Dissertations and research projects
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Developing a theoretical framework
Reflecting on your position, extended literature reviews, presenting qualitative data.
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What is a theoretical framework?
Developing a theoretical framework for your dissertation is one of the key elements of a qualitative research project. Through writing your literature review, you are likely to have identified either a problem that need ‘fixing’ or a gap that your research may begin to fill.
The theoretical framework is your toolbox . In the toolbox are your handy tools: a set of theories, concepts, ideas and hypotheses that you will use to build a solution to the research problem or gap you have identified.
The methodology is the instruction manual: the procedure and steps you have taken, using your chosen tools, to tackle the research problem.
Why do I need a theoretical framework?
Developing a theoretical framework shows that you have thought critically about the different ways to approach your topic, and that you have made a well-reasoned and evidenced decision about which approach will work best. theoretical frameworks are also necessary for solving complex problems or issues from the literature, showing that you have the skills to think creatively and improvise to answer your research questions. they also allow researchers to establish new theories and approaches, that future research may go on to develop., how do i create a theoretical framework for my dissertation.
First, select your tools. You are likely to need a variety of tools in qualitative research – different theories, models or concepts – to help you tackle different parts of your research question.
When deciding what tools would be best for the job of answering your research questions or problem, explore what existing research in your area has used. You may find that there is a ‘standard toolbox’ for qualitative research in your field that you can borrow from or apply to your own research.
You will need to justify why your chosen tools are best for the job of answering your research questions, at what stage they are most relevant, and how they relate to each other. Some theories or models will neatly fit together and appear in the toolboxes of other researchers. However, you may wish to incorporate a model or idea that is not typical for your research area – the ‘odd one out’ in your toolbox. If this is the case, make sure you justify and account for why it is useful to you, and look for ways that it can be used in partnership with the other tools you are using.
You should also be honest about limitations, or where you need to improvise (for example, if the ‘right’ tool or approach doesn’t exist in your area).
This video from the Skills Centre includes an overview and example of how you might create a theoretical framework for your dissertation:
How do I choose the 'right' approach?
When designing your framework and choosing what to include, it can often be difficult to know if you’ve chosen the ‘right’ approach for your research questions. One way to check this is to look for consistency between your objectives, the literature in your framework, and your overall ethos for the research. This means ensuring that the literature you have used not only contributes to answering your research objectives, but that you also use theories and models that are true to your beliefs as a researcher.
Reflecting on your values and your overall ambition for the project can be a helpful step in making these decisions, as it can help you to fully connect your methodology and methods to your research aims.
Should I reflect on my position as a researcher?
If you feel your position as a researcher has influenced your choice of methods or procedure in any way, the methodology is a good place to reflect on this. Positionality acknowledges that no researcher is entirely objective: we are all, to some extent, influenced by prior learning, experiences, knowledge, and personal biases. This is particularly true in qualitative research or practice-based research, where the student is acting as a researcher in their own workplace, where they are otherwise considered a practitioner/professional. It's also important to reflect on your positionality if you belong to the same community as your participants where this is the grounds for their involvement in the research (ie. you are a mature student interviewing other mature learners about their experences in higher education).
The following questions can help you to reflect on your positionality and gauge whether this is an important section to include in your dissertation (for some people, this section isn’t necessary or relevant):
- How might my personal history influence how I approach the topic?
- How am I positioned in relation to this knowledge? Am I being influenced by prior learning or knowledge from outside of this course?
- How does my gender/social class/ ethnicity/ culture influence my positioning in relation to this topic?
- Do I share any attributes with my participants? Are we part of a s hared community? How might this have influenced our relationship and my role in interviews/observations?
- Am I invested in the outcomes on a personal level? Who is this research for and who will feel the benefits?
One option for qualitative projects is to write an extended literature review. This type of project does not require you to collect any new data. Instead, you should focus on synthesising a broad range of literature to offer a new perspective on a research problem or question.
