyze the data later on; daily might be assigned ‘5’, a few times a week might be assigned ‘4’, and so on. That way, brands can create charts using the ‘top two’ and ‘bottom two’ values in a descriptive question to view these metrics side by side.

Another business might want to know how important local transit issues are to residents, so dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions will allow dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to indicate the degrees of opinion attached to various transit issues. Perhaps the transit business running this survey would use a sliding numeric scale to see how important a particular issue is.

Comparative survey questions

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139782">Comparative research questions are concerned with comparing individuals or groups of people based on one or more variables. These questions might be posed when a business wants to find out which segment of its dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139743">target audience might be more profitable, or which types of products might appeal to different sets of consumers.

For example, a business might want to know how the popularity of its chocolate bars is spread out across its entire customer base (i.e. do women prefer a certain flavor? Are children drawn to candy bars by certain packaging attributes? etc.). Questions in this case will be designed to profile and ‘compare’ segments of the market.

Other businesses might be looking to compare coffee consumption among older and younger consumers (i.e. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139741">demographic segments), the difference in smartphone usage between younger men and women, or how women from different regions differ in their approach to skincare.

Relationship-based survey questions

As the name suggests, relationship-based survey questions are concerned with the relationship between two or more variables within one or more dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139741">demographic groups. This might be a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139759">causal link between one thing and the other - for example, the consumption of caffeine and dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents ’ reported energy levels throughout the day. In this case, a coffee or energy drink brand might be interested in how energy levels differ between those who drink their caffeinated line of beverages and those who drink decaf/non-caffeinated beverages.

Alternatively, it might be a case of two or more factors co-existing, without there necessarily being a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139759">causal link - for example, a particular type of air freshener being more popular amongst a certain dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139741">demographic (maybe one that is controlled wirelessly via Bluetooth is more popular among younger homeowners than one that’s plugged into the wall with no controls). Knowing that millennials favor air fresheners which have options for swapping out scents and setting up schedules would be valuable information for new product development.

Advanced method survey questions

Aside from descriptive, comparative, and relationship-based survey questions, brands can opt to include advanced methodologies in their quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire for richer depth. Though advanced methods are more complex in terms of the insights output, quantilope’s Consumer Intelligence Platform automates the setup and analysis of these methods so that researchers of any background or skillset can leverage them with ease.

With quantilope’s pre-programmed suite of 12 advanced methodologies , including MaxDiff , TURF , Implicit , and more, users can drag and drop any of these into a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire and customize for their own dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research objectives.

For example, consider a beverage company that’s looking to expand its flavor profiles. This brand would benefit from a MaxDiff which forces dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to make tradeoff decisions between a set of flavors. A dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent might say that coconut is their most-preferred flavor, and lime their least (when in a consideration set with strawberry), yet later on in the MaxDiff that same dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent may say Strawberry is their most-preferred flavor (over black cherry and kiwi). While this is just one example of an advanced method, instantly you can see how much richer and more actionable these quantitative metrics become compared to a standard usage and attitude question .

Advanced methods can be used alongside descriptive, comparison, or relationship questions to add a new layer of context wherever a business sees fit. Back to table of contents 

Quantitative question formats  

So we’ve covered the kinds of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139736">quantitative research questions you might want to answer using dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research , but how do these translate into the actual format of questions that you might include on your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire ?

Thinking ahead to your reporting process during your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139742">questionnaire setup is actually quite important, as the available chart types differ among the types of questions asked; some question data is compatible with bar chart displays, others pie charts, others in trended line graphs, etc. Also consider how well the questions you’re asking will translate onto different devices that your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents might be using to complete the survey (mobile, PC, or tablet).

Single Select questions

Single select questions are the simplest form of quantitative questioning, as dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents are asked to choose just one answer from a list of items, which tend to be ‘either/or’, ‘yes/no’, or ‘true/false’ questions. These questions are useful when you need to get a clear answer without any qualifying nuances.

Multi-select questions

Multi-select questions (aka, dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139767">multiple choice ) offer more flexibility for responses, allowing for a number of responses on a single question. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">Respondents can be asked to ‘check all that apply’ or a cap can be applied (e.g. ‘select up to 3 choices’).

For example:

Aside from asking text-based questions like the above examples, a brand could also use a single or multi-select question to ask respondents to select the image they prefer more (like different iterations of a logo design, packaging options, branding colors, etc.). 

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139749">Likert dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139766">scale dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139766" data-dropdown-placement-param="top" data-term-id="281139766"> questions

A dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139749">Likert scale   is widely used as a convenient and easy-to-interpret rating method. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">Respondents find it easy to indicate their degree of feelings by selecting the response they most identify with.

Slider scales

Slider scales are another good interactive way of formatting questions. They allow dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to customize their level of feeling about a question, with a bit more variance and nuance allowed than a numeric scale:

One particularly common use of a slider scale in a dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139770">research dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139770" data-dropdown-placement-param="top" data-term-id="281139770"> study is known as a NPS (Net Promoter Score) - a way to measure dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139775">customer experience and loyalty . A 0-10 scale is used to ask customers how likely they are to recommend a brand’s product or services to others. The NPS score is calculated by subtracting the percentage of ‘detractors’ (those who respond with a 0-6) from the percentage of promoters (those who respond with a 9-10). dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">Respondents who select 7-8 are known as ‘passives’.

For example: 

Drag and drop questions

Drag-and-drop question formats are a more ‘gamified’ approach to survey capture as they ask dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to do more than simply check boxes or slide a scale. Drag-and-drop question formats are great for ranking exercises - asking dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents to place answer options in a certain order by dragging with their mouse. For example, you could ask survey takers to put pizza toppings in order of preference by dragging options from a list of possible answers to a box displaying their personal preferences:

Matrix questions

Matrix   questions are a great way to consolidate a number of questions that ask for the same type of response (e.g. single select yes/no, true/false, or multi-select lists). They are mutually beneficial - making a survey look less daunting for the dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondent , and easier for a brand to set up than asking multiple separate questions.

Items in a matrix question are presented one by one, as respondents cycle through the pages selecting one answer for each coffee flavor shown. 

While the above example shows a single-matrix question - meaning a respondent can only select one answer per element (in this case, coffee flavors), a matrix setup can also be used for multiple-choice questions - allowing respondents to choose multiple answers per element shown, or for rating questions - allowing respondents to assign a rating (e.g. 1-5) for a list of elements at once.  Back to table of contents 

How to write dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions  

We’ve reviewed the types of questions you might ask in a quantitative survey, and how you might format those questions, but now for the actual crafting of the content.

When considering which questions to include in your survey, you’ll first want to establish what your research goals are and how these relate to your business goals. For example, thinking about the three types of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions explained above - descriptive, comparative, and relationship-based - which type (or which combination) will best meet your research needs? The questions you ask dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents may be phrased in similar ways no matter what kind of layout you leverage, but you should have a good idea of how you’ll want to analyze the results as that will make it much easier to correctly set up your survey.

Quantitative questions tend to start with words like ‘how much,’ ‘how often,’ ‘to what degree,’ ‘what do you think of,’ ‘which of the following’ - anything that establishes what consumers do or think and that can be assigned a numerical code or value. Be sure to also include ‘other’ or ‘none of the above’ options in your quant questions, accommodating those who don’t feel the pre-set answers reflect their true opinion. As mentioned earlier, you can always include a small number of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139748">open-ended questions in your quant survey to account for any ideas or expanded feedback that the pre-coded questions don’t (or can’t) cover. Back to table of contents 

Examples of dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">quantitative survey questions  

dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139745">Quantitative survey questions impose limits on the answers that dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents can choose from, and this is a good thing when it comes to measuring consumer opinions on a large scale and comparing across dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents . A large volume of freeform, open-ended answers is interesting when looking for themes from qualitative studies, but impractical to wade through when dealing with a large dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139756">sample size , and impossible to subject to dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139774">statistical analysis .

For example, a quantitative survey might aim to establish consumers' smartphone habits. This could include their frequency of buying a new smartphone, the considerations that drive purchase, which features they use their phone for, and how much they like their smartphone.

Some examples of quantitative survey questions relating to these habits would be:

Q. How often do you buy a new smartphone?

[single select question]

More than once per year

Every 1-2 years

Every 3-5 years

Every 6+ years

Q. Thinking about when you buy a smartphone, please rank the following factors in order of importance:

[drag and drop ranking question]

screen size

storage capacity

Q. How often do you use the following features on your smartphone?

[matrix question]

Q. How do you feel about your current smartphone?

[sliding scale]

I love it <-------> I hate it

Answers from these above questions, and others within the survey, would be analyzed to paint a picture of smartphone usage and attitude trends across a population and its sub-groups. dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139738">Qualitative research might then be carried out to explore those findings further - for example, people’s detailed attitudes towards their smartphones, how they feel about the amount of time they spend on it, and how features could be improved. Back to table of contents 

quantilope’s Consumer Intelligence Platform specializes in automated, advanced survey insights so that researchers of any skill level can benefit from quick, high-quality consumer insights. With 12 advanced methods to choose from and a wide variety of quantitative question formats, quantilope is your one-stop-shop for all things dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139740">market research (including its dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139776">in-depth dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139738">qualitative research solution - inColor ).

When it comes to building your survey, you decide how you want to go about it. You can start with a blank slate and drop questions into your survey from a pre-programmed list, or you can get a head start with a survey dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139765">template for a particular business use case (like concept testing ) and customize from there. Once your survey is ready to launch, simply specify your dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139743">target audience , connect any panel (quantilope is panel agnostic), and watch as dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139737">respondents dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139783">answer questions in your survey in real-time by monitoring the fieldwork section of your project. AI-driven dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139764">data analysis takes the raw data and converts it into actionable findings so you never have to worry about manual calculations or statistical testing.

Whether you want to run your quantitative study entirely on your own or with the help of a classically trained research team member, the choice is yours on quantilope’s platform. For more information on how quantilope can help with your next dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139736">quantitative dropdown#toggle" data-dropdown-placement-param="top" data-term-id="281139768">research dropdown#toggle" data-dropdown-menu-id-param="menu_term_281139768" data-dropdown-placement-param="top" data-term-id="281139768"> project , get in touch below!

Get in touch to learn more about quantitative research with quantilope!

Related posts, what are brand perceptions and how can you measure them, how can brands build, measure, and manage brand equity, how to use a brand insights tool to improve your branding strategy, quantilope's 5th consecutive year as a 'fastest growing tech company'.

98 Quantitative Research Questions & Examples

As researchers, we know how powerful quantitative research data can be in helping answer strategic questions. Here, I’ve detailed 23 use cases and curated 98 quantitative market research questions with examples – making this a post you should add to your bookmark list 📚, so you can quickly refer back.

I’ve formatted this post to show you 10-15 questions for each use case. At the end of each section, I also share a quicker way to get similar insights using modern market research tools like Similarweb.

What is a quantitative research question?

Quantitative market research questions tell you the what, how, when, and where of a subject. From trendspotting to identifying patterns or establishing averages– using quantitative data is a clear and effective way to start solving business problems.

Types of quantitative research questions

Quantitative market research questions are divided into two main types: descriptive and causal.

• Descriptive research questions seek to quantify a phenomenon by focusing on a certain population or phenomenon to measure certain aspects of it, such as frequency, average, or relationship.
• Causal research questions explore the cause-and-effect relationship between two or more variables.

The ultimate list of questions for quantitative market research

Get clear explanations of the different applications and approaches to quantitative research–with the added bonus of seeing what questions to ask and how they can impact your business.

Examples of quantitative research questions for competitive analysis

A powerful example of quantitative research in play is when it’s used to inform a competitive analysis . A process that’s used to analyze and understand how industry leaders and companies of interest are performing.

Pro Tip: Collect data systematically, and use a competitive analysis framework to record your findings. You can refer back to it when you repeat the process later in the year.

• What is the market share of our major competitors?
• What is the average purchase price of our competitors’ products?
• How often do our competitors release new products?
• What is the total number of customer reviews for our competitors’ products?
• What is the average rating of our competitors’ products?
• What is the average customer satisfaction score for our competitors?
• What is the average return rate of our competitors’ products?
• What is the average shipping time for our competitors’ products?
• What is the average price discount offered by our competitors?
• What is the average lifespan of our competitors’ products?

With this data, you can determine your position in the market and benchmark your performance against rival companies. It can then be used to improve offerings, service standards, pricing, positioning, and operational effectiveness. Notice that all questions can be answered with a numerical response , a key component of all successful examples of quantitative market research questions.

Quantitative research question example: market analysis

🙋‍♀️ Question: What is the market share of our major competitors?

🤓 Insight sought: Industry market share of leaders and key competitors.

🤯 Challenges with traditional quantitative research methods: Outdated data is a major consideration; data freshness remains critical, yet is often tricky to obtain using traditional research methods. Markets shift fast, so being able to obtain and track market share in real time is a challenge many face.

💡 A new approach: Similarweb enables you to track this key business KPI in real-time using digital data directly from the platform. On any day, you can see what your market share is, along with any players in your market. Plus, you get to see rising stars showing significant growth, who may pose a threat through market disruption or new tactics.

⏰ Time to insight: 30 seconds

✅ How it’s done: Using Similarweb’s Web Industry Analysis, two digital metrics give you the intel needed to decipher the market share in any industry. I’m using the Banking, Credit, and Lending market throughout these examples. I’ve selected the US market, analyzing the performance of the previous 3 months.

• Share of visits 

Here, I can see the top players in my market based on the number of unique visitors to their sites. On top of the raw data that shows me the volume of visitors as a figure, I can quickly see the two players ( Capital One and Chase ) that have grown and by what percentage. On the side, you can see rising players in the industry. Now, while my initial question was to establish the market share of my major competitors, I can see there are a few disruptive players in my market who I’d want to track too; Synchrony.com being one of particular interest, given their substantial growth and traffic numbers.

• Share of search 

Viewing the overall market size based on total search volumes, you can explore industry leaders in more detail. The top websites are the top five players, ranking by traffic share . You can also view the month-over-month change in visits, which shows you who is performing best at any given time . It’s the same five names, with Paypal and Chase leading the pack. However, I see Wells Fargo is better at attracting repeat visitors, while Capital One and Bank of America perform better at drawing in unique visitors.

In answer to my question, what is the market share of my major competitors, I can quickly use Similarweb’s quantitative data to get my answer.

This traffic share visual can be downloaded from the platform. It plots the ten industry leader’s market share and allocates the remaining share to the rest of the market.

I can also download a market quadrant analysis, which takes two key data points, traffic share and unique visitors, and plots the industry leaders. All supporting raw data can be downloaded in .xls format or connected to other business intelligence platforms via the API.

Quantitative research questions for consumer behavior studies

These studies measure and analyze consumer behavior, preferences, and habits . Any type of audience analysis helps companies better understand customer intent, and adjust offerings, messaging, campaigns, SEO, and ultimately offer more relevant products and services within a market.

• What is the average amount consumers spend on a certain product each month?
• What percentage of consumers are likely to purchase a product based on its price?
• How do the demographics of the target audience affect their purchasing behavior?
• What type of incentive is most likely to increase the likelihood of purchase?
• How does the store’s location impact product sales and turnover?
• What are the key drivers of product loyalty among consumers?
• What are the most commonly cited reasons for not buying a product?
• How does the availability of product information impact purchasing decisions?
• What is the average time consumers spend researching a product before buying it?
• How often do consumers use social media when making a purchase decision?

While applying a qualitative approach to such studies is also possible, it’s a great example of quantitative market research in action. For larger corporations, studies that involve a large, relevant sample size of a target market deliver vital consumer insights at scale .

Read More: 83 Qualitative Research Questions & Examples

Quantitative research question and answer: content strategy and analysis

🙋‍♀️ Question: What type of content performed best in the market this past month?

🤓 Insight sought: Establish high-performing campaigns and promotions in a market.

🤯 Challenges with traditional quantitative research methods: Whether you consider putting together a panel yourself, or paying a company to do it for you, quantitative research at scale is costly and time-consuming. What’s more, you have to ensure that sampling is done right and represents your target audience.

💡 A new approach: Data analysis is the foundation of our entire business. For over 10 years, Similarweb has developed a unique, multi-dimensional approach to understanding the digital world. To see the specific campaigns that resonate most with a target audience, use Similarweb’s Popular Pages feature. Key metrics show which campaigns achieve the best results for any site (including rival firms), campaign take-up, and periodic changes in performance and interest.

✅ How it’s done: I’ve chosen Capital One and Wells Fargo to review. Using the Popular Pages campaign filter, I can view all pages identified by a URL parameter UTM. For clarity, I’ve highlighted specific campaigns showing high-growth and increasing popularity. I can view any site’s trending, new, or best-performing pages using a different filter.

In this example, I have highlighted three campaigns showing healthy growth, covering teen checking accounts, performance savings accounts, and add-cash-in-store. Next, I will perform the same check for another key competitor in my market.

Here, I can see financial health tools campaigns with over 300% month-over-month growth and smarter credit and FICO campaigns showing strong performance. This tells me that campaigns focussing on education and tools are growing in popularity within this market. 

Examples of quantitative research questions for brand tracking

These studies are designed to measure customers’ awareness, perceptions, behaviors, and attitudes toward a brand over time. Different applications include measuring brand awareness , brand equity, customer satisfaction, and purchase or usage intent.

These types of research surveys ask questions about brand knowledge, brand attributes, brand perceptions, and brand loyalty . The data collected can then be used to understand the current state of a brand’s performance, identify improvements, and track the success of marketing initiatives.

• To what extent is Brand Z associated with innovation?
• How do consumers rate the quality of Brand Z’s products and services?
• How has the awareness of Brand Z changed over the past 6 months?
• How does Brand Z compare to its competitors in terms of customer satisfaction?
• To what extent do consumers trust Brand Z?
• How likely are consumers to recommend Brand Z?
• What factors influence consumers’ purchase decisions when considering Brand Z?
• What is the average customer satisfaction score for equity?
• How does equity’s customer service compare to its competitors?
• How do customer perceptions of equity’s brand values compare to its competitors?

Quantitative research question example and answer: brand tracking

🙋‍♀️ Question: How has the awareness of Brand Z changed over the past 6 months?

🤓 Insight sought: How has brand awareness changed for my business and competitors over time.

⏰ Time to insight: 2 minutes

✅ How it’s done: Using Similarweb’s search overview , I can quickly identify which brands in my chosen market have the highest brand awareness over any time period or location. I can view these stats as a custom market or examine brands individually.

Here, I’ve chosen a custom view that shows me five companies side-by-side. In the top right-hand corner, under branded traffic, you get a quick snapshot of the share of website visits that were generated by branded keywords. A branded keyword is when a consumer types the brand name + a search term.

Below that, you will see the search traffic and engagement section. Here, I’ve filtered the results to show me branded traffic as a percentage of total traffic. Similarweb shows me how branded search volumes grow or decline monthly. Helping me answer the question of how brand awareness has changed over time.

Quantitative research questions for consumer ad testing

Another example of using quantitative research to impact change and improve results is ad testing. It measures the effectiveness of different advertising campaigns. It’s often known as A/B testing , where different visuals, content, calls-to-action, and design elements are experimented with to see which works best. It can show the impact of different ads on engagement and conversions.

A range of quantitative market research questions can be asked and analyzed to determine the optimal approach.

• How does changing the ad’s headline affect the number of people who click on the ad?
• How does varying the ad’s design affect its click-through rate?
• How does altering the ad’s call-to-action affect the number of conversions?
• How does adjusting the ad’s color scheme influence the number of people who view the ad?
• How does manipulating the ad’s text length affect the average amount of time a user spends on the landing page?
• How does changing the ad’s placement on the page affect the amount of money spent on the ad?
• How does varying the ad’s targeting parameters affect the number of impressions?
• How does altering the ad’s call-to-action language impact the click-through rate?

Quantitative question examples for social media monitoring

Quantitative market research can be applied to measure and analyze the impact of social media on a brand’s awareness, engagement, and reputation . By tracking key metrics such as the number of followers, impressions, and shares, brands can:

• Assess the success of their social media campaigns
• Understand what content resonates with customers
• Spot potential areas for improvement
• How often are people talking about our brand on social media channels?
• How many times has our brand been mentioned in the past month?
• What are the most popular topics related to our brand on social media?
• What is the sentiment associated with our brand across social media channels?
• How do our competitors compare in terms of social media presence?
• What is the average response time for customer inquiries on social media?
• What percentage of followers are actively engaging with our brand?
• What are the most popular hashtags associated with our brand?
• What types of content generate the most engagement on social media?
• How does our brand compare to our competitors in terms of reach and engagement on social media?

Example of quantitative research question and answer: social media monitoring

🙋‍♀️ Question: How does our brand compare to our competitors in terms of reach and engagement on social media?

🤓 Insight sought: The social channels that most effectively drive traffic and engagement in my market

✅ How it’s done: Similarweb Digital Research Intelligence shows you a marketing channels overview at both an industry and market level. With it, you can view the most effective social media channels in any industry and drill down to compare social performance across a custom group of competitors or an individual company.

Here, I’ve taken the five closest rivals in my market and clicked to expand social media channel data. Wells Fargo and Bank of America have generated the highest traffic volume from social media, with over 6.6 million referrals this year. Next, I can see the exact percentage of traffic generated by each channel and its relative share of traffic for each competitor. This shows me the most effective channels are Youtube, Facebook, LinkedIn, and Reddit – in that order.

In 30-seconds, I’ve discovered the following:

• YouTube is the most popular social network in my market.
• Facebook and LinkedIn are the second and third most popular channels.
• Wells Fargo is my primary target for a more in-depth review, with the highest performance on the top two channels.
• Bank of America is outperforming all key players significantly on LinkedIn.
• American Express has found a high referral opportunity on Reddit that others have been unable to match.

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Examples of quantitative research questions for online polls.

This is one of the oldest known uses of quantitative market research. It dates back to the 19th century when they were first used in America to try and predict the outcome of the presidential elections.

Polls are just short versions of surveys but provide a point-in-time perspective across a large group of people. You can add a poll to your website as a widget, to an email, or if you’ve got a budget to spend, you might use a company like YouGov to add questions to one of their online polls and distribute it to an audience en-masse.

• What is your annual income?
• In what age group do you fall?
• On average, how much do you spend on our products per month?
• How likely are you to recommend our products to others?
• How satisfied are you with our customer service?
• How likely are you to purchase our products in the future?
• On a scale of 1 to 10, how important is price when it comes to buying our products?
• How likely are you to use our products in the next six months?
• What other brands of products do you purchase?
• How would you rate our products compared to our competitors?

Quantitative research questions for eye tracking studies

These research studies measure how people look and respond to different websites or ad elements. It’s traditionally an example of quantitative research used by enterprise firms but is becoming more common in the SMB space due to easier access to such technologies.

• How much time do participants spend looking at each visual element of the product or ad?
• How does the order of presentation affect the impact of time spent looking at each visual element?
• How does the size of the visual elements affect the amount of time spent looking at them?
• What is the average time participants spend looking at the product or ad as a whole?
• What is the average number of fixations participants make when looking at the product or ad?
• Are there any visual elements that participants consistently ignore?
• How does the product’s design or advertising affect the average number of fixations?
• How do different types of participants (age, gender, etc.) interact with the product or ad differently?
• Is there a correlation between the amount of time spent looking at the product or ad and the participants’ purchase decision?
• How does the user’s experience with similar products or ads affect the amount of time spent looking at the current product or ad?