The main difference between an extended literature review and a dissertation where primary data is collected, is in the presentation of the methodology, results and discussion sections. This is because extended literature reviews do not actively involve participants or primary data collection, so there is no need to outline a procedure for data collection (the methodology) or to present and interpret ‘data’ (in the form of interview transcripts, numerical data, observations etc.) You will have much more freedom to decide which sections of the dissertation should be combined, and whether new chapters or sections should be added.
Here is an overview of a common structure for an extended literature review:
- Provide background information and context to set the ‘backdrop’ for your project.
- Explain the value and relevance of your research in this context. Outline what do you hope to contribute with your dissertation.
- Clarify a specific area of focus.
- Introduce your research aims (or problem) and objectives.
You will need to write a short, overview literature review to introduce the main theories, concepts and key research areas that you will explore in your dissertation. This set of texts – which may be theoretical, research-based, practice-based or policies – form your theoretical framework. In other words, by bringing these texts together in the literature review, you are creating a lens that you can then apply to more focused examples or scenarios in your discussion chapters.
As you will not be collecting primary data, your methodology will be quite different from a typical dissertation. You will need to set out the process and procedure you used to find and narrow down your literature. This is also known as a search strategy.
Including your search strategy
A search strategy explains how you have narrowed down your literature to identify key studies and areas of focus. This often takes the form of a search strategy table, included as an appendix at the end of the dissertation. If included, this section takes the place of the traditional 'methodology' section.
If you choose to include a search strategy table, you should also give an overview of your reading process in the main body of the dissertation. Think of this as a chronology of the practical steps you took and your justification for doing so at each stage, such as:
- Your key terms, alternatives and synonyms, and any terms that you chose to exclude.
- Your choice and combination of databases;
- Your inclusion/exclusion criteria, when they were applied and why. This includes filters such as language of publication, date, and country of origin;
- You should also explain which terms you combined to form search phrases and your use of Boolean searching (AND, OR, NOT);
- Your use of citation searching (selecting articles from the bibliography of a chosen journal article to further your search).
- Your use of any search models, such as PICO and SPIDER to help shape your approach.
- Search strategy template A simple template for recording your literature searching. This can be included as an appendix to show your search strategy.
The discussion section of an extended literature review is the most flexible in terms of structure. Think of this section as a series of short case studies or ‘windows’ on your research. In this section you will apply the theoretical framework you formed in the literature review – a combination of theories, models and ideas that explain your approach to the topic – to a series of different examples and scenarios. These are usually presented as separate discussion ‘chapters’ in the dissertation, in an order that you feel best fits your argument.
Think about an order for these discussion sections or chapters that helps to tell the story of your research. One common approach is to structure these sections by common themes or concepts that help to draw your sources together. You might also opt for a chronological structure if your dissertation aims to show change or development over time. Another option is to deliberately show where there is a lack of chronology or narrative across your case studies, by ordering them in a fragmentary order! You will be able to reflect upon the structure of these chapters elsewhere in the dissertation, explaining and defending your decision in the methodology and conclusion.
A summary of your key findings – what you have concluded from your research, and how far you have been able to successfully answer your research questions.
- Recommendations – for improvements to your own study, for future research in the area, and for your field more widely.
- Emphasise your contributions to knowledge and what you have achieved.
Depending on your research aims, and whether you are working with a case-study type approach (where each section of the dissertation considers a different example or concept through the lens established in your literature review), you might opt for one of the following structures:
Splitting the literature review across different chapters:
This structure allows you to pull apart the traditional literature review, introducing it little by little with each of your themed chapters. This approach works well for dissertations that attempt to show change or difference over time, as the relevant literature for that section or period can be introduced gradually to the reader.
Whichever structure you opt for, remember to explain and justify your approach. A marker will be interested in why you decided on your chosen structure, what it allows you to achieve/brings to the project and what alternatives you considered and rejected in the planning process. Here are some example sentence starters:
In qualitative studies, your results are often presented alongside the discussion, as it is difficult to include this data in a meaningful way without explanation and interpretation. In the dsicussion section, aim to structure your work thematically, moving through the key concepts or ideas that have emerged from your qualitative data. Use extracts from your data collection - interviews, focus groups, observations - to illustrate where these themes are most prominent, and refer back to the sources from your literature review to help draw conclusions.
Here's an example of how your data could be presented in paragraph format in this section:
Example from 'Reporting and discussing your findings ', Monash University .
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Prize-Winning Thesis and Dissertation Examples
Published on September 9, 2022 by Tegan George . Revised on July 18, 2023.
It can be difficult to know where to start when writing your thesis or dissertation . One way to come up with some ideas or maybe even combat writer’s block is to check out previous work done by other students on a similar thesis or dissertation topic to yours.
This article collects a list of undergraduate, master’s, and PhD theses and dissertations that have won prizes for their high-quality research.
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Award-winning undergraduate theses, award-winning master’s theses, award-winning ph.d. dissertations, other interesting articles.
University : University of Pennsylvania Faculty : History Author : Suchait Kahlon Award : 2021 Hilary Conroy Prize for Best Honors Thesis in World History Title : “Abolition, Africans, and Abstraction: the Influence of the “Noble Savage” on British and French Antislavery Thought, 1787-1807”
University : Columbia University Faculty : History Author : Julien Saint Reiman Award : 2018 Charles A. Beard Senior Thesis Prize Title : “A Starving Man Helping Another Starving Man”: UNRRA, India, and the Genesis of Global Relief, 1943-1947
University: University College London Faculty: Geography Author: Anna Knowles-Smith Award: 2017 Royal Geographical Society Undergraduate Dissertation Prize Title: Refugees and theatre: an exploration of the basis of self-representation
University: University of Washington Faculty: Computer Science & Engineering Author: Nick J. Martindell Award: 2014 Best Senior Thesis Award Title: DCDN: Distributed content delivery for the modern web
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University: University of Edinburgh Faculty: Informatics Author: Christopher Sipola Award: 2018 Social Responsibility & Sustainability Dissertation Prize Title: Summarizing electricity usage with a neural network
University: University of Ottawa Faculty: Education Author: Matthew Brillinger Award: 2017 Commission on Graduate Studies in the Humanities Prize Title: Educational Park Planning in Berkeley, California, 1965-1968
University: University of Ottawa Faculty: Social Sciences Author: Heather Martin Award: 2015 Joseph De Koninck Prize Title: An Analysis of Sexual Assault Support Services for Women who have a Developmental Disability
University : University of Ottawa Faculty : Physics Author : Guillaume Thekkadath Award : 2017 Commission on Graduate Studies in the Sciences Prize Title : Joint measurements of complementary properties of quantum systems
University: London School of Economics Faculty: International Development Author: Lajos Kossuth Award: 2016 Winner of the Prize for Best Overall Performance Title: Shiny Happy People: A study of the effects income relative to a reference group exerts on life satisfaction
University : Stanford University Faculty : English Author : Nathan Wainstein Award : 2021 Alden Prize Title : “Unformed Art: Bad Writing in the Modernist Novel”
University : University of Massachusetts at Amherst Faculty : Molecular and Cellular Biology Author : Nils Pilotte Award : 2021 Byron Prize for Best Ph.D. Dissertation Title : “Improved Molecular Diagnostics for Soil-Transmitted Molecular Diagnostics for Soil-Transmitted Helminths”
University: Utrecht University Faculty: Linguistics Author: Hans Rutger Bosker Award: 2014 AVT/Anéla Dissertation Prize Title: The processing and evaluation of fluency in native and non-native speech
University: California Institute of Technology Faculty: Physics Author: Michael P. Mendenhall Award: 2015 Dissertation Award in Nuclear Physics Title: Measurement of the neutron beta decay asymmetry using ultracold neutrons