Quantitative question examples for customer segmentation

Segmentation is becoming more important as organizations large and small seek to offer more personalized experiences. Effective segmentation helps businesses understand their customer’s needs–which can result in more targeted marketing, increased conversions, higher levels of loyalty, and better brand awareness.

If you’re just starting to segment your market, and want to know the best quantitative research questions to ask to help you do this, here are 20 to choose from.

Examples of quantitative research questions to segment customers

• What is your age range?
• What is your annual household income?
• What is your preferred online shopping method?
• What is your occupation?
• What types of products do you typically purchase?
• Are you a frequent shopper?
• How often do you purchase products online?
• What is your typical budget for online purchases?
• What is your primary motivation for purchasing products online?
• What factors influence your decision to purchase a product online?
• What device do you use most often when shopping online?
• What type of product categories are you most interested in?
• Do you prefer to shop online for convenience or for a better price?
• What type of discounts or promotions do you look for when making online purchases?
• How do you prefer to receive notifications about product promotions or discounts?
• What type of payment methods do you prefer when shopping online?
• What methods do you use to compare different products and prices when shopping online?
• What type of customer service do you expect when shopping online?
• What type of product reviews do you consider when making online purchases?
• How do you prefer to interact with a brand when shopping online?

Examples of quantitative research questions for analyzing customer segments

• What is the average age of customers in each segment?
• How do spending habits vary across customer segments?
• What is the average length of time customers spend in each segment?
• How does loyalty vary across customer segments?
• What is the average purchase size in each segment?
• What is the average frequency of purchases in each segment?
• What is the average customer lifetime value in each segment?
• How does customer satisfaction vary across customer segments?
• What is the average response rate to campaigns in each segment?
• How does customer engagement vary across customer segments?

These questions are ideal to ask once you’ve already defined your segments. We’ve written a useful post that covers the ins and outs of what market segmentation is and how to do it.

Additional applications of quantitative research questions

I’ve covered ten use cases for quantitative questions in detail. Still, there are other instances where you can put quantitative research to good use.

Product usage studies: Measure how customers use a product or service.

Preference testing: Testing of customer preferences for different products or services.

Sales analysis: Analysis of sales data to identify trends and patterns.

Distribution analysis: Analyzing distribution channels to determine the most efficient and effective way to reach customers.

Focus groups: Groups of consumers brought together to discuss and provide feedback on a particular product, service, or marketing campaign.

Consumer interviews: Conducted with customers to understand their behavior and preferences better.

Mystery shopping: Mystery shoppers are sent to stores to measure customer service levels and product availability.

Conjoint analysis: Analysis of how consumers value different attributes of a product or service.

Regression analysis: Statistical analysis used to identify relationships between different variables.

A/B testing: Testing two or more different versions of a product or service to determine which one performs better.

Brand equity studies: Measure, compare and analyze brand recognition, loyalty, and consumer perception.

Exit surveys: Collect numerical data to analyze employee experience and reasons for leaving, providing insight into how to improve the work environment and retain employees.

Price sensitivity testing: Measuring responses to different pricing models to find the optimal pricing model, and identify areas if and where discounts or incentives might be beneficial.

Quantitative market research survey examples

A recent GreenBook study shows that 89% of people in the market research industry use online surveys frequently–and for good reason. They’re quick and easy to set up, the cost is minimal, and they’re highly scalable too.

Questions are always formatted to provide close-ended answers that can be quantified. If you wish to collect free-text responses, this ventures into the realm of qualitative research . Here are a few examples.

Brand Loyalty Surveys: Companies use online surveys to measure customers’ loyalty to their brand. They include questions about how long an individual has been a customer, their overall satisfaction with the service or product, and the likelihood of them recommending the brand to others.

Customer Satisfaction Surveys: These surveys may include questions about the customer’s experience, their overall satisfaction, and the likelihood they will recommend a product or service to others.

Pricing Studies: This type of research reveals how customers value their products or services. These surveys may include questions about the customer’s willingness to pay for the product, the customer’s perception of the price and value, and their comparison of the price to other similar items.

Product/Service Usage Studies: These surveys measure how customers use their products or services. They can include questions about how often customers use a product, their preferred features, and overall satisfaction.

Here’s an example of a typical survey we’ve used when testing out potential features with groups of clients. After they’ve had the chance to use the feature for a period, we send a short survey, then use the feedback to determine the viability of the feature for future release.

Employee Experience Surveys: Another great example of quantitative data in action, and one we use at Similarweb to measure employee satisfaction. Many online platforms are available to help you conduct them; here, we use Culture AMP . The ability to manipulate the data, spot patterns or trends, then identify the core successes and development areas are astounding.

Read a connected post that shows 18 ways to use market research surveys .

How to answer quantitative research questions with Similarweb

For the vast majority of applications I’ve covered in this post, there’s a more modern, quicker, and more efficient way to obtain similar insights online. Gone are the days when companies need to use expensive outdated data or pay hefty sums of money to market research firms to conduct broad studies to get the answers they need.

By this point, I hope you’ve seen how quick and easy it is to use Similarweb to do market research the modern way. But I’ve only scratched the surface of its capabilities.

Take two to watch this introductory video and see what else you can uncover.

Added bonus: Similarweb API

If you need to crunch large volumes of data and already use tools like Tableau or PowerBI, you can seamlessly connect Similarweb via the API and pipe in the data. So for faster analysis of big data, you can leverage Similarweb data to use alongside the visualization tools you already know and love.

Similarweb’s suite of market intelligence solutions offers unbiased, accurate, honest insights you can trust. With a world of data at your fingertips, use Similarweb Digital Research Intelligence to uncover telling facts that help inform your research and strengthen your position.

Use it for:

Market Research

Benchmarking

Audience Insights

Company Research

Consumer Journey Tracking

Wrapping up

Today’s markets change at lightning speed. To keep up and succeed, companies need access to insights and intel they can depend on to be timely and on-point. While quantitative market research questions can and should always be asked, it’s important to leverage technology to increase your speed to insight, and thus improve reaction times and response to market shifts.

What is quantitative market research?

Quantitative market research is a form of research that uses numerical data to gain insights into the behavior and preferences of customers. It is used to measure and track the performance of products, services, and campaigns.

How does quantitative market research help businesses?

Quantitative market research can help businesses identify customer trends, measure customer satisfaction, and develop effective marketing strategies. It can also provide valuable insights into customer behavior, preferences, and attitudes.

What types of questions should be included in a quantitative market research survey?

Questions in a quantitative market research survey should be focused, clear, and specific. Questions should be structured to collect quantitative data, such as numbers, percentages, or frequency of responses.

What methods can be used to collect quantitative market research data?

Common methods used to collect quantitative market research data include surveys, interviews, focus groups, polls, and online questionnaires.

What are the advantages and disadvantages of using quantitative market research?

The advantages of using quantitative market research include the ability to collect data quickly, the ability to analyze data in a structured way, and the ability to identify trends. Disadvantages include the potential for bias, the cost of collecting data, and the difficulty in interpreting results.

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How to Write Quantitative Research Questions: Types With Examples

For research to be effective, it becomes crucial to properly formulate the quantitative research questions in a correct way. Otherwise, you will not get the answers you were looking for.

Has it ever happened that you conducted a quantitative research study and found out the results you were expecting are quite different from the actual results?

This could happen due to many factors like the unpredictable nature of respondents, errors in calculation, research bias, etc. However, your quantitative research usually does not provide reliable results when questions are not written correctly.

We get it! Structuring the quantitative research questions can be a difficult task.

Hence, in this blog, we will share a few bits of advice on how to write good quantitative research questions. We will also look at different types of quantitative research questions along with their examples.

Let’s start:

How to Write Quantitative Research Questions?

When you want to obtain actionable insight into the trends and patterns of the research topic to make sense of it, quantitative research questions are your best bet.

Being objective in nature, these questions provide you with detailed information about the research topic and help in collecting quantifiable data that can be easily analyzed. This data can be generalized to the entire population and help make data-driven and sound decisions.

Respondents find it easier to answer quantitative survey questions than qualitative questions . At the same time, researchers can also analyze them quickly using various statistical models.

However, when it comes to writing the quantitative research questions, one can get a little overwhelmed as the entire study depends on the types of questions used.

There is no “one good way” to prepare these questions. However, to design well-structured quantitative research questions, you can follow the 4-steps approach given below:

1. Select the Type of Quantitative Question

The first step is to determine which type of quantitative question you want to add to your study. There are three types of quantitative questions:

• Descriptive
• Comparative 
• Relationship-based

This will help you choose the correct words and phrases while constructing the question. At the same time, it will also assist readers in understanding the question correctly.

2. Identify the Type of Variable

The second step involves identifying the type of variable you are trying to measure, manipulate, or control. Basically, there are two types of variables:

• Independent variable (a variable that is being manipulated)
• Dependent variable (outcome variable)

If you plan to use descriptive research questions, you have to deal with a number of dependent variables. However, where you plan to create comparative or relationship research questions, you will deal with both dependent and independent variables.

3. Select the Suitable Structure

The next step is determining the structure of the research question. It involves:

• Identifying the components of the question. It involves the type of dependent or independent variable and a group of interest (the group from which the researcher tries to conclude the population).
• The number of different components used. Like, as to how many variables and groups are being examined.
• Order in which these are presented. For example, the independent variable before the dependent variable or vice versa.

4. Draft the Complete Research Question

The last step involves identifying the problem or issue that you are trying to address in the form of complete quantitative survey questions. Also, make sure to build an exhaustive list of response options to make sure your respondents select the correct response. If you miss adding important answer options, then the ones chosen by respondents may not be entirely true.

Types of Quantitative Research Questions With Examples

Quantitative research questions are generally used to answer the “who” and “what” of the research topic. For quantitative research to be effective, it is crucial that the respondents are able to answer your questions concisely and precisely. With that in mind, let’s look in greater detail at the three types of formats you can use when preparing quantitative market research questions.

1. Descriptive

Descriptive research questions are used to collect participants’ opinions about the variable that you want to quantify. It is the most effortless way to measure the particular variable (single or multiple variables) you are interested in on a large scale. Usually, descriptive research questions begin with “ how much,” “how often,” “what percentage,” “what proportion,” etc.

Examples of descriptive research questions include:

2. Comparative

Comparative research questions help you identify the difference between two or more groups based on one or more variables. In general, a comparative research question is used to quantify one variable; however, you can use two or more variables depending on your market research objectives.

Comparative research questions examples include:

3. Relationship-based

Relationship research questions are used to identify trends, causal relationships, or associations between two or more variables. It is not vital to distinguish between causal relationships, trends, or associations while using these types of questions. These questions begin with “What is the relationship” between independent and dependent variables, amongst or between two or more groups.

Relationship-based quantitative questions examples include:

Ready to Write Your Quantitative Research Questions?

So, there you have it. It was all about quantitative research question types and their examples. By now, you must have figured out a way to write quantitative research questions for your survey to collect actionable customer feedback.

Now, the only thing you need is a good survey maker tool, like ProProfs Survey Maker, that will glide your process of designing and conducting your surveys . You also get access to various survey question types, both qualitative and quantitative, that you can add to any kind of survey along with professionally-designed survey templates .

About the author

Emma David is a seasoned market research professional with 8+ years of experience. Having kick-started her journey in research, she has developed rich expertise in employee engagement, survey creation and administration, and data management. Emma believes in the power of data to shape business performance positively. She continues to help brands and businesses make strategic decisions and improve their market standing through her understanding of research methodologies.

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Opinion Stage » survey » Survey Questions

16 Types of Survey Questions, with 100 Examples

Good survey questions will help your business acquire the right information to drive growth. Surveys can be made up of different types of questions. Each type has a unique approach to gathering data. The questions you choose and the way you use them in your survey will affect its results.

These are the types of survey questions we will cover:

• Open-Ended Questions
• Closed-Ended Questions
• Multiple Choice Questions
• Dichotomous Questions
• Rating Scale Questions
• Likert Scale Questions
• Nominal Questions
• Demographic Questions
• Matrix Table Questions
• Side-by-Side Matrix Questions
• Data Reference Questions
• Choice Model Questions
• Net Promoter Score Questions
• Picture Choice Questions
• Image Rating Questions
• Visual Analog Scale Questions

But before we go into the actual question types, let’s talk a little about how you should use them.

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Ready to create your own?  Make a survey .

How to Use Survey Questions in Market Research

First, you need to make sure it’s a survey you’re after. In some cases, you may find that it’s actually a questionnaire that you need (read more here to learn the difference:  Survey Vs. Questionnaire ), or a research quiz. In any case, though, you will need to use the right type of questions.

To determine the right type of questions for your survey, consider these factors:

• The kind of data you want to gather
• The depth of the information you require
• How long it takes to answer the survey

Regardless of the size of your business, you can use surveys to learn about potential customers, research your product market fit, collect customer feedback or employee feedback, get new registrations, and improve retention.

Surveys can help you gather valuable insights into critical aspects of your business. From brand awareness to customer satisfaction, effective surveys give you the data you need to stay ahead of the competition.

So, how should you use surveys for your market research?

Try this market research survey

Ready to create your own?  Make a research survey .

Identify Customer Needs and Expectations

Perhaps the idea of using customer surveys in this advanced era of data analytics seems quaint. But one of the best ways to find out what consumers need and expect is to go directly to the source and ask. That’s why surveys still matter. All companies and online businesses can benefit from using market research surveys to determine the needs of their clients.

Determine Brand Attributes

A market research survey can also help your company identify the attributes that consumers associate with your brand. These could be tangible or intangible features that they think of when they see your brand. By determining your brand attributes, you can identify other brands in the same niche. Additionally, you can gain a clear understanding of what your audience values.

Understand Your Market’s Supply and Demand Chain

Surveying existing and potential customers enables you to understand the language of supply and demand. You can understand the measure of customer satisfaction and identify opportunities for the market to absorb new products. At the same time, you can use the data you collect to build customer-centric products or services. By understanding your target market, you can minimize the risks involved in important business ventures and develop an amazing customer experience.

Acquire Customer Demographic Information

Before any campaign or product launch, every company needs to determine its key demographic. Online surveys make it so much easier for marketers to get to know their audience and build effective user personas. With a market research survey, you can ask demographic survey questions to collect details such as family income, education, professional background, and ethnicity. It’s important to be careful and considerate in this area since questions that seem matter-of-fact to you may be experienced as loaded questions or sensitive questions by your audience.

Strategize for New Product Launches

Businesses of all sizes can use customer surveys to fine-tune products and improve services. Let’s say there’s a product you want to launch. But you’re hesitant to do so without ensuring that it will be well-received by your target audience. Why not send out a survey? With the data you gather from the survey responses, you can identify issues that may have been overlooked in the development process and make the necessary changes to improve your product’s success.

Develop a Strategic Marketing Plan

Surveys can be used in the initial phases of a campaign to help shape your marketing plan. Thanks to in-depth analytics, a quick and easy survey that respondents can finish within minutes can give you a clear idea of what potential consumers need and expect.

Create beautiful online surveys in minutes

Types of Survey Questions

No matter the purpose of your survey, the questions you ask will be crucial to its success. For this reason, it’s best to set the goal of your survey and define the information you want to gather before writing the questions.

Ask yourself: What do I want to know? Why do I want to know this? Can direct questions help me get the information I need? How am I going to use the data I gather?

Once you have a clear goal in mind, you can choose the best questions to elicit the right kind of information. We’ve made a list of the most common types of survey questions to help you get started.

1. Open-Ended Questions

If you prefer to gather qualitative insights from your respondents, the best way to do so is through an open-ended question. That’s because this survey question type gives respondents more opportunity to say what’s on their minds. After all, an open question doesn’t come with pre-set answer choices that respondents can select. Instead, it uses a text box where respondents can leave more detailed responses.

Ideally, you should ask such questions when you’re doing expert interviews or preliminary research. You may also opt to end surveys with this type of question. This is to give respondents a chance to share additional concerns with you. By letting respondents give answers in their own words, even to a single question, you can identify opportunities you might have overlooked. At the same time, it shows that you appreciate their effort to answer all your questions.

Since quantifying written answers isn’t easy to do, opt to use these questions sparingly, especially if you’re dealing with a large population.

Examples of open-ended questions:

• What can you tell us about yourself? (Your age, gender, hobbies, interests, and anything else you’re willing to share)
• How satisfied or dissatisfied are you with our service?
• What has kept you from signing up for our newsletter?

2. Closed-Ended Questions

Consumers want surveys they can answer in a jiffy. Closed-ended questions are ideal for market research for that reason. They come with a limited number of options, often one-word responses such as yes or no, multiple-choice, or a rating scale. Compared to open-ended questions, these drive limited insights because respondents only have to choose from pre-selected choices.

Ask closed-ended questions if you need to gather quantifiable data or to categorize your respondents. Furthermore, you can use such questions to drive higher response rates. Let’s say your audience isn’t particularly interested in the topic you intend to ask them about. You can use closed-ended questions to make it easier for them to complete the survey in minutes.

Close-ended question examples:

• Which of the following are you most likely to read? (a) a series of blog posts (b) a novel (c) the daily news (d) I don’t read on a regular basis
• How would you rate our service on a 5-point scale, with 1 representing bad service, and 5 representing great service?
• How likely are you to recommend us on a scale of 0 to 10?

3. Multiple Choice Questions

Multiple-choice questions are a basic type of closed-ended survey question that give respondents multiple answers to choose from. These questions can be broken down into two main categories:

• Single-answer questions – respondents are directed to choose one, and only one answer from a list of answer options.
• Multiple answer questions – where respondents can select a number of answers in a single question.

When designed correctly they can be very effective survey questions since they’re relatively simple questions to answer, and the data is easy to analyze.

Multiple-choice sample questions:

• It’s exceptional
• Could be better
• It’s terrible
• Whole-grain rice
• Gluten-free noodles
• Suger-free soft drinks
• Lactose-free ice cream

Try this product survey

Ready to create your own?  Make a product survey .

4. Dichotomous Questions

Dichotomous questions are a type of close-ended questions with only two answer options that represent the opposite of each other. In other words, yes/no questions, or true/false questions. They’re often used as screening questions to identify potential customers since they’re so quick and easy to answer and require no extra effort.

They’re also good for splitting your audience into two groups, enabling you to direct each group to a different series of questions. This can be done quite easily using skip logic which sends people on different survey paths based on their answers to previous questions.

Examples of questions:

Do you have experience working with Google Analytics? Yes/no Google Analytics is used for tracking user behavior. True/false Google Analytics has a steep learning curve for the average user. Agree/disagree

5. Rating Scale Questions

Also called ordinal questions, these questions help researchers measure customer sentiment in a quantitative way. This type of question comes with a range of response options. It could be from 1 to 5 or 1 to 10.

In a survey, a respondent selects the number that accurately represents their response. Of course, you have to establish the value of the numbers on your scale for it to be effective.

Rating scales can be very effective survey questions, however, the lack of proper survey scaling could lead to bad survey questions that respondents Don’t know how to answer. And even if they think you do, the results won’t be reliable because every respondent could interpret the scale differently. So, it’s important to be clear.

If you want to know how respondents experienced your customer service, you can establish a scale from 1 to 10 to measure customer sentiment. Then, assign the value of 1 and 10. The lowest number on the scale could, for instance, mean “very disappointed” while the highest value could represent “very satisfied”.

Examples of rating scale questions:

• On a scale of 0 to 10, how would you rate your last customer support interaction with us? (0=terrible, 10=amazing)
• How likely are you to recommend our company to a friend or colleague on a scale of 1 to 5? 1=very unlikely, 5=very likely
• How would you rate your shopping experience at our online business on a scale of 1 to 7? 1=bad, 4=ok, 7=amazing

6. Likert Scale Questions

These questions can either be unipolar or bipolar. Unipolar scales center on the presence or absence of quality. Moreover, they don’t have a natural midpoint. For example, a unipolar satisfaction scale may have the following options: extremely satisfied, very satisfied, moderately satisfied, slightly satisfied, and not satisfied.

Bipolar scales, on the other hand, are based on either side of neutrality. That means they have a midpoint. A common bipolar scale, for instance, may have the following options: extremely unsatisfied, very unsatisfied, somewhat unsatisfied, neither satisfied nor dissatisfied, somewhat satisfied, very satisfied, or extremely satisfied.

Likert scale questions can be used for a wide variety of objectives. They are great for collecting initial feedback. They can also help you gauge customer sentiment, among other things.

Likert scale sample questions:

• How important is it that you can access customer support 24/7? (Choices: Very Important, Important, Neutral, Low Importance, and Not Important At All)
• How satisfied are you after using our products? (Choices: Very Satisfied, Moderately Satisfied, Neutral, Slightly Unsatisfied, and Very Unsatisfied)
• How would you rate our customer care representative’s knowledge of our products? (Choices: Not at All Satisfactory, Low Satisfactory, Somewhat Satisfactory, Satisfactory, and Very Satisfactory)

Try this Likert scale survey

Ready to create your own?  Make a Likert scale survey .

7. Nominal Questions

Also a type of measurement scale, nominal questions come with tags or labels for identifying or classifying items. For these questions, you can use non-numeric variables. You can also assign numbers to each response option, but they won’t actually have value.

On a nominal scale, you assign each number to a unique label. Especially if the goal is identification, you have to stick to a one-to-one correlation between the numeric value and the label. Much like cars on a race track, numbers are assigned to identify the driver associated with the car. It doesn’t represent the characteristics of the vehicle.

However, when a nominal scale is used for classification, the numerical values assigned to each descriptor serve as a tag. This is for categorizing or arranging the objects in a class. For example, you want to know your respondents’ gender. You can assign the letter M for males and F for females in the survey question.

Examples of nominal questions:

• What is your hair color? (Choices: 1 – Black, 2 – Blonde, 3 – Brown, 4 – Red, 5 – Other)
• How old are you? (Choices: 1 – Under 25, 2 – 25-35, 3 – Over 35)
• How do you commute to work? (Choices: 1- Car, 2 – Bus, 3 – Train, 4 – Walk, 5 – Other)

8. Demographic Questions

As its name suggests, this question type is used for gathering information about a consumer. From their background to income level, these simple questions can provide you with deeper insights into your target market. They’re also used as screening questions since they can help you to identify the population segments you’re targeting.

Demographic questions  help you understand your target market. By collecting customer data, you can identify similarities and differences between different demographics. Then, you can make buyer personas and classify them based on who they are or what they do.

Some demographic topics can lead to quite loaded survey questions. When writing your demographic survey, try to identify the loaded questions and ask yourself if someone could find the question, the answer choices, or the lack of a certain answer choice offensive. Do your best to phrase them sensitively and respectfully, and if you can’t consider leaving them out.

With every single question that you write, it’s important to place yourself in the shoes of your respondents. If you want to ask students about their income, your response options should range below $20,000 per year, because most of them are probably not making more than that. But if your respondents are affluent, your choices should have a range higher than $100,000.

Examples of demographic questions:

• How old are you?
• What is your level of education?
• What is your marital status?
• What’s your current employment status?

Try this demographic survey

Ready to create your own?  Make a demographic survey .

9. Matrix Table Questions

If you need to ask a series of questions that require the same response options, you can group them together in a matrix table instead of breaking them into separate questions.