University: Stanford University Faculty: Management Science and Engineering Author: Shayan O. Gharan Award: Doctoral Dissertation Award 2013 Title: New Rounding Techniques for the Design and Analysis of Approximation Algorithms
University: University of Minnesota Faculty: Chemical Engineering Author: Eric A. Vandre Award: 2014 Andreas Acrivos Dissertation Award in Fluid Dynamics Title: Onset of Dynamics Wetting Failure: The Mechanics of High-speed Fluid Displacement
University: Erasmus University Rotterdam Faculty: Marketing Author: Ezgi Akpinar Award: McKinsey Marketing Dissertation Award 2014 Title: Consumer Information Sharing: Understanding Psychological Drivers of Social Transmission
University: University of Washington Faculty: Computer Science & Engineering Author: Keith N. Snavely Award: 2009 Doctoral Dissertation Award Title: Scene Reconstruction and Visualization from Internet Photo Collections
University: University of Ottawa Faculty: Social Work Author: Susannah Taylor Award: 2018 Joseph De Koninck Prize Title: Effacing and Obscuring Autonomy: the Effects of Structural Violence on the Transition to Adulthood of Street Involved Youth
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Home >> Blog >> Tips on writing a qualitative dissertation or thesis, from Braun & Clarke – Part 1
Tips on writing a qualitative dissertation or thesis, from Braun & Clarke – Part 1
Our advice here relates to many forms of qualitative research, and particularly to research involving the use of thematic analysis (TA).
Based on our experience of supervising students over two decades, as well as our writing on qualitative methodologies, we discuss what we think constitutes good practice – and note some common problems to avoid.
Our first tip is always to check local requirements ! Check what is required in your university context with regard to the format and presentation of your dissertation/thesis; if our advice clashes with this, discuss it with your supervisor. Sometimes requirements are “rules”, and sometimes they’re more norms and conventions, and there’s room to do things differently.
Qualitative centric research writing
Why might our advice here clash with what your local context expects or requires? The simple answer is that there isn’t a widely agreed on single standard for reporting qualitative research. Broadly speaking, there are two styles of qualitative research reporting – let’s call these “add qualitative research and stir” and “qualitative centric”. The “add qualitative and stir” style reflects the default conventions for reporting quantitative research slightly tweaked for qualitative research. Some characteristics of this style of reporting include:
- third-person/passive voice
- searching out and identifying a “gap” in the literature in the introduction
- methodological critique of existing research;
- and, when it comes to reporting the analysis, separate “results” and “discussion” sections.
This style of reporting is far more widely understood and accepted than the other.
What we advocate for is a “qualitative centric” style of reporting – one that is more in line with the ethos and values of qualitative research. This style departs from quantitative norms of empirical research reporting, and is consequently less widely recognised and understood.
This is why you might experience a clash between what we recommend as good practice and what is required in your local context. We experience this clash of reporting values all the time – we have been required by reviewers and editors on numerous occasions to turn our qualitative centric research papers into something more conventional, and our students have sometimes been required by examiners to turn their qualitative centric theses into something more conventional (e.g., by separating out an integrated “results and discussion” and including methodological critique in the introduction).
We want to be open about the fact that there can be risks in a qualitative centric style of reporting! One of the aims of this blog post, and the Twitter thread on which it is based, is to increase understanding of qualitative centric reporting styles so that fewer qualitative researchers are required to rework their research report into something less reflective of the ethos of qualitative research.
So, what are some of the features of a qualitative centric reporting style? Let’s work through a report section by section.
Think of the opening section of your report not as a literature review but as an introduction – the introduction is highly likely to include discussion of relevant literature, but the goal of the introduction is not to review the literature and find a “gap”. Instead, your goal in this section is to provide a context and rationale for your research.