While these bundled questions are convenient, you have to use them carefully. Visually, large matrix tables can seem overwhelming. In addition, online survey questions of this sort aren’t always mobile-friendly. Having too many questions or choices may even trigger undesirable survey-taking behavior such as straight-lining. This is when respondents select the same options without carefully considering each one. Sometimes, they do that because the actual experience feels like a complicated matrix and they just want to finish it.

Example of a matrix table:

How satisfied or dissatisfied are you with the following?

Interaction with sales staff

Product selection

Marketing messages

Pricing structure

Then, you can make a brief list of response options. There should be no more than five options.

10. Side-by-Side Matrix Questions

A side-by-side matrix is similar to your regular matrix table in that it allows you to group together questions that require simple response options. However, a matrix table only lets you collect data from a single variable. A side-by-side matrix, on the other hand, enables you to gather data on two or more dimensions.

For example, let’s say you want to ask respondents about the importance of different services and their satisfaction with each. You can group them together in a side-by-side matrix. By organizing questions in tables, your respondents can easily fill out the survey in minutes.

Much like a regular matrix table, you shouldn’t overwhelm consumers. Avoid adding too many variables to your table. Moreover, you should keep the response options short.

Examples of side-by-side matrix questions:

Example of side-by-side matrix:

How would you rate our shopping services?

Identify the variables. They can be customer support, packaging, and punctuality. Next, you should add different dimensions such as importance and satisfaction level. On each table, you should add a similar scale. You can start with 1, which could mean Not Important and Not Satisfied.

11. Data Reference Questions

Use data reference questions to gather validated data against standardized databases. For example, direct respondents to enter their postal code or zip code in a small text box. The value entered will then be cross-referenced with the database. If it is correct, their city or state will be displayed, and they can proceed with the survey. And if it is incorrect, they’ll be asked to enter a valid postal code or zip code.

Examples of data reference questions:

• What is your five-digit zip code?
• What is your postal code?

12. Choice Model Questions

Choice model questions enable you to understand the essential aspects of consumers’ decision-making process. This involves a quantitative method called Conjoint Analysis. It helps you grasp your users’ preferences, the features they like, and the right price range your target market can afford. More importantly, it enables you to understand if your new products will be accepted by your target market.

These questions also involve Maximum Difference Scaling, a method that allows the ranking of up to 30 elements. This can include product features, benefits, opportunities for potential investment, and possible marketing messages for an upcoming product.

Example of a choice model question:

• If you were to buy a sandwich, which ingredient combination would you choose?

Let’s say you want to know about consumers’ bread, filling, and sauce preferences. In your survey, you can give them three sandwich options. You can, for instance, offer three kinds of bread: grain wheat, parmesan oregano, and Italian. As for the sauces, you can make them choose between ranch, blue cheese, and mustard. Finally, you need to suggest three types of filling, for example, chicken, veggies, and meatballs.

Respondents will see unique combinations of these ingredients in your survey. Then, they will have to choose the one that they like best.

13. Net Promoter Score Questions

A net promoter score (NPS) survey question measures brand shareability, as well as customer satisfaction levels. It helps you get reliable customer insights and gauge the likelihood of respondents recommending your company to friends or colleagues (i.e. prospective customers). The scoring model involves a scale of 0 to 10, which is divided into three sections. Respondents who give a 9 to 10 score are considered Promoters. Passives give a 7 to 8 score, while the rest are considered Detractors.

Once you’ve gathered all the data, the responses per section are calculated. Then, the net value of promoters is shown. This type of survey question offers a useful form of initial feedback. It helps you understand why promoters are leaving high ratings so you can work on enhancing those strengths. At the same time, it enables you to determine weaknesses. It illustrates why detractors are leaving such low ratings.

Examples of net promoter score questions:

• On a scale of 0 to 10, how likely are you to recommend our brand to a friend or colleague? (0 = Not at all Likely and 10 = Very Likely)
• Would you encourage friends to work at our company?
• How likely are you to recommend (specific name of the product) to friends?

Try this NPS survey

Ready to create your own?  Make an NPS survey .

14. Picture Choice Questions

It’s no secret that people respond to visual content more than plain text. This applies to surveys as well – visual content can boost user experience.

Think of these as alternate questions to multiple-choice questions. Users can pick one or many from a visual list of options. You can use picture choice questions to make your survey more engaging.

Keep in mind, that it’s very easy to unintentionally create a leading question by using images that get a specific reaction from people. For example, if you’re asking about food preferences and one of the images is more attractive than others, people may see it as the perfect answer even if it doesn’t represent their favorite dish because it looks most attractive. So when you’re illustrating a variety of answers with images make sure their quality and attractiveness is similar.

Picture choice examples:

• What is your favorite pizza topping?
• Which color should we choose for our logo?
• What other products would you like to see in our online store?

Opinion Stage has an online  survey maker  tool that can help you design image-based survey questions in minutes. Choose from hundreds of professionally-designed templates, and tailor them to fit your needs, or design them from scratch.

Try this visual survey

Ready to create your own?  Make a visual survey .

15. Image Rating Questions

Another way to incorporate images in questions is through image ratings. Let’s say you want to know how satisfied consumers are with your products. You can display all of the items you want respondents to rate. Under each item, provide a shortlist of options (e.g. very unsatisfied, unsatisfied, neutral, satisfied, very unsatisfied).

You could also use a rank order question to let your respondents rank their favorite products. Simply give them multiple options, and then, ask them for their top three or five favorites. Or you could ask them to organize a series of answers by ranking.

For example, if it’s an employee engagement survey question you could ask your employees to rank a series of office activities from their least favorite to their most favorite. There are many ways to do this visually. Some tools use dropdown menus, and others let you move the answer options around, but the simplest way is to use numbers like in the example below.

Rank order questions should work well on mobile devices. After all, respondents only have to tap on their favorite items to participate.

Example of image rating questions:

• What are your 5 favorite desserts?

16. Visual Analog Scale Questions

Another type of scale you can use in a survey is the visual analog scale, which displays your questions in a more engaging manner. For instance, you can use text sliders or numeric sliders to ask respondents to rate the service they’ve received from your company and let them select an image line that best illustrates their answer.

You can also use pictures to depict each option. Smiley ratings are commonly used in surveys nowadays because they’re simple questions, easy on the eyes, and quite fun. Star ratings are also effective survey questions that require no extra effort.

Examples of visual analog scale questions:

• How would you rate the overall quality of our customer service?
• What do you think of our website’s interface?
• How satisfied are you with the way our service works in offline mode?

Create engaging image-based surveys in minutes

The Fundamentals of Good Survey Questions

There is an art to writing effective questions for your survey. Regardless of the kind of survey you plan to deploy, there are a few practices that you should adhere to.

Use Clear and Simple Language

Always choose clear and simple words when writing your online survey questions. In doing so, you can keep the questions short yet specific.

Complex phrasing, too many words, acronyms, and specialized jargon require extra effort and could cause confusion. Make it easy for your respondents to help you. Keep it simple.

Moreover, avoid  double-barreled questions , they will frustrate your respondents and skew your customer insights.  Here’s an example of a double-barreled question: “Did you find our new search feature helpful and easy to use? yes/no” Such a question might be simple to understand, but it isn’t easy to answer because it covers two issues. How could someone respond if they found the search feature helpful but difficult to understand? It would make more sense to separate it into two questions, i.e. did you find the new search feature helpful? Was the new search feature easy for you to use?

Focus on the Consumer

Make the survey engaging. Use the second-person (i.e., ‘you’ format) to address your respondents directly, and use the first-person (i.e., ‘we’ format) to refer to your company. This makes the survey more personal and helps respondents recall prior experiences with your company. In turn, it leads to quicker and more accurate answers.

Ask for Feedback

Get initial feedback from external people that fit the profile of your average user before sending your survey out. It’s like a user testing tool, you need someone who isn’t you to take a look and tell you if your survey is clear and friendly.

Require Minimal Effort to Answer

There’s no reason to ask people questions that aren’t essential to you. Ask people questions that really matter to you, and try to keep it down to the minimum number, so as not to waste their time. The more succinct a survey is, the more likely a respondent is to complete it. So, let them know that you value their time by designing a survey they can finish within minutes.

Stay Free From Bias

Survey question mistake #1 is to ask leading or biased questions. Don’t plant opinions in your respondents’ heads before they can formulate their own. Don’t ask people questions like “How good was your in-store experience today?” Phrase it in a neutral way like “On a scale of 1 to 10, how would you rate your in-store experience?”

Keep the Purpose of the Survey Vague

Sometimes, respondents have a tendency to give you the answers you want to hear. One of the simplest ways to prevent that is by keeping the purpose of your survey vague. Instead, you should give a general description of your survey.

Get a personalized survey up and running today

Sample Survey Questions

Below are sample questions for different market research needs. You can use many of them as close-ended questions as well as open questions, depending on your need and preference.

Brand Awareness Questions

• When was the last time you used (a type of product)?
• What brands come to mind as your top choice when you think of buying this product type?
• What factors do you consider when selecting a vendor? (rank by importance)
• Which of the following brands have you heard of? (please select all that apply)
• Where have you seen or heard of our brand in the last three months? (please select all that apply)
• How often have you heard people talking about our brand in the past three months?
• How familiar are you with our company?
• On a scale of 1 to 10, how likely are you to recommend our brand to a friend?

Customer Demographic Questions

• What gender do you identify as?
• Where were you born?
• Are you married?
• What is your annual household income?
• Do you support children under the age of 18?
• How many children under the age of 18 reside in your household?
• What category best describes your employment status?
• Which general geographic area of the state do you reside in?
• What is your current employment status?
• Which of the following languages can you speak fluently?

Brand & Marketing Feedback Questions

• Have you purchased from our company before?
• How long have you been a customer?
• Which best describes your latest experience with our brand? (please select all that apply)
• Which of the following attributes do you associate with our brand? (please select all that apply)
• What kind of feelings do you associate with our brand?
• Which of these marketing messages represents us best in your opinion?
• How would you rate your level of emotional attachment to our brand?
• What five words would you use to describe our brand to a friend or colleague?
• On a scale of 1 to 10, how likely are you to recommend our brand to a friend or colleague? (1 being Not at All Likely at 10 being Extremely Likely)

Product & Package Testing Questions

• What is your first impression of the product?
• How important are the following features to you?
• How would you rate the product’s quality?
• If the product was already available, how likely are you to purchase it?
• How likely are you to replace an old product with this one?
• How likely would you recommend this product to a friend or colleague?
• What did you like best about this product?
• What are the features that you want to see improved?
• Based on the value for money, how would you rate this product compared to the competition?
• What is your first impression of the product packaging?
• How satisfied or dissatisfied are you with the following features? (Visual appeal, Quality, and Price)
• How similar or different is the packaging from the competition?
• Does the packaging have too little or too much information?
• How likely are you to purchase the product based on its packaging?
• What did you like best about the packaging?
• What did you dislike about the packaging?
• How would you like the packaging to be improved?

Pricing Strategy Testing Questions

• How often do you purchase this type of product?
• What brands do you usually purchase? (Please select all that apply).
• On a scale of 1 to 5, how satisfied are you with the pricing of this type of product? (1 being Not at All Satisfied at 5 being Extremely Satisfied)
• What is the ideal price for this type of product?
• What price range would make you consider that the product is too expensive?
• At what price is the product too cheap that its quality is questionable?
• How much does the price for our product compare to other products on the market?
• If the product was available, how likely would you be to purchase it?

Customer Satisfaction Questions

• How would you rate the following products/services at (name of company)?
• Which of the following attributes would you use to describe our product/service? Please select all that apply.
• Would you recommend our company to a friend or colleague? (1 being Very Unlikely and 10 being Very Likely)
• How responsive has our support team been to your questions and concerns?
• How likely are you to purchase from our company again?
• What other comments, concerns, or questions do you have for us?

Brand Performance Questions

• When was the last time you used this type of product?
• When you think of our brand, what words come to mind?
• Which of the following are important to your decision-making process?
• How well do our products perform based on the following categories? (Price, Quality, Design, etc.)
• How well does our product meet your needs?
• What was missing or disappointing about your experience with our brand?
• What did you like most about your experience with our brand?
• How can we improve your experience?

Customer Behavior Questions

• In the household, are you the primary decision maker when it comes to purchasing this type of product?
• When was the last time you purchased this product type?
• How do you find out about brands offering this product type? Please select all that apply.
• When you think of this product type, which of the following are the top three brands that come to mind?
• How much of your purchasing decisions are influenced by social media?

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How to Improve Survey Response Rates

Every market research survey needs to be designed carefully in order to drive higher response rates. As a result, you can acquire the right data to inform the decision-making process.

Here are a few survey ideas to boost response rates:

Make It Personal

Write a survey as if it’s a conversation between you and your respondents. For example, use first-person pronouns to make your surveys feel more personal and customer-centric. In addition, stick with simple and specific language to better connect with respondents. Simply put, write your questions as you’d use them in a conversation with consumers.

Make It Engaging

Gathering data from consumers is essential to any business, but market research surveys don’t have to be dull. You can engage and connect with respondents on a human level through an interactive survey. As a result, you can obtain thorough responses and maximize the number of respondents that complete the entire survey.

Don’t Waste Their Time

No one wants to answer a survey with 50 questions because it takes too long to complete. Hence, you should narrow down your list to the most important ones. Only ask questions that will lead to actionable insights. As for the rest, you can get rid of them.

Offer Incentives

There are two types of incentives you can offer: monetary or non-monetary. Either way, you need to make sure that the incentive provides value to your target audience. In addition, you must choose between promised or prepaid incentives. In other words, you have to decide if you want to offer everyone or a small group of people some incentives.

Providing respondents with incentives to finish the survey can increase response rates—but not always. Customer satisfaction surveys, for example, won’t always need incentives because it might affect the quality of the results.

Make It Responsive

Perhaps the easiest way to gain respondents is to make your surveys responsive and mobile-optimized. In doing so, it will perform well and look amazing on all devices. It should also enable you to reach consumers during their daily commute or lunch break. Thus, make sure your survey is optimized for different kinds of devices, especially for mobile.

Offer Surveys in Multiple Channels

If a survey is optimized for all device types, it should be easily accessed on social media. So, take advantage of your platforms and share your survey on different social media channels to increase participation rates.

Designing surveys doesn’t have to be challenging. On the contrary, you can easily create interactive surveys with Opinion Stage. Create a survey from scratch, or choose one of our many professionally-made templates to complete it within minutes. Through Opinion Stage, you can drive higher response rates and evaluate results from a powerful analytics dashboard.

It’s important to be familiar with the different types of survey questions and when to use them. Getting to know each survey question type will help you improve your research. Not to mention, you can gain high-quality data when you design a survey with the right types of questions .

In addition, you should leverage the right tool to create engaging surveys in minutes. With an online survey maker like Opinion Stage, you can customize your surveys to fit your brand image. Or, you can choose from professionally-made templates. Either way, it can help boost response rates.

Last but not least, check your survey design before deploying it. Make sure to see what your survey will look like to your respondents. See opportunities for improvement, then apply the necessary changes.

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• Market Research

Quantitative research question examples

One of the best ways to determine how your target audience feels about your company or organization is through quantitative research. Once you understand user opinions, attitudes, behaviors, preferences, and market trends, you can make informed decisions that help you improve your products, services, and every aspect of the customer experience.

In this post, we’ll review what a quantitative research question is, cover the types of quantitative research questions, share examples of quantitative research questions across various fields, and highlight tips for creating a quantitative research survey.

Some background on quantitative research questions

Quantitative research questions collect objective, measurable, numerical data through

• Surveys and questionnaires
• Controlled observations
• Reviewing existing research to produce sound statistical analysis

The data includes ratings, counts, measurements, and percentages. Because this data is objective, it’s considered more reliable than qualitative research data.

Quantitative data helps researchers identify trends and patterns. They can use these insights to make informed decisions about company or organizational goals, targets, and strategic improvements to undertake.

Quantitative research questions are useful for measuring many things, but businesses commonly use them to determine overall customer satisfaction , gather feedback on existing products and services, gauge the demand for new products and services, and decide on business improvements to roll out.

Some examples of quantitative research questions include

• How many times per week do you use social media?
• How often do you visit our website?
• How many mobile shopping apps do you use?

Types of quantitative research questions

The three main types of quantitative research questions are descriptive, comparative, and relationship-based. Which type or types you use will depend on the kind of data you want to collect and your research objective.

Descriptive research questions are usually closed-ended, and they elicit participants’ opinions about a specific variable. With these questions, you may ask how often someone uses your product, when they use your product, or how much they’d be willing to pay for a specific product.

Comparative research questions consider differences between groups based on dependable variables. With these questions, you may want to compare brand preferences among men versus women, compare how often individuals use similar products, or assess how your products stack up against competitors’ offerings.

Relationship-based research questions are helpful for gauging trends, causal relationships, or connections between variables. You may develop questions that help you explore how color influences buying decisions for a product or assess the relationship between employee turnover and workplace environment.

Examples of quantitative research questions

Now let’s take a look at some examples of quantitative research questions in the fields of education, health, marketing, and social sciences.

Examples of quantitative research questions in education

• On a scale of 1 to 10, how much does parental participation in education impact student academic achievement?
• What impact does classroom size have on academic performance? Choose from the following: no impact, limited impact, high impact.
• How many times were you (the student) absent last semester?
• Is the relationship between extracurricular activities and student performance positive, negative, or neutral?
• On a scale of 1 to 5, how much do study habits impact student grades and test scores?

Examples of quantitative research questions in the mental and physical health fields

• On a scale of 1–10, how often do you feel stressed?
• How many times per week do you engage in activities to improve your mental well-being?
• How frequently do you exercise?
• Do you have a health insurance plan?
• How would you rate the care you received on your last visit with a primary care provider?
• What is the relationship between stress levels and physical health in retirees?
• On average, how many times per year do you visit a healthcare provider or facility?

Examples of quantitative research questions in marketing

• How often do you make buying decisions based on advertising or marketing campaigns?
• How often do you use products in this category?
• On a scale of 1–10, how satisfied are you with the quality of this product?
• On a scale of 1–10, how likely are you to recommend this product to others?
• How much are you willing to pay for this product?
• Which product features are the most important to you when making buying decisions in this category?
• How much do customer reviews impact your buying decisions?
• What is your preferred way to purchase products in this category (online or in the store)?

Examples of quantitative research questions in social sciences

• On a scale of 1 to 10, how much does income inequality impact academic performance?
• To what extent is there still a gender imbalance in pay/wages? Rate your answer on a scale of 1 to 5.
• To what degree does race impact rates of mental health diagnosis in adults? Rate your answer on a scale of 1 to 5.
• Does gender affect an individual’s contribution to household tasks?

Tips for creating quantitative research questions

Now that we’ve seen some examples, let’s review a few tips for creating your own quantitative research questions.

Since you’re looking for concrete data, ask questions such as

• What percentage?
• What proportion?

Let’s look at some concrete examples:

• How much is your weekly grocery budget?
• How many times per month do you visit a brick-and-mortar store?
• What percentage of your monthly income is spent on housing?

To increase the quality of your questions and ensure the best results

• Use different question types (i.e., descriptive, comparative, relationship-based).
• Keep the survey or questionnaire as short as you can without sacrificing data collection.
• Don’t use leading or biased questions.
• Use clear language and avoid jargon.
• Address one topic per question, starting with easier questions first to build momentum.
• Be sure to get approvals and informed consent before proceeding.

How to create a quantitative research survey

• Select the type of quantitative research question or questions from among the three discussed above — descriptive, comparative, or relationship-based — based on your research objective.
• Identify the type of variable you’re trying to measure — either independent (the variable being manipulated) or dependent (the outcome variable) — and the target audience. Measurement variables include nominal, ordinal, interval, and ratio.
• Decide on the structure of your research questions based on the type of questions you’ll be presenting. Structure pertains to variables, groups, and the order of the variables and groups in the questions.
• Draft your research questions and finalize your survey.

If you’re interested in learning more, we offer a more in-depth look at quantitative market research best practices . Also, check out our detailed, step-by-step guide on how to do market research .

You can build beautiful, easy-to-use, fully customizable surveys using Jotform’s premade survey templates or create them from scratch — no coding required. Tailor your surveys to match your business and your specific goals, and even share, collect, and analyze your survey results with our free online survey maker .

If you want to gather invaluable insights into user behavior, opinions, attitudes, and preferences, quantitative research is a great way to go about it. Jotform’s robust survey and questionnaire tools make it easy to get started.

Photo by ODISSEI on Unsplash

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• How to ask quantitative survey questions: types & examples

Eren Eltemur

Are you looking for a way to collect objective data for your research? You can use quantitative questions to get objective data. You can use forms.app to create and customize your surveys with ready-made templates. This article will discuss creating quantitative survey questions with forms.app and the key principles of creating quantitive survey questions.

• What is a quantitative question?

A quantitive question is an objective question about any kind of research topic. You can use these types of questions in your research surveys, and you can create a research repor t that is produced using the quantitative data based on the analysis of the responses to these quantitative survey questions.

It offers assistance when you need to generalize your study and make predictions about the future. Surveys are an excellent instrument for quantitative research because they are flexible, affordable, and allow data collection from many respondents. Quantitive questions allow researchers to collect numeric data , and it is a method to gather statistical results . 

The definition of a quantitative question

Quantitative and qualitative survey questions

The goal of quantitative research is to gather data that can be represented statistically. Researchers frequently use it to compare information about particular groups . Quantitative research can be directed towards a particular audience, generally identified by demographic data like age, gender, and region , even though the survey audience is relatively large. 

Qualitative research focuses on individuals' unique behavior , including their routines or the reasons behind their choices. To understand more about sentiments, attitudes, and behaviors that are harder to measure but provide crucial extra context to quantitive research.

• 3 Types of quantitative survey questions

Quantitive questions and their equıvelent of survey questions can be separated on a basis. The branches of quantitative questions are methods, but when you want to include these principles in your surveys, you use form builder features such as the Likert scale, open-ended questions, opinion scale, multiple choice, short text, and long text . In the end, what gives meaning to these types of questions is their way of gathering answers . Here are the types of quantitive questions and their branches: 

• Descriptive research questions : To make a general assumption about a group of people, such as their age, sex, and maybe ethnicity, or commonly used products, researchers can use these types of questions. There are common types of descriptive research questions: 
• Frequency questions : To understand how often a particular event occurs.
• Percentage questions : To determine the proportion of a group, such as customers.
• Range questions : To find the highest and the lowest point of something, such as price.
• Profile questions : To describe a characteristic of a particular group.
• Case study questions : To get a detailed understanding of a specific topic.
• Comparative research questions : These types of questions are used to compare individuals or groups and can be classified as experimental or casual research.
• Experimental : Used to test the cause-and-effect relationship of a hypothesis by interventions and manipulations.
• Causal : To comprehend how variations in one variable affect another.
• Relationship-based research questions : These types of questions are used to understand the link between two groups or topics. Here are some types of relationship-based research questions:
• Correlation questions : Used to test the cause-and-effect relationship of a hypothesis without any interventions and manipulations.
• Meta-analysis : The combined result of multiple similar studies to find patterns and inconsistencies.
• Cross-sectional : The relationship between two things at a particular time to find a correlation.
• Case-control : Regardless of the outcome, the relationship between particular outcomes to find patterns.
• How to write better quantitative survey questions

Creating a better quantitative survey can be a complicated task because of the survey's nature. The intention of the questions must be chosen first to get the desired result. Clear, effective and unbiased survey questions are essential for quantitive surveys. For this reason, here is the three-step you must follow to get the desired result:

1 - Select the objective and type

You must select the type of question you want to ask. What is your intention? Are they descriptive, comparative, or relationship-based questions? By choosing your intention, you can ask the right questions and select the right words, which is the key element of your survey .