If you do discuss bodies of literature, try to avoid summarising study after study after study… instead overview and synthesise a body of literature (What questions have been asked? What, if any, assumptions have been made? What are some of the common themes across the literature?). Have the confidence to tell the reader something about the state of the literature from your perspective.
Theoretical consistency in your introduction
If you embrace fully the ethos and values of qualitative research, you don’t just understand qualitative research as providing you with tools and techniques to generate and analyse data; you’re unlikely to be a committed positivist or (simple/pure) realist. So if you’re not a positivist or realist when conducting and reporting your own research, how should you handle reporting research in your introduction that is positivist/realist? We think it’s important to be theoretically consistent across your report!
That means not being a positivist/realist in your introduction when discussing quantitative research, then shifting to being something else when reporting your research. It means you need to think carefully about how you present and frame the findings of quantitative research. As an example, don’t present results from other projects as statements of fact (e.g. by stating “gay men are more likely than straight men to experience poor body image”), but rather as what other research has reported e.g. by saying “several quantitative studies suggest that gay men are more likely than straight men to experience poor body image”. It’s a subtle but important difference. It shows the reader that you understand your theoretical approach, and that it doesn’t (necessarily) align with the philosophical assumptions underpinning the quantitative research.
We would also advise against engaging in methodological critique based on the values and assumptions of quantitative research in an introduction (methodological critique consistent with the philosophical assumptions of your research may be appropriate).
Framing your research: inverted triangles or stacked boxes?
Ideally, your introduction will make an argument for your research and frame it within relevant wider contexts . It will flow beautifully – the reader will always know why they are being told something and where they are being taken next. There will be no jumping around from one to another seemingly unrelated topic.
To help with flow and structure, work out if your introduction is the classic “inverted triangle” (starts broad and gets increasingly more specific) or what we call the “stacking boxes” structure. With the latter, you have several different topics to discuss but they aren’t easily classifiable as broader or more specific, they are all roughly at the same level. Your task is to decide how to order or stack the boxes! This is a judgement call and you will often need to figure out what works best as you write . We regularly advise our students to reorder their stack of boxes; we do the same with our own work. You can’t always know ahead of writing how things will flow.
With a “stacking boxes” introduction, we strongly recommend having some signposting or an overview at the start of the introduction to help the reader understand what you will cover and where things are going. Try to have linking sentences between different topics or sections to signal transitions to the reader (we’ve been here, now we are going there…).
Typically, we’d advise you to end the introduction with your research questions/aims*. Any question (or questions) and aims should make sense to the reader – they definitely should not come as a surprise! – in light of the context you have presented. You want the reader to almost expect and anticipate your research question; you want your research question to make sense .
*Though, in some instances, this might work best at the start, ahead of your box stack! In such cases, you should come back to it at the end or before the start of the methodology. This works within a qualitative-centric introduction because you are not building towards a great “reveal” of the “gap” you have identified.
Make sure you formulate your research question in a way that is consistent with the ethos and values of qualitative research. Don’t frame your research question(s) as hypotheses or, indeed, discuss what you expect to find. A common error is to formulate a research question in terms of the impact or effect of X on Y – which is essentially a poorly-disguised quantitative hypothesis! Our book Successful Qualitative Research provides a detailed discussion of formulating research questions for qualitative research. If you’re using TA, we have recently published a paper Conceptual and Design Thinking for Thematic Analysis t hat includes guidance on appropriate research questions for reflective TA – the approach to TA that we developed and first wrote about in 2006 .
Circling back to the title
Let us circle around to thesis/dissertation titles here too – qualitative research is nothing if not recursive! Double check your title to make sure it isn’t implicitly quantitatively framed either. You really don’t want the reader to read your title and the introduction and be expecting a quantitative study when they get to your research questions! Ideally a good title tells the reader something about the topic, the methodological approach and perhaps also a key message from the analysis. Short, evocative quotations from participants can make great titles. Here’s an example from a project on gay fathers .
Read Part 2 of this blog.