2 - Identify the variable

The dependent and independent variables, as well as the target audiences , should be decided by researchers. The many variables you seek to analyze, manipulate, or control must be identified regardless of whether you are trying to develop a descriptive, comparative, or relationship-based research question. Here are some examples for 

variables: Number of books read per year, level of education, average working hours, and time spent on social media .

You can control a variable in addition to something you can measure. You might need to assess a few dependent variables if you merely intend to develop descriptive research questions. However, you will deal with dependent and independent variables in situations where you intend to create comparative and relationship-based research questions. In an experiment, an independent variable is a variable that is changed to observe the effect.

3 - Select the appropriate structure

The aims of the questions, the types of variables, the number of variables and the groups engaged all have an influence on the structure of the three different types of quantitative research questions.

a.   Select your lead phrase.

b.   Specify the dependent variable.

c.   List the organizations in which you are interested.

d.   Choose whether to include the dependent variable or groups.

• 16 great quantitative survey question examples

To make the steps and types clear as forms.app, we have gathered 16 quantitive question examples in surveys. Below you will see comparative, descriptive, and relationship-based research questions with specified variables and groups.

1  - What is the average life expectancy of individuals living in urban areas compared to the average life expectancy of individuals living in rural areas? 

• Question type : Comparative
• Variable : life expectancy
• Groups :  "urban" and "rural"

2  - What is the average number of sick days taken by employees who work more than 40 hours per week compared to employees who work less than 40 hours per week? 

• Variable : Number of sick days taken
• Group : employees who work more than 40 hours per week and employees who work less than 40 hours per week

3  - What is the average height of adults in [ Asians ]? 

• Question type : Descriptive
• Variable : Average height
• Group : Asians

4  - What is the average number of books read per year by people aged 18-24 compared to people aged 25-34? 

• Variable : Number of books read per year
• Group : people aged 18-24, people aged 25-34

  5  - What is the average number of cars per household in a [ specific country ]? 

• Variable : average number of cars per household
• Group : specific country

6  - What is the average temperature [ in a specific city ] during the month of July? 

• Variable : average temperature
• Group : specific city, the month of July

 7  - Is there a relationship between exercise frequency and weight loss? 

• Question type : Relationship
• Variable : Exercise frequency, Weight loss
• Group : n/a

  8  - Is there a relationship between air pollution and lung cancer? 

• Variable : Air pollution, Lung cancer

  9  - Is there a relationship between the level of education and average credit score? 

• Variable : Level of education, Average credit score

10  - What is the average number of customers served per hour at fast food restaurants in the city center compared to fast food restaurants in the suburbs? 

• Variable : Number of customers served per hour
• Group : fast food restaurants in the city center, fast food restaurants in the suburbs

  11  - What is the average age of business owners in a specific region? 

• Variable : average age
• Group : business owners in a specific region

12  - What is the average commute time for residents who use public transportation compared to residents who drive alone? 

• Variable : Commute time
• Group : Residents who use public transportation and residents who drive alone

13  - Is there a relationship between social media usage and academic performance among college students? 

• Variable : Social media usage, academic performance
• Group : College students

  14  - What is the average time spent on social media per day among teenagers compared to adults? 

• Variable : Time spent on social media per day
• Group : Teenagers and Adults

  15  - What is the average revenue per year for small business owners compared to large business owners? 

• Variable : Revenue per year
• Group : Small business owners and large business owners

16  - Is there a relationship between gender and the likelihood of receiving a promotion in a specific company? 

• Variable : Gender, the likelihood of receiving a promotion
• Group : specific company
• How to design a quantitative survey

Since the elements are clear now, you must clarify your topic and style, then create your survey considering your aim. For example , let's say we are creating a survey intended to learn about gender and its relationship with receiving a promotion. Our variable is gender and the likelihood of receiving a promotion, and our group is a particular company. Here are some example questions with suitable form fields you can use:

• How satisfied are you with the current position? (Opinion scale)
• My skills and abilities find use in my job position. (Star rating)
• I am satisfied with my current working hours.  (Star rating)
• When did you get hired by this company? (Short text)
• Are there any inequalities between male and female workers? (Yes/no)
• How likely will you be working for this organization a year from now? (Opinion scale)
• How stressed do you feel on a regular day at work? (Opinion scale)
• I feel that my work is seen and appreciated within my organization. (Yes/no)
• My job allows me to grow and develop new skills. (Yes/no)
• Do you think there is a relationship between gender and the likelihood of receiving a promotion in this company? (Yes/no)
• Create your quantitative survey today

It can be hard to create quantitive research questions if you are unfamiliar with the method. For this reason, forms.app gathered the detailed key method of creating quantitive survey questions. You can use ready-made templates to start or just from scratch since you now know how to create your quantitive survey questions. If you want to get started quickly, take a look at these:

Restaurant Review Survey

Employee Satisfaction Survey Template

App Evaluation Form

• Form Features
• Data Collection

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Quantitative Survey Questions: Craft Powerful Surveys for Data-Driven Insights

• Author Survey Point Team
• Published March 12, 2024

Are you tired of surveys that give you vague answers and leave you scratching your head? If you want clear, actionable insights to fuel your business decisions, quantitative surveys are the way to go. But how do you design surveys that actually deliver the data you need?

Let’s dive in and explore how to craft powerful quantitative survey questions that will transform your data collection efforts.

Table of Contents

Understanding Quantitative Survey Questions

At their core, quantitative survey questions deal with numbers and measurable data.  They’re designed to uncover trends, preferences, and behaviors across your target audience. Think of questions like:

• How many times per week do you exercise?
• On a scale of 1-10, how satisfied are you with our product?
• Which of these features is most important to you?

The beauty of quantitative surveys is that they leave less room for interpretation, making your results clearer and easier to translate into action.

Why Do Quantitative Survey Questions Matter?

Data is king in today’s business world. Here’s where quantitative surveys shine:

Decision-making confidence: Take the guesswork out of your choices. Make informed decisions backed by hard numbers.

Pinpoint trends: Track changes in customer preferences, market shifts, and identify areas where your business can improve.

Measure progress: See if your strategies are working. Numbers provide clear benchmarks for measuring success.

Uncover hidden insights: Dig beneath the surface responses to reveal patterns and connections that you might otherwise miss.

The Art of Effective Quantitative Survey Design

Ready to unleash the power of data? Here’s your roadmap for building effective quantitative surveys:

1. Define Your Goals

Don’t just throw questions together! What do you really want to know? Are you exploring customer satisfaction, market trends, or product preferences? Get crystal clear on your objectives – they’ll guide your entire survey design.

2. Know Your Audience

Who are you trying to reach? Tailor your questions and language to resonate with your target respondents. Avoid jargon or overly complex wording that could put people off.

3. The Power of Question Types

Get familiar with the various quantitative question formats and when to use them:

Multiple Choice: Great for providing specific options (e.g., “What’s your age range?”)

Likert Scale: Measure attitudes and opinions (e.g., “Strongly disagree” to “Strongly agree”)

Ranking Questions: Prioritize features or preferences (e.g., “Rank these features in order of importance.”)

Open-Ended Numerical: Gather specific data when the answer won’t fit neatly into predefined options (e.g., “How much do you spend on groceries per month?”)

4. Keep it Simple and Focused

People have short attention spans!  Your survey should be easy to understand and quick to complete. Here’s how:

Short and sweet questions: Avoid long, convoluted sentences.

Logical flow: Group similar questions together.

Limit open-ended questions: While sometimes necessary, use them sparingly as they take more effort for respondents.

5. Test, Test, Test!

Before launching your survey, test it with a small group to ensure clarity and that you’re getting the type of data you need. Make adjustments as necessary.

Common Mistakes to Avoid

Leading questions: Don’t phrase questions to sway the answer in one direction (e.g., “Don’t you agree our product is amazing?”)

Double-barreled questions: Stick to one question at a time (e.g., Avoid “How satisfied are you with our product and customer service?”)

Biased language: Keep your wording neutral to get the most accurate results.

Harnessing Your Data

Collecting survey data is just the first step. To make the most of your results:

Choose the right analysis tools: Use spreadsheets or dedicated survey analytics software to uncover insights.

Visualize your data: Charts and graphs make your findings easier to digest.

Tell the story: Share your insights with key stakeholders in a way that sparks action.

Frequently Asked Questions (FAQs)

Can I use quantitative survey questions for qualitative research? Absolutely! While quantitative questions are designed for numerical data, they can be adapted to gather qualitative insights by incorporating open-ended options.

How many questions should I include in my survey? The ideal number depends on your research goals and audience. However, aim for brevity to keep participants engaged without compromising data quality.

Are online surveys as reliable as in-person surveys? With advancements in technology, online surveys are increasingly reliable, offering cost-effectiveness and broader reach without compromising data quality.

What role do demographics play in crafting survey questions? Demographic information adds depth to your analysis, providing insights into how different groups perceive and respond to your questions.

Should I pre-test my survey questions? Absolutely! Pre-testing helps identify potential issues with clarity, wording, or bias, ensuring your survey collects accurate and meaningful data.

How can I encourage survey participation? Incentives, personalized invitations, and clear communication about the survey’s purpose can significantly boost participation rates.

Let’s Wrap It Up

Mastering quantitative survey questions is a game-changer. By following these guidelines, you’ll gain the clarity and confidence to make decisions that propel your business forward.  Remember, data-driven insights are your path to success!

Survey Point Team

Quantitative market research questions to ask for actionable insights

Types of quantitative market research questions, 36 quantitative research questions and examples, how to write your own quantitative market research questions, how to collect insightful data from your quantitative surveys, receive quantitative insights in weeks, not months.

There’s a big difference between asking “Why do you like our product?” and “On a scale of 1-10, how much do you like our product?” But both ways of asking are valuable in their own way.

Knowing your audience is not about guesswork or intuition, it is about concrete data. And while it’s valuable to learn the ‘why’ behind the ‘what’ with qualitative research, quantitative research is just as necessary — to spot trends, patterns and more.

Unlike qualitative research, which explores attitudes, opinions, and motivations through open-ended questions, quantitative research zeroes in on the numbers (see what we did there?). It’s the difference between gathering general opinions and collecting measurable, specific data.

But when is this approach the way to go? For starters, whenever you need to track factors over time, such as customer satisfaction. Or when assessing the popularity of a potential product feature, understanding demographic preferences, or analyzing consumer purchasing behavior in different locations.

Quantitative research reveals the impact and scale of sentiments for better decision-making. It’s also valuable when you’re looking to quantify the extent of a trend, measure the impact of a marketing campaign, or pin down the specifics of consumer behavior.

But how do you ask quantitative market research questions that don’t just scratch the surface? We’re here to give you some great examples of quantitative survey questions.

In the US? Check out these research platforms

Here are the top market research platforms in the US for reliable insights – check them out and start getting your insights today!

When thinking of quantitative market research questions, people often think ‘ ah, numbers ‘. But there’s more than meets the eye. Here’s how you can categorize the different types of quantitative research questions:

Descriptive quantitative research questions

These are your what , when , and how many types of questions. They help you sketch out the basic landscape of your market. For example, “How often do you shop online in a month?” or “What is your preferred method of payment while shopping online?” When you give answers people can select, it is quantifiable data. That’s different from asking: ”describe what a day out shopping looks like for you”, which is a qualitative question.

Comparative quantitative survey questions

These questions measure differences or changes over time or between groups. For instance, “How has your spending on online shopping changed since last year?” Comparative questions help you understand the dynamics and shifts in your market. Remember that you’re not just trying to find overlap: it’s just as important to know what differences there are.

Relationship-based quantitative survey questions

These questions aim to uncover correlations or relationships between two or more variables. They can reveal insights like, “Is there a link between age and the likelihood of using mobile payments?” These questions help you understand the deeper connections within your market, as well as test assumptions, as long as you dare to ask questions that challenge what you’re hoping to find.

Now, a quick note on reducing bias in quantitative survey questions . Here are some key points to remember:

• The key is in how you frame your questions.
• Always aim for neutrality.
• Avoid leading questions that suggest a particular answer.
• Be specific and clear to avoid confusion.
• Consider the order of your questions, as earlier questions can influence responses to later ones.

And finally, test your survey with a small group before a full rollout, to catch and correct any unintentional bias. This way, you ensure the data you collect is as accurate and reliable as possible, giving you the best insights to make those crucial business decisions.

If you want to make a quantitative survey that hits the spot, don’t just ask generic questions. We’re here with some examples that you can adapt to make your research a success.

Descriptive market research questions

With a descriptive quantitative research question, you can quickly get the most important info for your respondents on anything ranging from buying frequency to satisfaction levels.

• Insight : this question reveals the frequency of use, indicating customer dependency on your product or service.
• Benefit : understanding usage patterns can guide inventory management and marketing strategies.
• Insight : reveals the communication channels most favored by your audience.
• Benefit : tailor your customer service and marketing outreach to your customers’ preferred channels.
• Insight : provides an average spending figure for budget allocation in that category.
• Benefit : helps in pricing strategies and identifying the most lucrative customer segments.
• Insight : uncovers patterns in online shopping behavior.
• Benefit : optimizes the timing of online marketing campaigns and promotions.
• Insight : identifies the most effective channels for brand discovery.
• Benefit : informs where to allocate advertising spend for maximum impact.
• Insight : measures the likelihood (not effectiveness!) of word-of-mouth referrals.
• Benefit : assesses customer satisfaction and the potential for organic growth.
• Insight : highlights your unique selling points from the customer’s perspective.
• Benefit : guides messaging to emphasize what customers value most about your brand.
• Insight : offers a quantifiable measure of customer service satisfaction.
• Benefit : identifies areas for improvement in customer support.
• Insight : sheds light on the most popular aspects of your product.
• Benefit : informs product development and feature enhancement.
• Insight : uncovers the key motivators behind purchasing decisions.
• Benefit : helps create targeted marketing campaigns to focus on these driving factors. 

Comparative market research questions

If you want to analyze and compare different variables, these questions can help.

• Insight : highlights changes in consumer spending habits over time.
• Benefit : useful for identifying trends and shifts in consumer behavior, aiding in long-term planning. Especially valuable if you add qualitative insights to this quantitative data.
• Insight : compares consumer preferences between different shopping channels.
• Benefit : guides omnichannel marketing strategies and resource allocation.
• Insight : tracks changing consumer values and preferences over time.
• Benefit : useful for aligning product development and marketing with evolving consumer values.
• Insight : compares the weight of price versus brand in purchasing decisions.
• Benefit : informs pricing strategies and brand positioning efforts.
• Insight : evaluates customer perception of marketing efforts in product packaging.
• Benefit : assesses the impact of packaging on brand image and customer approval.

What are the top research platforms in the UK?

Here’s our list of the pros and cons of key market research platforms for UK brands

Relationship-based questions for quantitative research

In quantitative research, especially when exploring relationship-based aspects, the key is not to cram multiple inquiries into one question but to ask them sequentially.

This approach allows for a clearer and more focused response to each individual question. Later, during the analysis phase, you can then correlate the responses to uncover relationships between different variables.

For instance, instead of asking, “How often do you use our product and how satisfied are you with it?”, split this into two separate questions:

• “How often do you use our product (daily, weekly, monthly)?”
• “On a scale of 1-10, how satisfied are you with our product?”

By asking these questions separately, you ensure that respondents clearly focus on each aspect without being overwhelmed or confused by a dual-focused question. This approach yields more accurate and reliable data.

After the survey, you can analyze the results to see if there’s a correlation between usage frequency and satisfaction levels.

Here are some examples of combinations that can work well:

• What is your age group?
• Insight : correlates age with shopping preferences.
• Benefit : you can tailor marketing and sales strategies to different age demographics based on their preferred shopping channels.
• How long have you been using our products/services?
• Insight : links customer tenure with brand loyalty.
• Benefit : assesses the impact of long-term use on loyalty, informing customer retention initiatives.
• What is your approximate annual income?
• Insight : examines the relationship between income levels and purchasing behavior for premium products.
• Benefit : guides product and pricing strategies targeting different income segments.
• How often do you use social media for product discovery?
• Insight : assesses if frequent social media use for product discovery actually influences online shopping behavior.
• Benefit : informs the effectiveness of social media marketing in driving online sales in your target market.
• How would you rate your satisfaction with our post-purchase customer service (scale of 0-10)?
• Insight : links the level of service post-purchase with the likelihood of repeat purchases.
• Benefit : identifies if customer service is negatively or positively affecting repeat custom rates.

Brand tracking questions for quantitative insights

One thing you should definitely gather numerical data on, is your brand’s health. Just like your own health, stats, and numbers matter and can show you where to further investigate to ask qualitative research questions about. Learn if your brand stands strong through market trends and gain insights on whether your brand is growing in terms of awareness — and in which segments.

• Insight : measures brand awareness among the target audience.
• Benefit : helps assess the effectiveness of your marketing and branding efforts.
• Insight : evaluates brand loyalty and the potential for organic growth through word-of-mouth.
• Benefit : indicates customer satisfaction and the potential for brand advocacy.
• Insight: Identifies the most effective channels for brand discovery.
• Benefit: Informs where to focus marketing efforts for increased brand exposure.
• Insight: Measures brand visibility and frequency of encounters with the brand.
• Benefit: Helps evaluate the reach and frequency of marketing campaigns.
• Insight: Determines which brand values resonate most with the audience.
• Benefit: Aids in refining brand messaging and aligning it with customer values.

Quantitative consumer segmentation questions

Quantitative questions about customer segments can go beyond age group and gender. King Charles III is the same age as Ozzy Osbourne – would you say they’re very similar?

It is vital that you look at more variables so you can really tell the difference between your respondents, and make informed decisions based on the whole truth. Putting these consumer profiling questions and answers in specific ranges helps you create segments to tailor your marketing and customer experience for, rather than just aiming at the entire population.

• Insight : helps understand the economic demographics of your customers.
• Benefit : assists in pricing strategies and identifying which income groups are most engaged with your brand.
• Insight : reveals geographical spread and regional preferences.
• Benefit : guides regional marketing efforts and product distribution strategies.
• Insight : helps categorize customers by education level.
• Benefit : useful for tailoring communication and content complexity to different education backgrounds.
• Insight : provides insights into the professional background of your customers.
• Benefit : helps in creating industry-specific marketing campaigns and products.
• Insight : gives an idea of household size and composition.
• Benefit : useful for targeting products and services aimed at families or individuals.
• Insight : identifies customers who are parents of minors (which is different from parents of young adults, or even grown adults).
• Benefit : informs product and marketing strategies aimed at families with children.

Okay, so now you got the gist of it and have seen what quantitative questions can look like — as they come in all shapes and sizes. But they might feel too generic for your research, or you’re looking for something specific.

Here’s how you can whip up your own quantitative questions that deliver the insights you need for data-driven decisions.

Identify the key variables you need to measure

Start by pinpointing exactly what you want to know. Is it customer satisfaction, buying behavior, or brand awareness? Determining the specific variables you need to measure sets the foundation for your entire survey.

Choose the right survey distribution method

Think about how your questions will reach your audience. Will it be online through email or social media, over the phone, or in person? Your method should align with where your target audience is most active and responsive.

Make sure your questions are crystal-clear and unequivocally unbiased

We’ve mentioned it earlier, and we’ll do it again if we have to. The way you phrase your questions can make or break your survey. Aim for clarity and simplicity – questions should be easy to understand and answer. Avoid leading or loaded questions that might sway a respondent’s answer. Remember: it’s a survey, not a sales pitch.

Know where to ask for more detailed information and qualitative data

Quantitative market research questions only tell part of the story. If you see interesting trends in say purchase behavior or price sensitivity, or a particular product gets a bad rating, dig a little deeper. Follow up important questions with qualitative research questions to analyze what’s going on behind the numbers.

If you don’t want to end up with a pile of quantitative data that doesn’t do much for you or breaks the bank unnecessarily, it’s vital you choose a form of distributing the survey that makes sense. You can work with UK market research companies to outsource it all, or do it yourself. Here’s a brief look at the pros and cons of popular methods:

Telephone surveys:

• Pros : good for less tech-savvy demographics.
• Cons : time-consuming, potentially costly, and declining response rates. They might be better for qualitative research.

In-person surveys:

• Pros : also avoids any confusion with tech.
• Cons : logistically demanding and expensive, not suited for quick data collection.

Online survey software:

• Pros : cost-effective, broad reach, real-time data analysis, and versatile formats.
• Cons : it’s extra important to pay close attention to survey design, so people don’t get the urge to give false answers just to get to the end.

The choice is yours, but generally, quantitative research thrives when done with online surveys and it’s the go-to method for most international market research . And here at Attest, we help you get even more out of it by giving you a chock-full toolkit. From various types of questions to robust analytical tools (and a dedicated research expert for when you need a little extra help) — we set you up for measurable success.

Speed and accuracy in market research matter — but we don’t want you to sacrifice quality. With Attest, you get fast, actionable and high-quality insights.

Which market analysis tool is right for you?

Check our rundown of the top platforms for market analysis – and start making better decisions with reliable insights in no time!

VP Customer Success 

Sam joined Attest in 2019 and leads the Customer Research Team. Sam and her team support brands through their market research journey, helping them carry out effective research and uncover insights to unlock new areas for growth.

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Quantitative Research: Examples of Research Questions and Solutions

Are you ready to embark on a journey into the world of quantitative research? Whether you’re a seasoned researcher or just beginning your academic journey, understanding how to formulate effective research questions is essential for conducting meaningful studies. In this blog post, we’ll explore examples of quantitative research questions across various disciplines and discuss how StatsCamp.org courses can provide the tools and support you need to overcome any challenges you may encounter along the way.

Understanding Quantitative Research Questions

Quantitative research involves collecting and analyzing numerical data to answer research questions and test hypotheses. These questions typically seek to understand the relationships between variables, predict outcomes, or compare groups. Let’s explore some examples of quantitative research questions across different fields:

• What is the relationship between class size and student academic performance?
• Does the use of technology in the classroom improve learning outcomes?
• How does parental involvement affect student achievement?
• What is the effect of a new drug treatment on reducing blood pressure?
• Is there a correlation between physical activity levels and the risk of cardiovascular disease?
• How does socioeconomic status influence access to healthcare services?
• What factors influence consumer purchasing behavior?
• Is there a relationship between advertising expenditure and sales revenue?
• How do demographic variables affect brand loyalty?

Stats Camp: Your Solution to Mastering Quantitative Research Methodologies

At StatsCamp.org, we understand that navigating the complexities of quantitative research can be daunting. That’s why we offer a range of courses designed to equip you with the knowledge and skills you need to excel in your research endeavors. Whether you’re interested in learning about regression analysis, experimental design, or structural equation modeling, our experienced instructors are here to guide you every step of the way.

Bringing Your Own Data

One of the unique features of StatsCamp.org is the opportunity to bring your own data to the learning process. Our instructors provide personalized guidance and support to help you analyze your data effectively and overcome any roadblocks you may encounter. Whether you’re struggling with data cleaning, model specification, or interpretation of results, our team is here to help you succeed.