Victoria Clarke and Virginia Braun’s forthcoming book is Thematic Analysis: A Practical Guide . They have websites on thematic analysis and the story completion method . You can find them both on Twitter – @drvicclarke and @ginnybraun – where they tweet regularly about qualitative research.
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About Victoria Clarke
Victoria is an Associate Professor in Qualitative and Critical Psychology at the University of the West of England, Bristol, UK. You can find her on Twitter - @drvicclarke - regularly tweeting about qualitative research.
View all posts by Victoria Clarke
About Virginia Braun
Virginia is a Professor in Psychology at The University of Auckland, Aotearoa New Zealand. You can find her on Twitter - @ginnybraun – (re)tweeting about qualitative research and other issues.
View all posts by Virginia Braun
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Tips for a qualitative dissertation
17 October 2017
Tips for students
This blog is part of a series for Evidence-Based Health Care MSc students undertaking their dissertations.
Undertaking an MSc dissertation in Evidence-Based Health Care (EBHC) may be your first hands-on experience of doing qualitative research. I chatted to Dr. Veronika Williams, an experienced qualitative researcher, and tutor on the EBHC programme, to find out her top tips for producing a high-quality qualitative EBHC thesis.
1) Make the switch from a quantitative to a qualitative mindset
It’s not just about replacing numbers with words. Doing qualitative research requires you to adopt a different way of seeing and interpreting the world around you. Veronika asks her students to reflect on positivist and interpretivist approaches: If you come from a scientific or medical background, positivism is often the unacknowledged status quo. Be open to considering there are alternative ways to generate and understand knowledge.
2) Reflect on your role
Quantitative research strives to produce “clean” data unbiased by the context in which it was generated. With qualitative methods, this is neither possible nor desirable. Students should reflect on how their background and personal views shape the way they collect and analyse their data. This will not only add to the transparency of your work but will also help you interpret your findings.
3) Don’t forget the theory
Qualitative researchers use theories as a lens through which they understand the world around them. Veronika suggests that students consider the theoretical underpinning to their own research at the earliest stages. You can read an article about why theories are useful in qualitative research here.
4) Think about depth rather than breadth
Qualitative research is all about developing a deep and insightful understanding of the phenomenon/ concept you are studying. Be realistic about what you can achieve given the time constraints of an MSc. Veronika suggests that collecting and analysing a smaller dataset well is preferable to producing a superficial, rushed analysis of a larger dataset.
5) Blur the boundaries between data collection, analysis and writing up
Veronika strongly recommends keeping a research diary or using memos to jot down your ideas as your research progresses. Not only do these add to your audit trail, these entries will help contribute to your first draft and the process of moving towards theoretical thinking. Qualitative researchers move back and forward between their dataset and manuscript as their ideas develop. This enriches their understanding and allows emerging theories to be explored.
6) Move beyond the descriptive
When analysing interviews, for example, it can be tempting to think that having coded your transcripts you are nearly there. This is not the case! You need to move beyond the descriptive codes to conceptual themes and theoretical thinking in order to produce a high-quality thesis. Veronika warns against falling into the pitfall of thinking writing up is, “Two interviews said this whilst three interviewees said that”.
7) It’s not just about the average experience
When analysing your data, consider the outliers or negative cases, for example, those that found the intervention unacceptable. Although in the minority, these respondents will often provide more meaningful insight into the phenomenon or concept you are trying to study.
8) Bounce ideas
Veronika recommends sharing your emerging ideas and findings with someone else, maybe with a different background or perspective. This isn’t about getting to the “right answer” rather it offers you the chance to refine your thinking. Be sure, though, to fully acknowledge their contribution in your thesis.
9) Be selective
In can be a challenge to meet the dissertation word limit. It won’t be possible to present all the themes generated by your dataset so focus! Use quotes from across your dataset that best encapsulate the themes you are presenting. Display additional data in the appendix. For example, Veronika suggests illustrating how you moved from your coding framework to your themes.