Courses Offered at StatsCamp.org

• Latent Profile Analysis Course : Learn how to identify subgroups, or profiles, within a heterogeneous population based on patterns of responses to multiple observed variables.
• Bayesian Statistics Course : A comprehensive introduction to Bayesian data analysis, a powerful statistical approach for inference and decision-making. Through a series of engaging lectures and hands-on exercises, participants will learn how to apply Bayesian methods to a wide range of research questions and data types.
• Structural Equation Modeling (SEM) Course : Dive into advanced statistical techniques for modeling complex relationships among variables.
• Multilevel Modeling Course : A in-depth exploration of this advanced statistical technique, designed to analyze data with nested structures or hierarchies. Whether you’re studying individuals within groups, schools within districts, or any other nested data structure, multilevel modeling provides the tools to account for the dependencies inherent in such data.

As you embark on your journey into quantitative research, remember that StatsCamp.org is here to support you every step of the way. Whether you’re formulating research questions, analyzing data, or interpreting results, our courses provide the knowledge and expertise you need to succeed. Join us today and unlock the power of quantitative research!

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Quantitative Research Questions Examples & Types

• Post author By Andrew Chornyy
• Post date Feb 02, 2024
• No Comments on Quantitative Research Questions Examples & Types

Quantitative research questions form the backbone of solid data analysis , a crucial step in understanding market trends and consumer behavior. As we delve into the art of crafting precise, measurable questions, remember: the clarity of your inquiry directly impacts the quality of your findings. It’s not just about asking; it’s about asking right. Here at Plerdy, where data-driven insights are paramount, we recognize the power of well-structured questions in revealing actionable truths. In this article, we’ll guide you through shaping questions that bring clear, objective results, ensuring your research strikes the perfect balance between depth and simplicity. Discover the keys of effective quantitative inquiry and transform your data analysis with Plerdy.

Understanding Quantitative Research Questions

Quantitative research questions are the gateway to unlocking a world of data-driven insights. Central to effective research, these questions help us quantify variables, compare groups, and establish relationships in a structured, objective manner.

Definition: At their core, quantitative research questions seek measurable, numeric answers. They are designed to collect data that can be statistically analyzed, ensuring precise, objective outcomes. This approach is ideal for studies that require definitive results rather than subjective interpretations.

Characteristics:

• Specificity: They are clear and focused, aiming at specific variables or groups.
• Measurability: These questions ensure that responses can be quantified in numerical terms.
• Objectivity: They maintain neutrality, avoiding any bias in phrasing.
• Identifying Trends: By quantifying responses, these questions help in spotting patterns and trends in data.
• Making Comparisons: They allow for the comparison of different groups or variables.
• Predicting Outcomes: They assist in forecasting future trends based on current data.

Quantitative research questions are a vital tool for researchers and analysts. They provide a structured path to gaining valuable insights, crucial for making informed decisions. Whether you’re exploring market dynamics or investigating social trends, crafting these questions with precision is key to obtaining reliable, actionable data. As we journey through the nuances of these questions, keep in mind their potential to transform your understanding of the world around us.

Types of Quantitative Research Questions

In the realm of data analysis, understanding the types of quantitative research questions is pivotal for conducting robust research. These questions are classified based on their objective, leading to distinct approaches in data collection and interpretation.

Descriptive Questions:

• Objective: These questions aim to describe characteristics or functions.
• Structure: Often begin with “What is” or “How many.”
• What is the average income of a family in a specific region?
• How many hours per week do teenagers spend on social media ?

Comparative Questions:

• Objective: Designed to compare two or more groups or variables.
• Structure: Typically structured as “How does X compare to Y?”
• How does the customer satisfaction level differ between Brand A and Brand B?
• What is the difference in test scores between students who study online and those who attend traditional classes?

Relationship-based Questions:

• Objective: Explore the relationship between variables.
• Structure: Often phrased as “What is the relationship between X and Y?”
• What is the relationship between diet and heart health?
• How does exercise frequency relate to stress levels in working adults?

These types of questions are the bedrock of quantitative research, providing a clear path to analyze and interpret data. Descriptive questions lay the foundation by establishing basic facts. Comparative questions build on this by highlighting differences or similarities, while relationship-based questions delve deeper into how variables interact and influence each other.

To effectively employ these questions, researchers must be clear and precise in their phrasing, ensuring each question aligns with their specific research goals. By mastering these types, you can unlock a wealth of information and insights , critical for making informed decisions in any field. Remember that quantitative research may simplify complex data into usable knowledge.

Crafting Effective Quantitative Research Questions

Crafting effective quantitative research questions is a crucial step in any data-driven study, setting the stage for meaningful and reliable results. To ensure precision and clarity , following a structured approach is essential.

• Identifying Variables: Start by pinpointing the independent and dependent variables. The dependent variable is measured, while the independent variable is changed. For example, in a study on education, “teaching methods” could be your independent variable, and “student performance” could be the dependent variable. Understanding these variables helps in formulating a focused question.
• Question Structure: A well-structured question is clear and to the point. It directly addresses the relationship or comparison you’re investigating. Use phrases like “What impact does…,” “How does…,” or “What is the correlation between…” to structure your question. Keep it concise to avoid confusion.
• Ensuring Clarity and Precision: Avoid ambiguity. Your question should be understandable to someone outside your field. This means avoiding technical jargon and being as specific as possible about what you are investigating.

For instance:

• Unclear: How does technology affect learning?
• Clear: What is the impact of interactive digital textbooks on high school students’ math test scores?

Crafting effective quantitative research questions involves a balance of specificity, clarity, and structure. Begin by identifying your variables, then structure your question in a way that clearly conveys your investigative aim. Finally, ensure the wording is precise and free from ambiguity. This approach will not only refine your research focus but also enhance the comprehensibility and relevancy of your study, making it a valuable contribution to your field.

Real-world Examples of Quantitative Research Questions

Exploring quantitative research problems in real-world settings shows their practicality across fields. These examples not only demonstrate the diversity of these questions but also provide insight into how they drive specific, measurable outcomes.

• Education: In the educational sector, a common focus is on evaluating teaching methods and their effectiveness. An example question could be, “What is the impact of blended learning on the mathematics achievement of high school students compared to traditional teaching methods?” This question targets a specific teaching approach and measurable student performance .
• Healthcare: Healthcare research often revolves around patient outcomes and treatment efficacy. A question like, “How does a 6-week physical therapy program affect the recovery rate of post-operative knee surgery patients?” precisely addresses a treatment duration and a measurable patient outcome.
• Social Sciences: In social sciences, research questions might explore societal trends or behaviors. An example could be, “What is the correlation between social media usage and anxiety levels among young adults in urban areas?” This question is aimed at understanding the relationship between a widespread modern habit and a specific psychological condition.

Some real-world quantitative research questions on marketing strategy and social media monitoring:

Marketing Strategy Research Questions

• “How does varying the headline of an online advertisement influence its CTR?”
• “What impact does the use of different images in ads have on viewer engagement rates?”
• “Does incorporating video content in ads increase the conversion rate compared to static images?”
• “How does the integration of user testimonials in ad layouts affect viewer response rates?”
• “What effect does changing the color palette of an ad have on viewer attention span?”
• “Does the use of brighter colors in ads lead to an increased number of views and interactions?”
• “How does modifying the length and tone of ad copy influence the time users spend on the corresponding landing page?”
• “What is the effect of using direct vs. suggestive call-to-actions in ad texts on the user response rate?”
• “How does the positioning of an ad on a webpage influence the advertising cost per click?”
• “Does the placement of ads above the fold result in better engagement compared to below the fold?”
• “What is the effect of using demographic-based targeting on the total number of ad impressions?”
• “How does altering location targeting in digital ads influence the audience reach and diversity?”

Social Media Monitoring Research Questions

• “How frequently is our brand mentioned on social media platforms within a given time frame?”
• “What is the ratio of positive to negative brand mentions on social media during product launch periods?”
• “Which types of social media posts (images, videos, text) generate the highest engagement for our brand?”
• “What are the prevalent themes in user-generated content related to our brand on social platforms?”
• “How does the introduction of a new hashtag influence engagement and sharing rates on our social media channels?”
• “What impact do social media promotional campaigns have on follower growth and interaction rates?”

Advanced Ad Analysis Questions:

• “What is the click-through rate for ads with interactive elements like quizzes or polls compared to standard ads?”
• “How does the inclusion of interactive features in ads influence the time spent by users on the website?”
• “How do ad engagement rates vary during different seasons or major holidays?”
• “What impact does season-specific ad theming have on conversion rates?”
• “What is the optimal frequency for displaying retargeting ads to maximize conversions without causing ad fatigue?”
• “How does the timing of ad displays (time of day/week) affect user engagement and click rates?”

Deep Dive into Social Media Dynamics Questions:

• “What is the change in brand mentions and engagement rates after collaborating with social media influencers?”
• “How does influencer marketing affect the demographic profile of the brand’s social media followers?”
• “What is the average time spent by users on our social media pages before and after specific campaign launches?”
• “Which types of content (live videos, stories, posts) lead to the highest user interaction rates on our social media platforms?”
• “How does the engagement rate for our brand differ across various social media platforms?”
• “What are the differences in audience demographics and interaction patterns across different social media channels?”
• “What is the overall sentiment (positive, negative, neutral) expressed in user comments on our social media posts?”
• “How do product launches or service updates influence the sentiment of discussions around the brand on social media?”

Optimizing Digital Presence Questions:

• “How does social media traffic contribute to user behavior and conversion rates on the company’s website?”
• “What is the correlation between social media activity and lead generation on the company’s digital platforms?”
• “Which content strategies lead to the highest growth in followers and engagement on our social media channels?”
• “How does the frequency and type of content posted on social media influence brand perception and customer loyalty?”

These quantitative research questions are designed to provide concrete data that can help businesses refine their marketing strategies and social media presence for maximum effectiveness and engagement.

These real-world examples demonstrate the value of concise, targeted, and measurable quantitative research topics. By following this approach, researchers can effectively investigate and draw significant conclusions in their respective fields. Whether it’s understanding educational techniques, medical treatments, or societal behaviors, well-structured quantitative research questions are instrumental in uncovering valuable insights and contributing to informed decision-making .

Common Mistakes to Avoid

In the process of formulating quantitative research questions, certain common mistakes can significantly hinder the effectiveness of your study. Being aware of these pitfalls is essential for conducting meaningful research.

• Vague Wording: Ambiguity is the enemy of clarity. Questions like “How does social media influence behavior?” are too broad. Instead, specify the aspect of behavior, such as “How does social media use impact the attention span of teenagers?”
• Over-complicating Questions: Simplicity is key. Avoid convoluted questions that might confuse respondents. For instance, instead of asking “What are the various factors that affect the decision-making process of consumers purchasing technological gadgets?” simplify it to “What key factors influence consumer decisions when buying technological gadgets?”

Crafting clear, concise, and focused quantitative research questions is crucial. Avoid vague wording and over-complication. By steering clear of these common mistakes, you ensure that your research questions are robust and yield valuable, actionable data. This approach not only enhances the quality of your research but also increases its relevance and applicability to your target audience.

Quantitative research question writing is essential for gaining insights in any discipline. Through clarity, specificity, and focus, these questions become powerful tools in your analytical arsenal. Remember, the precision of your inquiry shapes the depth of your understanding. As we’ve explored various facets of quantitative questioning, the potential for data-driven decision-making becomes evident. For more insights and strategies to elevate your research, explore other articles on the Plerdy blog. Ready to dive deeper into data analytics ? Plerdy offers an array of tools to enhance your digital strategy. Check out Plerdy’s solutions for your next project – a step towards transforming data into actionable insights.

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Quantitative Survey Questions: Definition, Types, Examples, and More

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Asking the right question to your audience can help you gather accurate and significant data. But what type of questions should you ask your audience – quantitative or qualitative? This depends on the type of data you want to collect. 

Quantitative research questions allow respondents to answer concisely. In this article, we’ll go over some popular quantitative research questions and the different types of quantitative research questions.

Definition of quantitative research questions?

Quantitative research questions are objective questions that provide detailed knowledge about a research topic. The data obtained with quantitative research questions are numerical that can be examined statistically. 

Quantitative research questions help look into trends and patterns to make logical sense of the research topic. The data gathered can be generalized to the entire population and help make data-driven and sound decisions. 

Statistical reports are hard to argue with, making the data more reliable. Quantitative research requires precise information so the data it brings is reliable and valid. 

Popular Quantitative Research Questions

Here are some of the most common quantitative research questions you can use in your quantitative surveys:

👉How often do you visit an art gallery?

👉How much do you pay for the hotel’s VIP services?

👉What differences did you notice between our website and app interface?

👉What is the effect of social media on self-confidence?

👉What is the relationship between age and alcohol consumption? 

The best way to create a quantitative survey is by using online survey tools that offer a diverse range of question types. This way you can choose which quantitative question would best serve the purpose of your survey.

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Now let’s dive into the different types of quantitative research questions.

What are the different types of quantitative research questions?

There are three types of quantitative research questions . 

Each of these type helps you gather unique insights. You can determine which research question types to use based on the type of data you want to gather and the research objective. 

• Descriptive Research Questions- These questions are used for gathering customers’ opinions about variables one wants to measure.
• Comparative Research Questions- These questions are used for examining the difference between two or more groups based on one or more dependable variables.
• Relationship-based Research Questions- These questions are used for identifying trends, causal relationships, or associations between two or more variables. 

In our next section, we’ll explore the three types of quantitative research questions in detail and look at their examples.

15 quantitative survey question examples

Let’s take a look at some examples of quantitative research questions

1. Descriptive Research Questions

It simply implies that you want to gather information about variables that you are trying to quantify or measure. Descriptive research questions help gather a customer’s opinion about variables you want to measure.

These questions mostly begin with-

• What percentage?
• What proportion?

Descriptive research questions focus mostly on one group and one variable. Rarely do these questions include multiple groups and variables. Here are a few examples of descriptive research questions

We have shared a few questions that you can use as an inspiration to create your own research question. You can use the following quantitative research question examples for your market research. 

Let’s look at a few examples of quantitative research question types. 

Question 1: How much fast food do Americans consume per week?

• Variable: Fast food intake
• Group: American

Question 2: How often do students between the ages of 15 – 18 use Facebook weekly?

• Variable: Weekly use of Facebook
• Group: Students between ages 15 – 18

Question 3: How often do male and female university students use a food delivery app monthly?

• Variables: Use of food delivery app
• Group: 1. Male University students
• Female University students

Question 4: What is the preferred choice of cuisine of the Italians?

• Variable: Cuisine
• Groups: Italian

Question 5: What are the important factors influencing the career choice of Asian-American University students?

• Variable: Factors influencing career choice
• Group: Asian-American University students

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2. Comparative Research Question

Comparative research questions help examine the difference between two or more groups based on one or more dependable variables. The number of variables depends on the need of market research. 

The question asks the respondents, “what is the difference in” a dependent variable between two or more groups?

Let’s look at some quantitative research question examples for this type that you can use in competitive analysis. 

Question 1: What is the difference in time spent on video games between people aged 12 to 17 and 18 to 25?

• Variable: Time spent on video games
• Group 1: People within the age range 12 and 17
• Group 2: People within the age range 18 and 25

Question 2: What is the difference in attitude towards online shopping between millennials adults and Adults born before 1980?

• Variable: Attitude towards online shopping
• Group 1: Millennial adults
• Group 2: Adults born before 1980

Question 3: What is the difference in the attitude towards politics between Mexicans and Americans in America?

• Variable: Attitude towards Politics
• Group 1: Mexicans in America
• Groups 2: Americans in America

Question 4: What is the difference in the usage of Snapchat between Canadian male and female university students?

• Variable: usage of Snapchat
• Group 1: Canadian Male University student
• Group 2: Canadian Female University student

Question 5: What is the difference in attitude toward rock music between Gen-Z and Millennials?

• Variables: Attitude toward rock music
• Group 1: Gen-Z
• Group 2: Millennials

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3. Relationship-based Research Questions

Relationship-based research questions are the best quantitative research question examples when you need to identify trends, causal relationships, or associations between two or more variables. 

When using the term relationship in statistics, it is important to remember that it refers to experimental research design. 

In this case, examining the cause and effect between two variables is possible. This means it is possible to say which variable was responsible for the effect on the other variable. 

However, when you use relationship-based research questions, you do not have to distinguish between causal relationships, trends, or associations. 

The question in this type begins with “What is the relationship” between or amongst independent and dependent variables, amongst or between two or more groups? 

Question 1: What is the relationship between gender and attitude towards romantic movies amongst Middle-aged people?

• Dependent Variable: Attitude towards romantic movies
• Independent Variables: Gender
• Group: Middle-aged people

Question 2: What is the relationship between age and fast food preference in Australia?

• Dependent Variable: Fast Food preference
• Independent Variable: Age
• Group: Australia

Question 3: What is the relationship between age and lifestyle among women?

• Dependent Variable: Lifestyle
• Group: Women

Question 4: What is the relationship between Salary and Job satisfaction among people working in the corporate business?

• Dependent Variable: Job satisfaction
• Independent Variable: Salary
• Group: People working in corporate business

Question 5: What is the relationship between University degrees and Job positions amongst employees in Multinational Companies?

• Dependent Variable: Job position
• Independent Variable: University Degree
• Group: Employees in a Multinational Company

This quantitative research question example can help you help segment customers based on their shared characteristics. Leverage a data analysis platform that enables you to identify patterns between responses and help you group customers with similar attributes. 

This way, you can create unique customer profiles and personalized campaigns that appeal to each customer. 

Learn the Key Steps To Conduct Descriptive Research with Voxco’s Guide to Descriptive Research.

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How to Write Good Quantitative Survey Questions?

Follow the steps listed below to design quantitative survey questions:

Step 1: Choose the type of quantitative survey question  

Select a type that corresponds to the survey’s goal. The kind of answers given by respondents are determined by the type of question posed. 

Step 2: Identify the target group as well as dependent and independent variables

The next step is to choose the target audience and the variables to be measured. Variables can be categorized into 4 types: nominal, ordinal, interval, and ratio. 

Step 3: Give a proper structure to the survey 

After the first 2 points have been taken care of, it is now time to structure the survey such that it is uncomplicated. Simple and unambiguous wordings should be used to frame the questions.

Importance of Quantitative Research Questions

Quantitative research questions play a vital role in the design and implementation of the research method. The questions provide a clear framework to help you understand what data you need to gather and investigate the correlation between quantitative variables. 

Here are some key reasons that make quantitative research questions important.  

1. Objective analysis 

This research question allows you to seek numerical data and focus on measurable variables. It provides a more standardized result and objective measurement. 

2. Generalizability 

Quantitative data enables you to make generalizations about the target population based on your research sample. By clearly defining variables and the target population, you can draw conclusions that are applicable to the intended population. 

3. Statistical analysis 

A well-defined quantitative research question gathers statistical data that allows you to perform statistical analysis. This allows you to identify patterns, correlations, trends, and differences within the data, thus providing meaningful insights. 

When to use Quantitative Research Questions?

Let’s look at the situations when you should use quantitative research questions. 

1. When exploring the relationship between quantitative variables. 

What is the relationship between students’ play time and their health? 

This is an example of quantitative research question where you intended to identify the relation between the variables of students’ health and their playtime. 

2. When comparing different groups. 

Is there any significant difference in the satisfaction level between software A and software B? 

This is a quantitative research question example where you explore the difference in satisfaction between two variables. 

3. When evaluating trends and patterns. 

How has the purchase frequency changed over the fourth quarter of the year?

This is an example of quantitative research question where you uncover the trend or changes in purchase frequency over time. 

4. When conducting large-scale surveys. 

Quantitative questions are valuable when you intend to conduct large-scale surveys targeting a wide range of participants. It allows a standardized and systematic approach to data collection and analysis, enabling you to draw meaningful conclusions. 

Also Read: Quantitative Research Vs Qualitative Research . 

This sums up our article on quantitative research question examples. You can use these question types to create interactive market research surveys that provide meaningful insights. You can choose to use these questions separately or together in a survey depending on your research goal.

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Adding Quantitative Research Questions in Online Surveys

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One of the things that makes Alchemer a powerful online survey and research platform is the sheer number of question types you have access to as a user. This flexibility also allows you to add different question types to any survey, so you don’t have to choose between quantitative and qualitative questions in your survey. You can have both.

If you’re unsure of the difference between quantitative and qualitative, read the article, Does your Consumer Survey Data Paint The Whole Picture . This blog explores the differences between the two question types but here is the short version:

• Quantitative questions will tell you Who and What.
• Qualitative questions will tell you Why.

Quantitative questions are easier to measure and easier for survey takers to answer. Qualitative questions, on the other hand, are subjective and harder to measure. They are also harder for survey-takers to answer and too many can lead to survey fatigue.

Qualitative questions (like open textboxes or essay questions) are great for the exploratory phase of your research project or to delve deeper into a matter, but you want to use them sparingly. Don’t tire your survey-takers or yourself. Trying to analyze essay question answers to find a common theme can be arduous and time-consuming.

One way to make qualitative questions easier on both of you is to use Video Feedback questions, which allow people to respond with a video, rather than writing out their answers.

If you need hard statistics or quantifiable numbers, use quantitative questions. You can assign numeric values for easy, objective measurement and comparison.

Quantitative questions are close-ended which makes them easy to answer. You can ask a lot of these questions without tiring survey respondents. But you’ll want to mix up the question types to keep your survey interesting and your respondents engaged.

In this article we will explore the different ways to ask quantitative questions in your online survey.

How to Phrase Quantitative Questions

Quantitative questions typically start with how or what. Some common leading phrases include:

• How frequently?
• What percentage?
• What proportion?
• To what extent?

Here are some quantitative question examples:

• How many text messages do you send a day?
• How frequently do you text while driving?
• How often do you send text messages while at work?

Be sure to identify all of the variables that might affect the outcome. Also be sure to include all of the groups you are interested in. Neglecting to recognize variables and groups involved will create gaps in your data that will make it hard for you to base sound decisions on.

In the example above, work and driving are variables that likely alter texting behavior. In this example, you could also collect demographic information such as age, gender, and job function so you can compare texting habits between these groups.

Quantitative Question Types

Most online survey tools offer an array of answer formats. This is good news, as these various options will engage your customers and reduce survey fatigue.

Mix up these close-ended question types to increase your response rate:

Radio Button Example:

Checkbox Example:

Drop Down Menu Example:

Drag and Drop Example:

Likert Scale Example:

Sliding Scale Example:

Star Ranking Example:

Net Promoter Score Example:

Image Select Example:

Matrix Example:

Considerations When Choosing Quantitative Question Types

While it is nice to vary your question types to keep respondents interested, it is important to consider the reporting options. Some question types report in bar and pie charts where others may not. Always test your survey and check the reports to ensure you are collecting the data in the format that best suits your needs.

Also consider the type of device your respondents will be using. Interactive question types are engaging but may not be reliable on all mobile devices. Long matrix tables can be frustrating on a mobile device since the radio buttons or checkboxes are small. Image select questions may not render properly or take too long to load.

Use “Other” as Answer Option When Necessary

Hopefully you have considered all of the relevant answer options when crafting your quantitative question. Of course, it is now always possible to include every answer option.

If you are fearful of not including an answer option, use an “Other” answer choice and provide a textbox so respondents can specify the alternative. These are easy to setup when using a radio button or checkbox question type.

If your question is well designed, the “Other” answer option should be the exception rather than the rule. Analyzing the textbox information should not be too arduous since there are likely only a few of them. If more than 50% selected “Other “ as the answer option than perhaps you needed to do some exploratory research.

Quantifiable Results

So there you have it; 10 different quantitative question types that will keep your survey interesting and your respondents engaged. But the best part is that you will have quantifiable data that you can act on! Related Articles: Does You Consumer Survey Data Paint The Whole Picture: When to Use Qualitative Vs. Quantitative Research Questions Quantitative Vs. Qualitative Research – When to Use Which Using Qualitative Exploration To Create Quantitative Surveys Using Highly Interactive Questions In Online Surveys

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Writing survey questions.

Perhaps the most important part of the survey process is the creation of questions that accurately measure the opinions, experiences and behaviors of the public. Accurate random sampling will be wasted if the information gathered is built on a shaky foundation of ambiguous or biased questions. Creating good measures involves both writing good questions and organizing them to form the questionnaire.

Questionnaire design is a multistage process that requires attention to many details at once. Designing the questionnaire is complicated because surveys can ask about topics in varying degrees of detail, questions can be asked in different ways, and questions asked earlier in a survey may influence how people respond to later questions. Researchers are also often interested in measuring change over time and therefore must be attentive to how opinions or behaviors have been measured in prior surveys.

Surveyors may conduct pilot tests or focus groups in the early stages of questionnaire development in order to better understand how people think about an issue or comprehend a question. Pretesting a survey is an essential step in the questionnaire design process to evaluate how people respond to the overall questionnaire and specific questions, especially when questions are being introduced for the first time.

For many years, surveyors approached questionnaire design as an art, but substantial research over the past forty years has demonstrated that there is a lot of science involved in crafting a good survey questionnaire. Here, we discuss the pitfalls and best practices of designing questionnaires.

Question development

There are several steps involved in developing a survey questionnaire. The first is identifying what topics will be covered in the survey. For Pew Research Center surveys, this involves thinking about what is happening in our nation and the world and what will be relevant to the public, policymakers and the media. We also track opinion on a variety of issues over time so we often ensure that we update these trends on a regular basis to better understand whether people’s opinions are changing.

At Pew Research Center, questionnaire development is a collaborative and iterative process where staff meet to discuss drafts of the questionnaire several times over the course of its development. We frequently test new survey questions ahead of time through qualitative research methods such as  focus groups , cognitive interviews, pretesting (often using an  online, opt-in sample ), or a combination of these approaches. Researchers use insights from this testing to refine questions before they are asked in a production survey, such as on the ATP.

Measuring change over time

Many surveyors want to track changes over time in people’s attitudes, opinions and behaviors. To measure change, questions are asked at two or more points in time. A cross-sectional design surveys different people in the same population at multiple points in time. A panel, such as the ATP, surveys the same people over time. However, it is common for the set of people in survey panels to change over time as new panelists are added and some prior panelists drop out. Many of the questions in Pew Research Center surveys have been asked in prior polls. Asking the same questions at different points in time allows us to report on changes in the overall views of the general public (or a subset of the public, such as registered voters, men or Black Americans), or what we call “trending the data”.

When measuring change over time, it is important to use the same question wording and to be sensitive to where the question is asked in the questionnaire to maintain a similar context as when the question was asked previously (see  question wording  and  question order  for further information). All of our survey reports include a topline questionnaire that provides the exact question wording and sequencing, along with results from the current survey and previous surveys in which we asked the question.

The Center’s transition from conducting U.S. surveys by live telephone interviewing to an online panel (around 2014 to 2020) complicated some opinion trends, but not others. Opinion trends that ask about sensitive topics (e.g., personal finances or attending religious services ) or that elicited volunteered answers (e.g., “neither” or “don’t know”) over the phone tended to show larger differences than other trends when shifting from phone polls to the online ATP. The Center adopted several strategies for coping with changes to data trends that may be related to this change in methodology. If there is evidence suggesting that a change in a trend stems from switching from phone to online measurement, Center reports flag that possibility for readers to try to head off confusion or erroneous conclusions.

Open- and closed-ended questions

One of the most significant decisions that can affect how people answer questions is whether the question is posed as an open-ended question, where respondents provide a response in their own words, or a closed-ended question, where they are asked to choose from a list of answer choices.

For example, in a poll conducted after the 2008 presidential election, people responded very differently to two versions of the question: “What one issue mattered most to you in deciding how you voted for president?” One was closed-ended and the other open-ended. In the closed-ended version, respondents were provided five options and could volunteer an option not on the list.

When explicitly offered the economy as a response, more than half of respondents (58%) chose this answer; only 35% of those who responded to the open-ended version volunteered the economy. Moreover, among those asked the closed-ended version, fewer than one-in-ten (8%) provided a response other than the five they were read. By contrast, fully 43% of those asked the open-ended version provided a response not listed in the closed-ended version of the question. All of the other issues were chosen at least slightly more often when explicitly offered in the closed-ended version than in the open-ended version. (Also see  “High Marks for the Campaign, a High Bar for Obama”  for more information.)

Researchers will sometimes conduct a pilot study using open-ended questions to discover which answers are most common. They will then develop closed-ended questions based off that pilot study that include the most common responses as answer choices. In this way, the questions may better reflect what the public is thinking, how they view a particular issue, or bring certain issues to light that the researchers may not have been aware of.

When asking closed-ended questions, the choice of options provided, how each option is described, the number of response options offered, and the order in which options are read can all influence how people respond. One example of the impact of how categories are defined can be found in a Pew Research Center poll conducted in January 2002. When half of the sample was asked whether it was “more important for President Bush to focus on domestic policy or foreign policy,” 52% chose domestic policy while only 34% said foreign policy. When the category “foreign policy” was narrowed to a specific aspect – “the war on terrorism” – far more people chose it; only 33% chose domestic policy while 52% chose the war on terrorism.

In most circumstances, the number of answer choices should be kept to a relatively small number – just four or perhaps five at most – especially in telephone surveys. Psychological research indicates that people have a hard time keeping more than this number of choices in mind at one time. When the question is asking about an objective fact and/or demographics, such as the religious affiliation of the respondent, more categories can be used. In fact, they are encouraged to ensure inclusivity. For example, Pew Research Center’s standard religion questions include more than 12 different categories, beginning with the most common affiliations (Protestant and Catholic). Most respondents have no trouble with this question because they can expect to see their religious group within that list in a self-administered survey.

In addition to the number and choice of response options offered, the order of answer categories can influence how people respond to closed-ended questions. Research suggests that in telephone surveys respondents more frequently choose items heard later in a list (a “recency effect”), and in self-administered surveys, they tend to choose items at the top of the list (a “primacy” effect).

Because of concerns about the effects of category order on responses to closed-ended questions, many sets of response options in Pew Research Center’s surveys are programmed to be randomized to ensure that the options are not asked in the same order for each respondent. Rotating or randomizing means that questions or items in a list are not asked in the same order to each respondent. Answers to questions are sometimes affected by questions that precede them. By presenting questions in a different order to each respondent, we ensure that each question gets asked in the same context as every other question the same number of times (e.g., first, last or any position in between). This does not eliminate the potential impact of previous questions on the current question, but it does ensure that this bias is spread randomly across all of the questions or items in the list. For instance, in the example discussed above about what issue mattered most in people’s vote, the order of the five issues in the closed-ended version of the question was randomized so that no one issue appeared early or late in the list for all respondents. Randomization of response items does not eliminate order effects, but it does ensure that this type of bias is spread randomly.

Questions with ordinal response categories – those with an underlying order (e.g., excellent, good, only fair, poor OR very favorable, mostly favorable, mostly unfavorable, very unfavorable) – are generally not randomized because the order of the categories conveys important information to help respondents answer the question. Generally, these types of scales should be presented in order so respondents can easily place their responses along the continuum, but the order can be reversed for some respondents. For example, in one of Pew Research Center’s questions about abortion, half of the sample is asked whether abortion should be “legal in all cases, legal in most cases, illegal in most cases, illegal in all cases,” while the other half of the sample is asked the same question with the response categories read in reverse order, starting with “illegal in all cases.” Again, reversing the order does not eliminate the recency effect but distributes it randomly across the population.

Question wording

The choice of words and phrases in a question is critical in expressing the meaning and intent of the question to the respondent and ensuring that all respondents interpret the question the same way. Even small wording differences can substantially affect the answers people provide.

An example of a wording difference that had a significant impact on responses comes from a January 2003 Pew Research Center survey. When people were asked whether they would “favor or oppose taking military action in Iraq to end Saddam Hussein’s rule,” 68% said they favored military action while 25% said they opposed military action. However, when asked whether they would “favor or oppose taking military action in Iraq to end Saddam Hussein’s rule  even if it meant that U.S. forces might suffer thousands of casualties, ” responses were dramatically different; only 43% said they favored military action, while 48% said they opposed it. The introduction of U.S. casualties altered the context of the question and influenced whether people favored or opposed military action in Iraq.

There has been a substantial amount of research to gauge the impact of different ways of asking questions and how to minimize differences in the way respondents interpret what is being asked. The issues related to question wording are more numerous than can be treated adequately in this short space, but below are a few of the important things to consider:

First, it is important to ask questions that are clear and specific and that each respondent will be able to answer. If a question is open-ended, it should be evident to respondents that they can answer in their own words and what type of response they should provide (an issue or problem, a month, number of days, etc.). Closed-ended questions should include all reasonable responses (i.e., the list of options is exhaustive) and the response categories should not overlap (i.e., response options should be mutually exclusive). Further, it is important to discern when it is best to use forced-choice close-ended questions (often denoted with a radio button in online surveys) versus “select-all-that-apply” lists (or check-all boxes). A 2019 Center study found that forced-choice questions tend to yield more accurate responses, especially for sensitive questions.  Based on that research, the Center generally avoids using select-all-that-apply questions.

It is also important to ask only one question at a time. Questions that ask respondents to evaluate more than one concept (known as double-barreled questions) – such as “How much confidence do you have in President Obama to handle domestic and foreign policy?” – are difficult for respondents to answer and often lead to responses that are difficult to interpret. In this example, it would be more effective to ask two separate questions, one about domestic policy and another about foreign policy.

In general, questions that use simple and concrete language are more easily understood by respondents. It is especially important to consider the education level of the survey population when thinking about how easy it will be for respondents to interpret and answer a question. Double negatives (e.g., do you favor or oppose  not  allowing gays and lesbians to legally marry) or unfamiliar abbreviations or jargon (e.g., ANWR instead of Arctic National Wildlife Refuge) can result in respondent confusion and should be avoided.

Similarly, it is important to consider whether certain words may be viewed as biased or potentially offensive to some respondents, as well as the emotional reaction that some words may provoke. For example, in a 2005 Pew Research Center survey, 51% of respondents said they favored “making it legal for doctors to give terminally ill patients the means to end their lives,” but only 44% said they favored “making it legal for doctors to assist terminally ill patients in committing suicide.” Although both versions of the question are asking about the same thing, the reaction of respondents was different. In another example, respondents have reacted differently to questions using the word “welfare” as opposed to the more generic “assistance to the poor.” Several experiments have shown that there is much greater public support for expanding “assistance to the poor” than for expanding “welfare.”

We often write two versions of a question and ask half of the survey sample one version of the question and the other half the second version. Thus, we say we have two  forms  of the questionnaire. Respondents are assigned randomly to receive either form, so we can assume that the two groups of respondents are essentially identical. On questions where two versions are used, significant differences in the answers between the two forms tell us that the difference is a result of the way we worded the two versions.

One of the most common formats used in survey questions is the “agree-disagree” format. In this type of question, respondents are asked whether they agree or disagree with a particular statement. Research has shown that, compared with the better educated and better informed, less educated and less informed respondents have a greater tendency to agree with such statements. This is sometimes called an “acquiescence bias” (since some kinds of respondents are more likely to acquiesce to the assertion than are others). This behavior is even more pronounced when there’s an interviewer present, rather than when the survey is self-administered. A better practice is to offer respondents a choice between alternative statements. A Pew Research Center experiment with one of its routinely asked values questions illustrates the difference that question format can make. Not only does the forced choice format yield a very different result overall from the agree-disagree format, but the pattern of answers between respondents with more or less formal education also tends to be very different.

One other challenge in developing questionnaires is what is called “social desirability bias.” People have a natural tendency to want to be accepted and liked, and this may lead people to provide inaccurate answers to questions that deal with sensitive subjects. Research has shown that respondents understate alcohol and drug use, tax evasion and racial bias. They also may overstate church attendance, charitable contributions and the likelihood that they will vote in an election. Researchers attempt to account for this potential bias in crafting questions about these topics. For instance, when Pew Research Center surveys ask about past voting behavior, it is important to note that circumstances may have prevented the respondent from voting: “In the 2012 presidential election between Barack Obama and Mitt Romney, did things come up that kept you from voting, or did you happen to vote?” The choice of response options can also make it easier for people to be honest. For example, a question about church attendance might include three of six response options that indicate infrequent attendance. Research has also shown that social desirability bias can be greater when an interviewer is present (e.g., telephone and face-to-face surveys) than when respondents complete the survey themselves (e.g., paper and web surveys).

Lastly, because slight modifications in question wording can affect responses, identical question wording should be used when the intention is to compare results to those from earlier surveys. Similarly, because question wording and responses can vary based on the mode used to survey respondents, researchers should carefully evaluate the likely effects on trend measurements if a different survey mode will be used to assess change in opinion over time.

Question order

Once the survey questions are developed, particular attention should be paid to how they are ordered in the questionnaire. Surveyors must be attentive to how questions early in a questionnaire may have unintended effects on how respondents answer subsequent questions. Researchers have demonstrated that the order in which questions are asked can influence how people respond; earlier questions can unintentionally provide context for the questions that follow (these effects are called “order effects”).

One kind of order effect can be seen in responses to open-ended questions. Pew Research Center surveys generally ask open-ended questions about national problems, opinions about leaders and similar topics near the beginning of the questionnaire. If closed-ended questions that relate to the topic are placed before the open-ended question, respondents are much more likely to mention concepts or considerations raised in those earlier questions when responding to the open-ended question.

For closed-ended opinion questions, there are two main types of order effects: contrast effects ( where the order results in greater differences in responses), and assimilation effects (where responses are more similar as a result of their order).

An example of a contrast effect can be seen in a Pew Research Center poll conducted in October 2003, a dozen years before same-sex marriage was legalized in the U.S. That poll found that people were more likely to favor allowing gays and lesbians to enter into legal agreements that give them the same rights as married couples when this question was asked after one about whether they favored or opposed allowing gays and lesbians to marry (45% favored legal agreements when asked after the marriage question, but 37% favored legal agreements without the immediate preceding context of a question about same-sex marriage). Responses to the question about same-sex marriage, meanwhile, were not significantly affected by its placement before or after the legal agreements question.

Another experiment embedded in a December 2008 Pew Research Center poll also resulted in a contrast effect. When people were asked “All in all, are you satisfied or dissatisfied with the way things are going in this country today?” immediately after having been asked “Do you approve or disapprove of the way George W. Bush is handling his job as president?”; 88% said they were dissatisfied, compared with only 78% without the context of the prior question.

Responses to presidential approval remained relatively unchanged whether national satisfaction was asked before or after it. A similar finding occurred in December 2004 when both satisfaction and presidential approval were much higher (57% were dissatisfied when Bush approval was asked first vs. 51% when general satisfaction was asked first).

Several studies also have shown that asking a more specific question before a more general question (e.g., asking about happiness with one’s marriage before asking about one’s overall happiness) can result in a contrast effect. Although some exceptions have been found, people tend to avoid redundancy by excluding the more specific question from the general rating.

Assimilation effects occur when responses to two questions are more consistent or closer together because of their placement in the questionnaire. We found an example of an assimilation effect in a Pew Research Center poll conducted in November 2008 when we asked whether Republican leaders should work with Obama or stand up to him on important issues and whether Democratic leaders should work with Republican leaders or stand up to them on important issues. People were more likely to say that Republican leaders should work with Obama when the question was preceded by the one asking what Democratic leaders should do in working with Republican leaders (81% vs. 66%). However, when people were first asked about Republican leaders working with Obama, fewer said that Democratic leaders should work with Republican leaders (71% vs. 82%).

The order questions are asked is of particular importance when tracking trends over time. As a result, care should be taken to ensure that the context is similar each time a question is asked. Modifying the context of the question could call into question any observed changes over time (see  measuring change over time  for more information).

A questionnaire, like a conversation, should be grouped by topic and unfold in a logical order. It is often helpful to begin the survey with simple questions that respondents will find interesting and engaging. Throughout the survey, an effort should be made to keep the survey interesting and not overburden respondents with several difficult questions right after one another. Demographic questions such as income, education or age should not be asked near the beginning of a survey unless they are needed to determine eligibility for the survey or for routing respondents through particular sections of the questionnaire. Even then, it is best to precede such items with more interesting and engaging questions. One virtue of survey panels like the ATP is that demographic questions usually only need to be asked once a year, not in each survey.

U.S. Surveys

Other research methods.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .

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Home Market Research

Quantitative Research: What It Is, Practices & Methods

Quantitative research involves analyzing and gathering numerical data to uncover trends, calculate averages, evaluate relationships, and derive overarching insights. It’s used in various fields, including the natural and social sciences. Quantitative data analysis employs statistical techniques for processing and interpreting numeric data.

Research designs in the quantitative realm outline how data will be collected and analyzed with methods like experiments and surveys. Qualitative methods complement quantitative research by focusing on non-numerical data, adding depth to understanding. Data collection methods can be qualitative or quantitative, depending on research goals. Researchers often use a combination of both approaches to gain a comprehensive understanding of phenomena.

What is Quantitative Research?

Quantitative research is a systematic investigation of phenomena by gathering quantifiable data and performing statistical, mathematical, or computational techniques. Quantitative research collects statistically significant information from existing and potential customers using sampling methods and sending out online surveys , online polls , and questionnaires , for example.

One of the main characteristics of this type of research is that the results can be depicted in numerical form. After carefully collecting structured observations and understanding these numbers, it’s possible to predict the future of a product or service, establish causal relationships or Causal Research , and make changes accordingly. Quantitative research primarily centers on the analysis of numerical data and utilizes inferential statistics to derive conclusions that can be extrapolated to the broader population.

An example of a quantitative research study is the survey conducted to understand how long a doctor takes to tend to a patient when the patient walks into the hospital. A patient satisfaction survey can be administered to ask questions like how long a doctor takes to see a patient, how often a patient walks into a hospital, and other such questions, which are dependent variables in the research. This kind of research method is often employed in the social sciences, and it involves using mathematical frameworks and theories to effectively present data, ensuring that the results are logical, statistically sound, and unbiased.

Data collection in quantitative research uses a structured method and is typically conducted on larger samples representing the entire population. Researchers use quantitative methods to collect numerical data, which is then subjected to statistical analysis to determine statistically significant findings. This approach is valuable in both experimental research and social research, as it helps in making informed decisions and drawing reliable conclusions based on quantitative data.

Quantitative Research Characteristics

Quantitative research has several unique characteristics that make it well-suited for specific projects. Let’s explore the most crucial of these characteristics so that you can consider them when planning your next research project:

• Structured tools: Quantitative research relies on structured tools such as surveys, polls, or questionnaires to gather quantitative data . Using such structured methods helps collect in-depth and actionable numerical data from the survey respondents, making it easier to perform data analysis.
• Sample size: Quantitative research is conducted on a significant sample size  representing the target market . Appropriate Survey Sampling methods, a fundamental aspect of quantitative research methods, must be employed when deriving the sample to fortify the research objective and ensure the reliability of the results.
• Close-ended questions: Closed-ended questions , specifically designed to align with the research objectives, are a cornerstone of quantitative research. These questions facilitate the collection of quantitative data and are extensively used in data collection processes.
• Prior studies: Before collecting feedback from respondents, researchers often delve into previous studies related to the research topic. This preliminary research helps frame the study effectively and ensures the data collection process is well-informed.
• Quantitative data: Typically, quantitative data is represented using tables, charts, graphs, or other numerical forms. This visual representation aids in understanding the collected data and is essential for rigorous data analysis, a key component of quantitative research methods.
• Generalization of results: One of the strengths of quantitative research is its ability to generalize results to the entire population. It means that the findings derived from a sample can be extrapolated to make informed decisions and take appropriate actions for improvement based on numerical data analysis.

Quantitative Research Methods

Quantitative research methods are systematic approaches used to gather and analyze numerical data to understand and draw conclusions about a phenomenon or population. Here are the quantitative research methods:

• Primary quantitative research methods
• Secondary quantitative research methods

Primary Quantitative Research Methods

Primary quantitative research is the most widely used method of conducting market research. The distinct feature of primary research is that the researcher focuses on collecting data directly rather than depending on data collected from previously done research. Primary quantitative research design can be broken down into three further distinctive tracks and the process flow. They are:

A. Techniques and Types of Studies

There are multiple types of primary quantitative research. They can be distinguished into the four following distinctive methods, which are:

01. Survey Research

Survey Research is fundamental for all quantitative outcome research methodologies and studies. Surveys are used to ask questions to a sample of respondents, using various types such as online polls, online surveys, paper questionnaires, web-intercept surveys , etc. Every small and big organization intends to understand what their customers think about their products and services, how well new features are faring in the market, and other such details.

By conducting survey research, an organization can ask multiple survey questions , collect data from a pool of customers, and analyze this collected data to produce numerical results. It is the first step towards collecting data for any research. You can use single ease questions . A single-ease question is a straightforward query that elicits a concise and uncomplicated response.

This type of research can be conducted with a specific target audience group and also can be conducted across multiple groups along with comparative analysis . A prerequisite for this type of research is that the sample of respondents must have randomly selected members. This way, a researcher can easily maintain the accuracy of the obtained results as a huge variety of respondents will be addressed using random selection. 

Traditionally, survey research was conducted face-to-face or via phone calls. Still, with the progress made by online mediums such as email or social media, survey research has also spread to online mediums.There are two types of surveys , either of which can be chosen based on the time in hand and the kind of data required:

Cross-sectional surveys: Cross-sectional surveys are observational surveys conducted in situations where the researcher intends to collect data from a sample of the target population at a given point in time. Researchers can evaluate various variables at a particular time. Data gathered using this type of survey is from people who depict similarity in all variables except the variables which are considered for research . Throughout the survey, this one variable will stay constant.

• Cross-sectional surveys are popular with retail, SMEs, and healthcare industries. Information is garnered without modifying any parameters in the variable ecosystem.
• Multiple samples can be analyzed and compared using a cross-sectional survey research method.
• Multiple variables can be evaluated using this type of survey research.
• The only disadvantage of cross-sectional surveys is that the cause-effect relationship of variables cannot be established as it usually evaluates variables at a particular time and not across a continuous time frame.

Longitudinal surveys: Longitudinal surveys are also observational surveys , but unlike cross-sectional surveys, longitudinal surveys are conducted across various time durations to observe a change in respondent behavior and thought processes. This time can be days, months, years, or even decades. For instance, a researcher planning to analyze the change in buying habits of teenagers over 5 years will conduct longitudinal surveys.

• In cross-sectional surveys, the same variables were evaluated at a given time, and in longitudinal surveys, different variables can be analyzed at different intervals.
• Longitudinal surveys are extensively used in the field of medicine and applied sciences. Apart from these two fields, they are also used to observe a change in the market trend analysis , analyze customer satisfaction, or gain feedback on products/services.
• In situations where the sequence of events is highly essential, longitudinal surveys are used.
• Researchers say that when research subjects need to be thoroughly inspected before concluding, they rely on longitudinal surveys.