10) Don’t panic!
There will be a stage during analysis and write up when it seems undoable. Unlike quantitative researchers who begin analysis with a clear plan, qualitative research is more of a journey. Everything will fall into place by the end. Be sure, though, to allow yourself enough time to make sense of the rich data qualitative research generates.
Qualitative research methods.
Managing school behavior: a qualitative case study
Committee member, journal title, journal issn, volume title, research projects, organizational units, journal issue, is version of.
The purposes of this dissertation research were to understand the methods by which building-level school administrators collect office discipline referral data, and to understand the ways they make decisions based on that data. In order to achieve this overall objective, the following research questions framed this study:
1. To what extent do administrators have access to behavior data that inform their decisions on how to improve student success in school and society?
2. To what extent do administrators use behavior data to improve student success in school and in society?
3. What do administrators perceive it would take to enhance the effectiveness of their current efforts to improve students' success in school and society?
One mid-sized suburban school district from the Midwest was selected for this case study research. Eleven school building administrators were interviewed to provide insight into the research questions. Participants in the study self-selected pseudonyms to preserve anonymity. Interviews were conducted face to face, and then transcribed.
The themes that emerged from the interviews include: (1) participants' perceptions of and experiences with collecting and analyzing student behavior data, (2) participants' perceptions of and experiences with using behavior data to improve student success in school and in society, and (3) participants' perceptions of necessary steps to take to enhance the effectiveness of their current efforts to improve students' success in school and society. The findings from this study describe practices used for collecting student attendance data, office referral data, and suspension and expulsion data. Building-level school leaders recognize that data collection and analysis of building- and school district-level conduct and/or behavior data would help them establish patterns of behavior for individual students, as well as students throughout the building. The aim for school administrators should be to use research-based strategies, practices, and programs that have proven successful when they plan interventions and programmatic changes for students.
Based on its findings, this study recommends that further investigation into data collection processes that lead to improved behavioral outcomes for students be conducted. Consistent data collection, supported by a systemic procedure to analyze that data, is paramount to increase the effectiveness of any behavior support program. As schools continue to face challenges associated with providing adequate behavioral supports for students, building capacity with teaching and administrative staff is recommended, so that a continuum of behavioral supports could be provided to meet the diverse behavioral needs of buildings, schools, and districts.
Subject categories, collections.
Qualitative Data Analysis Methods 101:
The “big 6” methods + examples.
By: Kerryn Warren (PhD) | Reviewed By: Eunice Rautenbach (D.Tech) | May 2020 (Updated April 2023)
Qualitative data analysis methods. Wow, that’s a mouthful.
If you’re new to the world of research, qualitative data analysis can look rather intimidating. So much bulky terminology and so many abstract, fluffy concepts. It certainly can be a minefield!
Don’t worry – in this post, we’ll unpack the most popular analysis methods , one at a time, so that you can approach your analysis with confidence and competence – whether that’s for a dissertation, thesis or really any kind of research project.
What (exactly) is qualitative data analysis?
To understand qualitative data analysis, we need to first understand qualitative data – so let’s step back and ask the question, “what exactly is qualitative data?”.
Qualitative data refers to pretty much any data that’s “not numbers” . In other words, it’s not the stuff you measure using a fixed scale or complex equipment, nor do you analyse it using complex statistics or mathematics.
So, if it’s not numbers, what is it?
Words, you guessed? Well… sometimes , yes. Qualitative data can, and often does, take the form of interview transcripts, documents and open-ended survey responses – but it can also involve the interpretation of images and videos. In other words, qualitative isn’t just limited to text-based data.
So, how’s that different from quantitative data, you ask?
Simply put, qualitative research focuses on words, descriptions, concepts or ideas – while quantitative research focuses on numbers and statistics . Qualitative research investigates the “softer side” of things to explore and describe , while quantitative research focuses on the “hard numbers”, to measure differences between variables and the relationships between them. If you’re keen to learn more about the differences between qual and quant, we’ve got a detailed post over here .