02. Correlational Research

A comparison between two entities is invariable. Correlation research is conducted to establish a relationship between two closely-knit entities and how one impacts the other, and what changes are eventually observed. This research method is carried out to give value to naturally occurring relationships, and a minimum of two different groups are required to conduct this quantitative research method successfully. Without assuming various aspects, a relationship between two groups or entities must be established.

Researchers use this quantitative research design to correlate two or more variables using mathematical analysis methods. Patterns, relationships, and trends between variables are concluded as they exist in their original setup. The impact of one of these variables on the other is observed, along with how it changes the relationship between the two variables. Researchers tend to manipulate one of the variables to attain the desired results.

Ideally, it is advised not to make conclusions merely based on correlational research. This is because it is not mandatory that if two variables are in sync that they are interrelated.

Example of Correlational Research Questions :

• The relationship between stress and depression.
• The equation between fame and money.
• The relation between activities in a third-grade class and its students.

03. Causal-comparative Research

This research method mainly depends on the factor of comparison. Also called quasi-experimental research , this quantitative research method is used by researchers to conclude the cause-effect equation between two or more variables, where one variable is dependent on the other independent variable. The independent variable is established but not manipulated, and its impact on the dependent variable is observed. These variables or groups must be formed as they exist in the natural setup. As the dependent and independent variables will always exist in a group, it is advised that the conclusions are carefully established by keeping all the factors in mind.

Causal-comparative research is not restricted to the statistical analysis of two variables but extends to analyzing how various variables or groups change under the influence of the same changes. This research is conducted irrespective of the type of relationship that exists between two or more variables. Statistical analysis plan is used to present the outcome using this quantitative research method.

Example of Causal-Comparative Research Questions:

• The impact of drugs on a teenager. The effect of good education on a freshman. The effect of substantial food provision in the villages of Africa.

04. Experimental Research

Also known as true experimentation, this research method relies on a theory. As the name suggests, experimental research is usually based on one or more theories. This theory has yet to be proven before and is merely a supposition. In experimental research, an analysis is done around proving or disproving the statement. This research method is used in natural sciences. Traditional research methods are more effective than modern techniques.

There can be multiple theories in experimental research. A theory is a statement that can be verified or refuted.

After establishing the statement, efforts are made to understand whether it is valid or invalid. This quantitative research method is mainly used in natural or social sciences as various statements must be proved right or wrong.

• Traditional research methods are more effective than modern techniques.
• Systematic teaching schedules help children who struggle to cope with the course.
• It is a boon to have responsible nursing staff for ailing parents.

B. Data Collection Methodologies

The second major step in primary quantitative research is data collection. Data collection can be divided into sampling methods and data collection using surveys and polls.

01. Data Collection Methodologies: Sampling Methods

There are two main sampling methods for quantitative research: Probability and Non-probability sampling .

Probability sampling: A theory of probability is used to filter individuals from a population and create samples in probability sampling . Participants of a sample are chosen by random selection processes. Each target audience member has an equal opportunity to be selected in the sample.

There are four main types of probability sampling:

• Simple random sampling: As the name indicates, simple random sampling is nothing but a random selection of elements for a sample. This sampling technique is implemented where the target population is considerably large.
• Stratified random sampling: In the stratified random sampling method , a large population is divided into groups (strata), and members of a sample are chosen randomly from these strata. The various segregated strata should ideally not overlap one another.
• Cluster sampling: Cluster sampling is a probability sampling method using which the main segment is divided into clusters, usually using geographic segmentation and demographic segmentation parameters.
• Systematic sampling: Systematic sampling is a technique where the starting point of the sample is chosen randomly, and all the other elements are chosen using a fixed interval. This interval is calculated by dividing the population size by the target sample size.

Non-probability sampling: Non-probability sampling is where the researcher’s knowledge and experience are used to create samples. Because of the researcher’s involvement, not all the target population members have an equal probability of being selected to be a part of a sample.

There are five non-probability sampling models:

• Convenience sampling: In convenience sampling , elements of a sample are chosen only due to one prime reason: their proximity to the researcher. These samples are quick and easy to implement as there is no other parameter of selection involved.
• Consecutive sampling: Consecutive sampling is quite similar to convenience sampling, except for the fact that researchers can choose a single element or a group of samples and conduct research consecutively over a significant period and then perform the same process with other samples.
• Quota sampling: Using quota sampling , researchers can select elements using their knowledge of target traits and personalities to form strata. Members of various strata can then be chosen to be a part of the sample as per the researcher’s understanding.
• Snowball sampling: Snowball sampling is conducted with target audiences who are difficult to contact and get information. It is popular in cases where the target audience for analysis research is rare to put together.
• Judgmental sampling: Judgmental sampling is a non-probability sampling method where samples are created only based on the researcher’s experience and research skill .

02. Data collection methodologies: Using surveys & polls

Once the sample is determined, then either surveys or polls can be distributed to collect the data for quantitative research.

Using surveys for primary quantitative research

A survey is defined as a research method used for collecting data from a pre-defined group of respondents to gain information and insights on various topics of interest. The ease of survey distribution and the wide number of people it can reach depending on the research time and objective makes it one of the most important aspects of conducting quantitative research.

Fundamental levels of measurement – nominal, ordinal, interval, and ratio scales

Four measurement scales are fundamental to creating a multiple-choice question in a survey. They are nominal, ordinal, interval, and ratio measurement scales without the fundamentals of which no multiple-choice questions can be created. Hence, it is crucial to understand these measurement levels to develop a robust survey.

Use of different question types

To conduct quantitative research, close-ended questions must be used in a survey. They can be a mix of multiple question types, including multiple-choice questions like semantic differential scale questions , rating scale questions , etc.

Survey Distribution and Survey Data Collection

In the above, we have seen the process of building a survey along with the research design to conduct primary quantitative research. Survey distribution to collect data is the other important aspect of the survey process. There are different ways of survey distribution. Some of the most commonly used methods are:

• Email: Sending a survey via email is the most widely used and effective survey distribution method. This method’s response rate is high because the respondents know your brand. You can use the QuestionPro email management feature to send out and collect survey responses.
• Buy respondents: Another effective way to distribute a survey and conduct primary quantitative research is to use a sample. Since the respondents are knowledgeable and are on the panel by their own will, responses are much higher.
• Embed survey on a website: Embedding a survey on a website increases a high number of responses as the respondent is already in close proximity to the brand when the survey pops up.
• Social distribution: Using social media to distribute the survey aids in collecting a higher number of responses from the people that are aware of the brand.
• QR code: QuestionPro QR codes store the URL for the survey. You can print/publish this code in magazines, signs, business cards, or on just about any object/medium.
• SMS survey: The SMS survey is a quick and time-effective way to collect a high number of responses.
• Offline Survey App: The QuestionPro App allows users to circulate surveys quickly, and the responses can be collected both online and offline.

Survey example

An example of a survey is a short customer satisfaction (CSAT) survey that can quickly be built and deployed to collect feedback about what the customer thinks about a brand and how satisfied and referenceable the brand is.

Using polls for primary quantitative research

Polls are a method to collect feedback using close-ended questions from a sample. The most commonly used types of polls are election polls and exit polls . Both of these are used to collect data from a large sample size but using basic question types like multiple-choice questions.

C. Data Analysis Techniques

The third aspect of primary quantitative research design is data analysis . After collecting raw data, there must be an analysis of this data to derive statistical inferences from this research. It is important to relate the results to the research objective and establish the statistical relevance of the results.

Remember to consider aspects of research that were not considered for the data collection process and report the difference between what was planned vs. what was actually executed.

It is then required to select precise Statistical Analysis Methods , such as SWOT, Conjoint, Cross-tabulation, etc., to analyze the quantitative data.

• SWOT analysis: SWOT Analysis stands for the acronym of Strengths, Weaknesses, Opportunities, and Threat analysis. Organizations use this statistical analysis technique to evaluate their performance internally and externally to develop effective strategies for improvement.
• Conjoint Analysis: Conjoint Analysis is a market analysis method to learn how individuals make complicated purchasing decisions. Trade-offs are involved in an individual’s daily activities, and these reflect their ability to decide from a complex list of product/service options.
• Cross-tabulation: Cross-tabulation is one of the preliminary statistical market analysis methods which establishes relationships, patterns, and trends within the various parameters of the research study.
• TURF Analysis: TURF Analysis , an acronym for Totally Unduplicated Reach and Frequency Analysis, is executed in situations where the reach of a favorable communication source is to be analyzed along with the frequency of this communication. It is used for understanding the potential of a target market.

Inferential statistics methods such as confidence interval, the margin of error, etc., can then be used to provide results.

Secondary Quantitative Research Methods

Secondary quantitative research or desk research is a research method that involves using already existing data or secondary data. Existing data is summarized and collated to increase the overall effectiveness of the research.

This research method involves collecting quantitative data from existing data sources like the internet, government resources, libraries, research reports, etc. Secondary quantitative research helps to validate the data collected from primary quantitative research and aid in strengthening or proving, or disproving previously collected data.

The following are five popularly used secondary quantitative research methods:

• Data available on the internet: With the high penetration of the internet and mobile devices, it has become increasingly easy to conduct quantitative research using the internet. Information about most research topics is available online, and this aids in boosting the validity of primary quantitative data.
• Government and non-government sources: Secondary quantitative research can also be conducted with the help of government and non-government sources that deal with market research reports. This data is highly reliable and in-depth and hence, can be used to increase the validity of quantitative research design.
• Public libraries: Now a sparingly used method of conducting quantitative research, it is still a reliable source of information, though. Public libraries have copies of important research that was conducted earlier. They are a storehouse of valuable information and documents from which information can be extracted.
• Educational institutions: Educational institutions conduct in-depth research on multiple topics, and hence, the reports that they publish are an important source of validation in quantitative research.
• Commercial information sources: Local newspapers, journals, magazines, radio, and TV stations are great sources to obtain data for secondary quantitative research. These commercial information sources have in-depth, first-hand information on market research, demographic segmentation, and similar subjects.

Quantitative Research Examples

Some examples of quantitative research are:

• A customer satisfaction template can be used if any organization would like to conduct a customer satisfaction (CSAT) survey . Through this kind of survey, an organization can collect quantitative data and metrics on the goodwill of the brand or organization in the customer’s mind based on multiple parameters such as product quality, pricing, customer experience, etc. This data can be collected by asking a net promoter score (NPS) question , matrix table questions, etc. that provide data in the form of numbers that can be analyzed and worked upon.
• Another example of quantitative research is an organization that conducts an event, collecting feedback from attendees about the value they see from the event. By using an event survey , the organization can collect actionable feedback about the satisfaction levels of customers during various phases of the event such as the sales, pre and post-event, the likelihood of recommending the organization to their friends and colleagues, hotel preferences for the future events and other such questions.

What are the Advantages of Quantitative Research?

There are many advantages to quantitative research. Some of the major advantages of why researchers use this method in market research are:

Collect Reliable and Accurate Data:

Quantitative research is a powerful method for collecting reliable and accurate quantitative data. Since data is collected, analyzed, and presented in numbers, the results obtained are incredibly reliable and objective. Numbers do not lie and offer an honest and precise picture of the conducted research without discrepancies. In situations where a researcher aims to eliminate bias and predict potential conflicts, quantitative research is the method of choice.

Quick Data Collection:

Quantitative research involves studying a group of people representing a larger population. Researchers use a survey or another quantitative research method to efficiently gather information from these participants, making the process of analyzing the data and identifying patterns faster and more manageable through the use of statistical analysis. This advantage makes quantitative research an attractive option for projects with time constraints.

Wider Scope of Data Analysis:

Quantitative research, thanks to its utilization of statistical methods, offers an extensive range of data collection and analysis. Researchers can delve into a broader spectrum of variables and relationships within the data, enabling a more thorough comprehension of the subject under investigation. This expanded scope is precious when dealing with complex research questions that require in-depth numerical analysis.

Eliminate Bias:

One of the significant advantages of quantitative research is its ability to eliminate bias. This research method leaves no room for personal comments or the biasing of results, as the findings are presented in numerical form. This objectivity makes the results fair and reliable in most cases, reducing the potential for researcher bias or subjectivity.

In summary, quantitative research involves collecting, analyzing, and presenting quantitative data using statistical analysis. It offers numerous advantages, including the collection of reliable and accurate data, quick data collection, a broader scope of data analysis, and the elimination of bias, making it a valuable approach in the field of research. When considering the benefits of quantitative research, it’s essential to recognize its strengths in contrast to qualitative methods and its role in collecting and analyzing numerical data for a more comprehensive understanding of research topics.

Best Practices to Conduct Quantitative Research

Here are some best practices for conducting quantitative research:

• Differentiate between quantitative and qualitative: Understand the difference between the two methodologies and apply the one that suits your needs best.
• Choose a suitable sample size: Ensure that you have a sample representative of your population and large enough to be statistically weighty.
• Keep your research goals clear and concise: Know your research goals before you begin data collection to ensure you collect the right amount and the right quantity of data.
• Keep the questions simple: Remember that you will be reaching out to a demographically wide audience. Pose simple questions for your respondents to understand easily.

Quantitative Research vs Qualitative Research

Quantitative research and qualitative research are two distinct approaches to conducting research, each with its own set of methods and objectives. Here’s a comparison of the two:

Quantitative Research

• Objective: The primary goal of quantitative research is to quantify and measure phenomena by collecting numerical data. It aims to test hypotheses, establish patterns, and generalize findings to a larger population.
• Data Collection: Quantitative research employs systematic and standardized approaches for data collection, including techniques like surveys, experiments, and observations that involve predefined variables. It is often collected from a large and representative sample.
• Data Analysis: Data is analyzed using statistical techniques, such as descriptive statistics, inferential statistics, and mathematical modeling. Researchers use statistical tests to draw conclusions and make generalizations based on numerical data.
• Sample Size: Quantitative research often involves larger sample sizes to ensure statistical significance and generalizability.
• Results: The results are typically presented in tables, charts, and statistical summaries, making them highly structured and objective.
• Generalizability: Researchers intentionally structure quantitative research to generate outcomes that can be helpful to a larger population, and they frequently seek to establish causative connections.
• Emphasis on Objectivity: Researchers aim to minimize bias and subjectivity, focusing on replicable and objective findings.

Qualitative Research

• Objective: Qualitative research seeks to gain a deeper understanding of the underlying motivations, behaviors, and experiences of individuals or groups. It explores the context and meaning of phenomena.
• Data Collection: Qualitative research employs adaptable and open-ended techniques for data collection, including methods like interviews, focus groups, observations, and content analysis. It allows participants to express their perspectives in their own words.
• Data Analysis: Data is analyzed through thematic analysis, content analysis, or grounded theory. Researchers focus on identifying patterns, themes, and insights in the data.
• Sample Size: Qualitative research typically involves smaller sample sizes due to the in-depth nature of data collection and analysis.
• Results: Findings are presented in narrative form, often in the participants’ own words. Results are subjective, context-dependent, and provide rich, detailed descriptions.
• Generalizability: Qualitative research does not aim for broad generalizability but focuses on in-depth exploration within a specific context. It provides a detailed understanding of a particular group or situation.
• Emphasis on Subjectivity: Researchers acknowledge the role of subjectivity and the researcher’s influence on the Research Process . Participant perspectives and experiences are central to the findings.

Researchers choose between quantitative and qualitative research methods based on their research objectives and the nature of the research question. Each approach has its advantages and drawbacks, and the decision between them hinges on the particular research objectives and the data needed to address research inquiries effectively.

Quantitative research is a structured way of collecting and analyzing data from various sources. Its purpose is to quantify the problem and understand its extent, seeking results that someone can project to a larger population.

Companies that use quantitative rather than qualitative research typically aim to measure magnitudes and seek objectively interpreted statistical results. So if you want to obtain quantitative data that helps you define the structured cause-and-effect relationship between the research problem and the factors, you should opt for this type of research.

At QuestionPro , we have various Best Data Collection Tools and features to conduct investigations of this type. You can create questionnaires and distribute them through our various methods. We also have sample services or various questions to guarantee the success of your study and the quality of the collected data.

Quantitative research is a systematic and structured approach to studying phenomena that involves the collection of measurable data and the application of statistical, mathematical, or computational techniques for analysis.

Quantitative research is characterized by structured tools like surveys, substantial sample sizes, closed-ended questions, reliance on prior studies, data presented numerically, and the ability to generalize findings to the broader population.

The two main methods of quantitative research are Primary quantitative research methods, involving data collection directly from sources, and Secondary quantitative research methods, which utilize existing data for analysis.

1.Surveying to measure employee engagement with numerical rating scales. 2.Analyzing sales data to identify trends in product demand and market share. 4.Examining test scores to assess the impact of a new teaching method on student performance. 4.Using website analytics to track user behavior and conversion rates for an online store.

1.Differentiate between quantitative and qualitative approaches. 2.Choose a representative sample size. 3.Define clear research goals before data collection. 4.Use simple and easily understandable survey questions.

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Survey questions 101: 70+ survey question examples, types of surveys, and FAQs

How well do you understand your prospects and customers—who they are, what keeps them awake at night, and what brought them to your business in search of a solution? Asking the right survey questions at the right point in their customer journey is the most effective way to put yourself in your customers’ shoes.

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This comprehensive intro to survey questions contains over 70 examples of effective questions, an overview of different types of survey questions, and advice on how to word them for maximum effect. Plus, we’ll toss in our pre-built survey templates, expert survey insights, and tips to make the most of AI for Surveys in Hotjar. ✨

Surveying your users is the simplest way to understand their pain points, needs, and motivations. But first, you need to know how to set up surveys that give you the answers you—and your business—truly need. Impactful surveys start here:

❓ The main types of survey questions : most survey questions are classified as open-ended, closed-ended, nominal, Likert scale, rating scale, and yes/no. The best surveys often use a combination of questions.

💡 70+ good survey question examples : our top 70+ survey questions, categorized across ecommerce, SaaS, and publishing, will help you find answers to your business’s most burning questions

✅ What makes a survey question ‘good’ : a good survey question is anything that helps you get clear insights and business-critical information about your customers 

❌ The dos and don’ts of writing good survey questions : remember to be concise and polite, use the foot-in-door principle, alternate questions, and test your surveys. But don’t ask leading or loaded questions, overwhelm respondents with too many questions, or neglect other tools that can get you the answers you need.

👍 How to run your surveys the right way : use a versatile survey tool like Hotjar Surveys that allows you to create on-site surveys at specific points in the customer journey or send surveys via a link

🛠️ 10 use cases for good survey questions : use your survey insights to create user personas, understand pain points, measure product-market fit, get valuable testimonials, measure customer satisfaction, and more

Use Hotjar to build your survey and get the customer insight you need to grow your business.

6 main types of survey questions

Let’s dive into our list of survey question examples, starting with a breakdown of the six main categories your questions will fall into:

Open-ended questions

Closed-ended questions

Nominal questions

Likert scale questions

Rating scale questions

'Yes' or 'no' questions

1. Open-ended survey questions

Open-ended questions  give your respondents the freedom to  answer in their own words , instead of limiting their response to a set of pre-selected choices (such as multiple-choice answers, yes/no answers, 0–10 ratings, etc.). 

Examples of open-ended questions:

What other products would you like to see us offer?

If you could change just one thing about our product, what would it be?

When to use open-ended questions in a survey

The majority of example questions included in this post are open-ended, and there are some good reasons for that:

Open-ended questions help you learn about customer needs you didn’t know existed , and they shine a light on areas for improvement that you may not have considered before. If you limit your respondents’ answers, you risk cutting yourself off from key insights.

Open-ended questions are very useful when you first begin surveying your customers and collecting their feedback. If you don't yet have a good amount of insight, answers to open-ended questions will go a long way toward educating you about who your customers are and what they're looking for.

There are, however, a few downsides to open-ended questions:

First, people tend to be less likely to respond to open-ended questions in general because they take comparatively more effort to answer than, say, a yes/no one

Second, but connected: if you ask consecutive open-ended questions during your survey, people will get tired of answering them, and their answers might become less helpful the more you ask

Finally, the data you receive from open-ended questions will take longer to analyze compared to easy 1-5 or yes/no answers—but don’t let that stop you. There are plenty of shortcuts that make it easier than it looks (we explain it all in our post about how to analyze open-ended questions , which includes a free analysis template.)

💡 Pro tip: if you’re using Hotjar Surveys, let our AI for Surveys feature analyze your open-ended survey responses for you. Hotjar AI reviews all your survey responses and provides an automated summary report of key findings, including supporting quotes and actionable recommendations for next steps.

2. Closed-ended survey questions

Closed-end questions limit a user’s response options to a set of pre-selected choices. This broad category of questions includes

‘Yes’ or ‘no’ questions

When to use closed-ended questions

Closed-ended questions work brilliantly in two scenarios:

To open a survey, because they require little time and effort and are therefore easy for people to answer. This is called the foot-in-the-door principle: once someone commits to answering the first question, they may be more likely to answer the open-ended questions that follow.

When you need to create graphs and trends based on people’s answers. Responses to closed-ended questions are easy to measure and use as benchmarks. Rating scale questions, in particular (e.g. where people rate customer service or on a scale of 1-10), allow you to gather customer sentiment and compare your progress over time.

3. Nominal questions

A nominal question is a type of survey question that presents people with multiple answer choices; the answers are  non-numerical in nature and don't overlap  (unless you include an ‘all of the above’ option).

Example of nominal question:

What are you using [product name] for?

Personal use

Both business and personal use

When to use nominal questions

Nominal questions work well when there is a limited number of categories for a given question (see the example above). They’re easy to create graphs and trends from, but the downside is that you may not be offering enough categories for people to reply.

For example, if you ask people what type of browser they’re using and only give them three options to choose from, you may inadvertently alienate everybody who uses a fourth type and now can’t tell you about it.

That said, you can add an open-ended component to a nominal question with an expandable ’other’ category, where respondents can write in an answer that isn’t on the list. This way, you essentially ask an open-ended question that doesn’t limit them to the options you’ve picked.

4. Likert scale questions

The Likert scale is typically a 5- or 7-point scale that evaluates a respondent’s level of agreement with a statement or the intensity of their reaction toward something.

The scale develops symmetrically: the median number (e.g. a 3 on a 5-point scale) indicates a point of neutrality, the lowest number (always 1) indicates an extreme view, and the highest number (e.g. a 5 on a 5-point scale) indicates the opposite extreme view.

Example of a Likert scale question:

When to use Likert scale questions

Likert-type questions are also known as ordinal questions because the answers are presented in a specific order. Like other multiple-choice questions, Likert scale questions come in handy when you already have some sense of what your customers are thinking. For example, if your open-ended questions uncover a complaint about a recent change to your ordering process, you could use a Likert scale question to determine how the average user felt about the change.

A series of Likert scale questions can also be turned into a matrix question. Since they have identical response options, they are easily combined into a single matrix and break down the pattern of single questions for users.

5. Rating scale questions

Rating scale questions are questions where the answers map onto a numeric scale (such as rating customer support on a scale of 1-5, or likelihood to recommend a product from 0-10).

Examples of rating questions:

How likely are you to recommend us to a friend or colleague on a scale of 0-10?

How would you rate our customer service on a scale of 1-5?

When to use rating questions

Whenever you want to assign a numerical value to your survey or visualize and compare trends , a rating question is the way to go.

A typical rating question is used to determine Net Promoter Score® (NPS®) : the question asks customers to rate their likelihood of recommending products or services to their friends or colleagues, and allows you to look at the results historically and see if you're improving or getting worse. Rating questions are also used for customer satisfaction (CSAT) surveys and product reviews.

When you use a rating question in a survey, be sure to explain what the scale means (e.g. 1 for ‘Poor’, 5 for ‘Amazing’). And consider adding a follow-up open-ended question to understand why the user left that score.

Example of a rating question (NPS):

6. ‘Yes’ or ‘no’ questions

These dichotomous questions are super straightforward, requiring a simple ‘yes’ or ‘no’ reply.

Examples of yes/no questions:

Was this article useful? (Yes/No)

Did you find what you were looking for today? (Yes/No)

When to use ‘yes’ or ‘no’ questions

‘Yes’ and ‘no’ questions are a good way to quickly segment your respondents . For example, say you’re trying to understand what obstacles or objections prevent people from trying your product. You can place a survey on your pricing page asking people if something is stopping them, and follow up with the segment who replied ‘yes’ by asking them to elaborate further.

These questions are also effective for getting your foot in the door: a ‘yes’ or ‘no’ question requires very little effort to answer. Once a user commits to answering the first question, they tend to become more willing to answer the questions that follow, or even leave you their contact information.

70+ more survey question examples

Below is a list of good survey questions, categorized across ecommerce, software as a service (SaaS), and publishing. You don't have to use them word-for-word, but hopefully, this list will spark some extra-good ideas for the surveys you’ll run immediately after reading this article. (Plus, you can create all of them with Hotjar Surveys—stick with us a little longer to find out how. 😉)

📊 9 basic demographic survey questions

Ask these questions when you want context about your respondents and target audience, so you can segment them later. Consider including demographic information questions in your survey when conducting user or market research as well. 

But don’t ask demographic questions just for the sake of it—if you're not going to use some of the data points from these sometimes sensitive questions (e.g. if gender is irrelevant to the result of your survey), move on to the ones that are truly useful for you, business-wise. 

Take a look at the selection of examples below, and keep in mind that you can convert most of them to multiple choice questions:

What is your name?

What is your age?

What is your gender?

What company do you work for?

What vertical/industry best describes your company?

What best describes your role?

In which department do you work?

What is the total number of employees in your company (including all locations where your employer operates)?

What is your company's annual revenue?

🚀 Get started: gather more info about your users with our product-market fit survey template .

👥 20+ effective customer questions

These questions are particularly recommended for ecommerce companies:

Before purchase

What information is missing or would make your decision to buy easier?

What is your biggest fear or concern about purchasing this item?

Were you able to complete the purpose of your visit today?

If you did not make a purchase today, what stopped you?

After purchase

Was there anything about this checkout process we could improve?

What was your biggest fear or concern about purchasing from us?

What persuaded you to complete the purchase of the item(s) in your cart today?

If you could no longer use [product name], what’s the one thing you would miss the most?

What’s the one thing that nearly stopped you from buying from us?

👉 Check out our 7-step guide to setting up an ecommerce post-purchase survey .

Other useful customer questions

Do you have any questions before you complete your purchase?

What other information would you like to see on this page?

What were the three main things that persuaded you to create an account today?

What nearly stopped you from creating an account today?

Which other options did you consider before choosing [product name]?

What would persuade you to use us more often?

What was your biggest challenge, frustration, or problem in finding the right [product type] online?

Please list the top three things that persuaded you to use us rather than a competitor.

Were you able to find the information you were looking for?

How satisfied are you with our support?

How would you rate our service/support on a scale of 0-10? (0 = terrible, 10 = stellar)

How likely are you to recommend us to a friend or colleague? ( NPS question )

Is there anything preventing you from purchasing at this point?

🚀 Get started: learn how satisfied customers are with our expert-built customer satisfaction and NPS survey templates .

Set up a survey in seconds

Use Hotjar's free survey templates to build virtually any type of survey, and start gathering valuable insights in moments.

🛍 30+ product survey questions

These questions are particularly recommended for SaaS companies:

Questions for new or trial users

What nearly stopped you from signing up today?

How likely are you to recommend us to a friend or colleague on a scale of 0-10? (NPS question)

Is our pricing clear? If not, what would you change?

Questions for paying customers

What convinced you to pay for this service?

What’s the one thing we are missing in [product type]?

What's one feature we can add that would make our product indispensable for you?

If you could no longer use [name of product], what’s the one thing you would miss the most?

🚀 Get started: find out what your buyers really think with our pricing plan feedback survey template .

Questions for former/churned customers

What is the main reason you're canceling your account? Please be blunt and direct.

If you could have changed one thing in [product name], what would it have been?

If you had a magic wand and could change anything in [product name], what would it be?

🚀 Get started: find out why customers churn with our free-to-use churn analysis survey template .

Other useful product questions

What were the three main things that persuaded you to sign up today?

Do you have any questions before starting a free trial?

What persuaded you to start a trial?

Was this help section useful?

Was this article useful?

How would you rate our service/support on a scale of 1-10? (0 = terrible, 10 = stellar)

Is there anything preventing you from upgrading at this point?

Is there anything on this page that doesn't work the way you expected it to?

What could we change to make you want to continue using us?

If you did not upgrade today, what stopped you?

What's the next thing you think we should build?

How would you feel if we discontinued this feature?

What's the next feature or functionality we should build?

🚀 Get started: gather feedback on your product with our free-to-use product feedback survey template .

🖋 20+ effective questions for publishers and bloggers

Questions to help improve content.

If you could change just one thing in [publication name], what would it be?

What other content would you like to see us offer?

How would you rate this article on a scale of 1–10?

If you could change anything on this page, what would you have us do?

If you did not subscribe to [publication name] today, what was it that stopped you?

🚀 Get started: find ways to improve your website copy and messaging with our content feedback survey template .

New subscriptions

What convinced you to subscribe to [publication] today?

What almost stopped you from subscribing?

What were the three main things that persuaded you to join our list today?

Cancellations

What is the main reason you're unsubscribing? Please be specific.

Other useful content-related questions

What’s the one thing we are missing in [publication name]?

What would persuade you to visit us more often?

How likely are you to recommend us to someone with similar interests? (NPS question)

What’s missing on this page?

What topics would you like to see us write about next?

How useful was this article?

What could we do to make this page more useful?

Is there anything on this site that doesn't work the way you expected it to?

What's one thing we can add that would make [publication name] indispensable for you?

If you could no longer read [publication name], what’s the one thing you would miss the most?

💡 Pro tip: do you have a general survey goal in mind, but are struggling to pin down the right questions to ask? Give Hotjar’s AI for Surveys a go and watch as it generates a survey for you in seconds with questions tailored to the exact purpose of the survey you want to run.

What makes a good survey question?

We’ve run through more than 70 of our favorite survey questions—but what is it that makes a good survey question, well, good ? An effective question is anything that helps you get clear insights and business-critical information about your customers , including

Who your target market is

How you should price your products

What’s stopping people from buying from you

Why visitors leave your website

With this information, you can tailor your website, products, landing pages, and messaging to improve the user experience and, ultimately, maximize conversions .

How to write good survey questions: the DOs and DON’Ts

To help you understand the basics and avoid some rookie mistakes, we asked a few experts to give us their thoughts on what makes a good and effective survey question.

Survey question DOs

✅ do focus your questions on the customer.

It may be tempting to focus on your company or products, but it’s usually more effective to put the focus back on the customer. Get to know their needs, drivers, pain points, and barriers to purchase by asking about their experience. That’s what you’re after: you want to know what it’s like inside their heads and how they feel when they use your website and products.

Rather than asking, “Why did you buy our product?” ask, “What was happening in your life that led you to search for this solution?” Instead of asking, “What's the one feature you love about [product],” ask, “If our company were to close tomorrow, what would be the one thing you’d miss the most?” These types of surveys have helped me double and triple my clients.

✅ DO be polite and concise (without skimping on micro-copy)

Put time into your micro-copy—those tiny bits of written content that go into surveys. Explain why you’re asking the questions, and when people reach the end of the survey, remember to thank them for their time. After all, they’re giving you free labor!

✅ DO consider the foot-in-the-door principle

One way to increase your response rate is to ask an easy question upfront, such as a ‘yes’ or ‘no’ question, because once people commit to taking a survey—even just the first question—they’re more likely to finish it.

✅ DO consider asking your questions from the first-person perspective

Disclaimer: we don’t do this here at Hotjar. You’ll notice all our sample questions are listed in second-person (i.e. ‘you’ format), but it’s worth testing to determine which approach gives you better answers. Some experts prefer the first-person approach (i.e. ‘I’ format) because they believe it encourages users to talk about themselves—but only you can decide which approach works best for your business.

I strongly recommend that the questions be worded in the first person. This helps create a more visceral reaction from people and encourages them to tell stories from their actual experiences, rather than making up hypothetical scenarios. For example, here’s a similar question, asked two ways: “What do you think is the hardest thing about creating a UX portfolio?” versus “My biggest problem with creating my UX portfolio is…” 

The second version helps get people thinking about their experiences. The best survey responses come from respondents who provide personal accounts of past events that give us specific and real insight into their lives.

✅ DO alternate your questions often

Shake up the questions you ask on a regular basis. Asking a wide variety of questions will help you and your team get a complete view of what your customers are thinking.

✅ DO test your surveys before sending them out

A few years ago, Hotjar created a survey we sent to 2,000 CX professionals via email. Before officially sending it out, we wanted to make sure the questions really worked. 

We decided to test them out on internal staff and external people by sending out three rounds of test surveys to 100 respondents each time. Their feedback helped us perfect the questions and clear up any confusing language.

Survey question DON’Ts

❌ don’t ask closed-ended questions if you’ve never done research before.

If you’ve just begun asking questions, make them open-ended questions since you have no idea what your customers think about you at this stage. When you limit their answers, you just reinforce your own assumptions.

There are two exceptions to this rule:

Using a closed-ended question to get your foot in the door at the beginning of a survey

Using rating scale questions to gather customer sentiment (like an NPS survey)

❌ DON’T ask a lot of questions if you’re just getting started

Having to answer too many questions can overwhelm your users. Stick with the most important points and discard the rest.

Try starting off with a single question to see how your audience responds, then move on to two questions once you feel like you know what you’re doing.

How many questions should you ask? There’s really no perfect answer, but we recommend asking as few as you need to ask to get the information you want. In the beginning, focus on the big things:

Who are your users?

What do potential customers want?

How are they using your product?

What would win their loyalty?

❌ DON’T just ask a question when you can combine it with other tools

Don’t just use surveys to answer questions that other tools (such as analytics) can also answer. If you want to learn about whether people find a new website feature helpful, you can also observe how they’re using it through traditional analytics, session recordings , and other user testing tools for a more complete picture.

Don’t use surveys to ask people questions that other tools are better equipped to answer. I’m thinking of questions like “What do you think of the search feature?” with pre-set answer options like ‘Very easy to use,’ ‘Easy to use,’ etc. That’s not a good question to ask. 

Why should you care about what people ‘think’ about the search feature? You should find out whether it helps people find what they need and whether it helps drive conversions for you. Analytics, user session recordings, and user testing can tell you whether it does that or not.

❌ DON’T ask leading questions

A leading question is one that prompts a specific answer. Avoid asking leading questions because they’ll give you bad data. For example, asking, “What makes our product better than our competitors’ products?” might boost your self-esteem, but it won’t get you good information. Why? You’re effectively planting the idea that your own product is the best on the market.

❌ DON’T ask loaded questions

A loaded question is similar to a leading question, but it does more than just push a bias—it phrases the question such that it’s impossible to answer without confirming an underlying assumption.

A common (and subtle) form of loaded survey question would be, “What do you find useful about this article?” If we haven’t first asked you whether you found the article useful at all, then we’re asking a loaded question.

❌ DON’T ask about more than one topic at once

For example, “Do you believe our product can help you increase sales and improve cross-collaboration?”

This complex question, also known as a ‘double-barreled question’, requires a very complex answer as it begs the respondent to address two separate questions at once:

Do you believe our product can help you increase sales?

Do you believe our product can help you improve cross-collaboration?

Respondents may very well answer 'yes', but actually mean it for the first part of the question, and not the other. The result? Your survey data is inaccurate, and you’ve missed out on actionable insights.

Instead, ask two specific questions to gather customer feedback on each concept.

How to run your surveys

The format you pick for your survey depends on what you want to achieve and also on how much budget or resources you have. You can

Use an on-site survey tool , like Hotjar Surveys , to set up a website survey that pops up whenever people visit a specific page: this is useful when you want to investigate website- and product-specific topics quickly. This format is relatively inexpensive—with Hotjar’s free forever plan, you can even run up to 3 surveys with unlimited questions for free.

Use Hotjar Surveys to embed a survey as an element directly on a page: this is useful when you want to grab your audience’s attention and connect with customers at relevant moments, without interrupting their browsing. (Scroll to the bottom of this page to see an embedded survey in action!) This format is included on Hotjar’s Business and Scale plans—try it out for 15 days with a free Ask Business trial .

Use a survey builder and create a survey people can access in their own time: this is useful when you want to reach out to your mailing list or a wider audience with an email survey (you just need to share the URL the survey lives at). Sending in-depth questionnaires this way allows for more space for people to elaborate on their answers. This format is also relatively inexpensive, depending on the tool you use.

Place survey kiosks in a physical location where people can give their feedback by pressing a button: this is useful for quick feedback on specific aspects of a customer's experience (there’s usually plenty of these in airports and waiting rooms). This format is relatively expensive to maintain due to the material upkeep.

Run in-person surveys with your existing or prospective customers: in-person questionnaires help you dig deep into your interviewees’ answers. This format is relatively cheap if you do it online with a user interview tool or over the phone, but it’s more expensive and time-consuming if done in a physical location.

💡 Pro tip: looking for an easy, cost-efficient way to connect with your users? Run effortless, automated user interviews with Engage , Hotjar’s user interview tool. Get instant access to a pool of 200,000+ participants (or invite your own), and take notes while Engage records and transcribes your interview.

10 survey use cases: what you can do with good survey questions

Effective survey questions can help improve your business in many different ways. We’ve written in detail about most of these ideas in other blog posts, so we’ve rounded them up for you below.

1. Create user personas

A user persona is a character based on the people who currently use your website or product. A persona combines psychographics and demographics and reflects who they are, what they need, and what may stop them from getting it.

Examples of questions to ask:

Describe yourself in one sentence, e.g. “I am a 30-year-old marketer based in Dublin who enjoys writing articles about user personas.”

What is your main goal for using this website/product?

What, if anything, is preventing you from doing it?

👉 Our post about creating simple and effective user personas in four steps highlights some great survey questions to ask when creating a user persona.

🚀 Get started: use our user persona survey template or AI for Surveys to inform your user persona.

2. Understand why your product is not selling

Few things are more frightening than stagnant sales. When the pressure is mounting, you’ve got to get to the bottom of it, and good survey questions can help you do just that.

What made you buy the product? What challenges are you trying to solve?

What did you like most about the product? What did you dislike the most?

What nearly stopped you from buying?

👉 Here’s a detailed piece about the best survey questions to ask your customers when your product isn’t selling , and why they work so well.

🚀 Get started: our product feedback survey template helps you find out whether your product satisfies your users. Or build your surveys in the blink of an eye with Hotjar AI.

3. Understand why people leave your website

If you want to figure out why people are leaving your website , you’ll have to ask questions.

A good format for that is an exit-intent pop-up survey, which appears when a user clicks to leave the page, giving them the chance to leave website feedback before they go.

Another way is to focus on the people who did convert, but just barely—something Hotjar founder David Darmanin considers essential for taking conversions to the next level. By focusing on customers who bought your product (but almost didn’t), you can learn how to win over another set of users who are similar to them: those who almost bought your products, but backed out in the end.

Example of questions to ask:

Not for you? Tell us why. ( Exit-intent pop-up —ask this when a user leaves without buying.)

What almost stopped you from buying? (Ask this post-conversion .)

👉 Find out how HubSpot Academy increased its conversion rate by adding an exit-intent survey that asked one simple question when users left their website: “Not for you? Tell us why.”

🚀 Get started: place an exit-intent survey on your site. Let Hotjar AI draft the survey questions by telling it what you want to learn.

I spent the better half of my career focusing on the 95% who don’t convert, but it’s better to focus on the 5% who do. Get to know them really well, deliver value to them, and really wow them. That’s how you’re going to take that 5% to 10%.

4. Understand your customers’ fears and concerns

Buying a new product can be scary: nobody wants to make a bad purchase. Your job is to address your prospective customers’ concerns, counter their objections, and calm their fears, which should lead to more conversions.

👉 Take a look at our no-nonsense guide to increasing conversions for a comprehensive write-up about discovering the drivers, barriers, and hooks that lead people to converting on your website.

🚀 Get started: understand why your users are tempted to leave and discover potential barriers with a customer retention survey .

5. Drive your pricing strategy

Are your products overpriced and scaring away potential buyers? Or are you underpricing and leaving money on the table?

Asking the right questions will help you develop a pricing structure that maximizes profit, but you have to be delicate about how you ask. Don’t ask directly about price, or you’ll seem unsure of the value you offer. Instead, ask questions that uncover how your products serve your customers and what would inspire them to buy more.

How do you use our product/service?

What would persuade you to use our product more often?

What’s the one thing our product is missing?

👉 We wrote a series of blog posts about managing the early stage of a SaaS startup, which included a post about developing the right pricing strategy —something businesses in all sectors could benefit from.

🚀 Get started: find the sweet spot in how to price your product or service with a Van Westendorp price sensitivity survey or get feedback on your pricing plan .

6. Measure and understand product-market fit

Product-market fit (PMF) is about understanding demand and creating a product that your customers want, need, and will actually pay money for. A combination of online survey questions and one-on-one interviews can help you figure this out.

What's one thing we can add that would make [product name] indispensable for you?

If you could change just one thing in [product name], what would it be?

👉 In our series of blog posts about managing the early stage of a SaaS startup, we covered a section on product-market fit , which has relevant information for all industries.

🚀 Get started: discover if you’re delivering the best products to your market with our product-market fit survey .

7. Choose effective testimonials

Human beings are social creatures—we’re influenced by people who are similar to us. Testimonials that explain how your product solved a problem for someone are the ultimate form of social proof. The following survey questions can help you get some great testimonials.

What changed for you after you got our product?

How does our product help you get your job done?

How would you feel if you couldn’t use our product anymore?

👉 In our post about positioning and branding your products , we cover the type of questions that help you get effective testimonials.

🚀 Get started: add a question asking respondents whether you can use their answers as testimonials in your surveys, or conduct user interviews to gather quotes from your users.

8. Measure customer satisfaction

It’s important to continually track your overall customer satisfaction so you can address any issues before they start to impact your brand’s reputation. You can do this with rating scale questions.

For example, at Hotjar, we ask for feedback after each customer support interaction (which is one important measure of customer satisfaction). We begin with a simple, foot-in-the-door question to encourage a response, and use the information to improve our customer support, which is strongly tied to overall customer satisfaction.

How would you rate the support you received? (1-5 scale)

If 1-3: How could we improve?

If 4-5: What did you love about the experience?

👉 Our beginner’s guide to website feedback goes into great detail about how to measure customer service, NPS , and other important success metrics.

🚀 Get started: gauge short-term satisfaction level with a CSAT survey .

9. Measure word-of-mouth recommendations

Net Promoter Score is a measure of how likely your customers are to recommend your products or services to their friends or colleagues. NPS is a higher bar than customer satisfaction because customers have to be really impressed with your product to recommend you.

Example of NPS questions (to be asked in the same survey):

How likely are you to recommend this company to a friend or colleague? (0-10 scale)

What’s the main reason for your score?

What should we do to WOW you?

👉 We created an NPS guide with ecommerce companies in mind, but it has plenty of information that will help companies in other industries as well.

🚀 Get started: measure whether your users would refer you to a friend or colleague with an NPS survey . Then, use our free NPS calculator to crunch the numbers.

10. Redefine your messaging

How effective is your messaging? Does it speak to your clients' needs, drives, and fears? Does it speak to your strongest selling points?

Asking the right survey questions can help you figure out what marketing messages work best, so you can double down on them.

What attracted you to [brand or product name]?

Did you have any concerns before buying [product name]?

Since you purchased [product name], what has been the biggest benefit to you?

If you could describe [brand or product name] in one sentence, what would you say?

What is your favorite thing about [brand or product name]?

How likely are you to recommend this product to a friend or colleague? (NPS question)

👉 We talk about positioning and branding your products in a post that’s part of a series written for SaaS startups, but even if you’re not in SaaS (or you’re not a startup), you’ll still find it helpful.

Have a question for your customers? Ask!

Feedback is at the heart of deeper empathy for your customers and a more holistic understanding of their behaviors and motivations. And luckily, people are more than ready to share their thoughts about your business— they're just waiting for you to ask them. Deeper customer insights start right here, with a simple tool like Hotjar Surveys.

Build surveys faster with AI🔥

Use AI in Hotjar Surveys to build your survey, place it on your website or send it via email, and get the customer insight you need to grow your business.

FAQs about survey questions

How many people should i survey/what should my sample size be.

A good rule of thumb is to aim for at least 100 replies that you can work with.

You can use our  sample size calculator  to get a more precise answer, but understand that collecting feedback is research, not experimentation. Unlike experimentation (such as A/B testing ), all is not lost if you can’t get a statistically significant sample size. In fact, as little as ten replies can give you actionable information about what your users want.

How many questions should my survey have?

There’s no perfect answer to this question, but we recommend asking as few as you need to ask in order to get the information you want. Remember, you’re essentially asking someone to work for free, so be respectful of their time.

Why is it important to ask good survey questions?

A good survey question is asked in a precise way at the right stage in the customer journey to give you insight into your customers’ needs and drives. The qualitative data you get from survey responses can supplement the insight you can capture through other traditional analytics tools (think Google Analytics) and behavior analytics tools (think heatmaps and session recordings , which visualize user behavior on specific pages or across an entire website).

The format you choose for your survey—in-person, email, on-page, etc.—is important, but if the questions themselves are poorly worded you could waste hours trying to fix minimal problems while ignoring major ones a different question could have uncovered. 

How do I analyze open-ended survey questions?

A big pile of  qualitative data  can seem intimidating, but there are some shortcuts that make it much easier to analyze. We put together a guide for  analyzing open-ended questions in 5 simple steps , which should answer all your questions.

But the fastest way to analyze open questions is to use the automated summary report with Hotjar AI in Surveys . AI turns the complex survey data into:

Key findings

Actionable insights

Will sending a survey annoy my customers?

Honestly, the real danger is  not  collecting feedback. Without knowing what users think about your page and  why  they do what they do, you’ll never create a user experience that maximizes conversions. The truth is, you’re probably already doing something that bugs them more than any survey or feedback button would.

If you’re worried that adding an on-page survey might hurt your conversion rate, start small and survey just 10% of your visitors. You can stop surveying once you have enough replies.

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

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Methodology

• Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

Table of contents

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

• Surveys :  List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
• Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
• Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

• Interviews : Asking open-ended questions verbally to respondents.
• Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
• Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
• Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

• Use quantitative research if you want to confirm or test something (a theory or hypothesis )
• Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

• Average scores ( means )
• The number of times a particular answer was given
• The correlation or causation between two or more variables
• The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

• Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
• Thematic analysis : Closely examining the data to identify the main themes and patterns
• Discourse analysis : Studying how communication works in social contexts

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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