So, qualitative analysis is easier than quantitative, right?
Not quite. In many ways, qualitative data can be challenging and time-consuming to analyse and interpret. At the end of your data collection phase (which itself takes a lot of time), you’ll likely have many pages of text-based data or hours upon hours of audio to work through. You might also have subtle nuances of interactions or discussions that have danced around in your mind, or that you scribbled down in messy field notes. All of this needs to work its way into your analysis.
Making sense of all of this is no small task and you shouldn’t underestimate it. Long story short – qualitative analysis can be a lot of work! Of course, quantitative analysis is no piece of cake either, but it’s important to recognise that qualitative analysis still requires a significant investment in terms of time and effort.
Need a helping hand?
In this post, we’ll explore qualitative data analysis by looking at some of the most common analysis methods we encounter. We’re not going to cover every possible qualitative method and we’re not going to go into heavy detail – we’re just going to give you the big picture. That said, we will of course includes links to loads of extra resources so that you can learn more about whichever analysis method interests you.
Without further delay, let’s get into it.
The “Big 6” Qualitative Analysis Methods
There are many different types of qualitative data analysis, all of which serve different purposes and have unique strengths and weaknesses . We’ll start by outlining the analysis methods and then we’ll dive into the details for each.
The 6 most popular methods (or at least the ones we see at Grad Coach) are:
- Content analysis
- Narrative analysis
- Discourse analysis
- Thematic analysis
- Grounded theory (GT)
- Interpretive phenomenological analysis (IPA)
Let’s take a look at each of them…
QDA Method #1: Qualitative Content Analysis
Content analysis is possibly the most common and straightforward QDA method. At the simplest level, content analysis is used to evaluate patterns within a piece of content (for example, words, phrases or images) or across multiple pieces of content or sources of communication. For example, a collection of newspaper articles or political speeches.
With content analysis, you could, for instance, identify the frequency with which an idea is shared or spoken about – like the number of times a Kardashian is mentioned on Twitter. Or you could identify patterns of deeper underlying interpretations – for instance, by identifying phrases or words in tourist pamphlets that highlight India as an ancient country.
Because content analysis can be used in such a wide variety of ways, it’s important to go into your analysis with a very specific question and goal, or you’ll get lost in the fog. With content analysis, you’ll group large amounts of text into codes , summarise these into categories, and possibly even tabulate the data to calculate the frequency of certain concepts or variables. Because of this, content analysis provides a small splash of quantitative thinking within a qualitative method.
Naturally, while content analysis is widely useful, it’s not without its drawbacks . One of the main issues with content analysis is that it can be very time-consuming , as it requires lots of reading and re-reading of the texts. Also, because of its multidimensional focus on both qualitative and quantitative aspects, it is sometimes accused of losing important nuances in communication.
Content analysis also tends to concentrate on a very specific timeline and doesn’t take into account what happened before or after that timeline. This isn’t necessarily a bad thing though – just something to be aware of. So, keep these factors in mind if you’re considering content analysis. Every analysis method has its limitations , so don’t be put off by these – just be aware of them ! If you’re interested in learning more about content analysis, the video below provides a good starting point.
QDA Method #2: Narrative Analysis
As the name suggests, narrative analysis is all about listening to people telling stories and analysing what that means . Since stories serve a functional purpose of helping us make sense of the world, we can gain insights into the ways that people deal with and make sense of reality by analysing their stories and the ways they’re told.
You could, for example, use narrative analysis to explore whether how something is being said is important. For instance, the narrative of a prisoner trying to justify their crime could provide insight into their view of the world and the justice system. Similarly, analysing the ways entrepreneurs talk about the struggles in their careers or cancer patients telling stories of hope could provide powerful insights into their mindsets and perspectives . Simply put, narrative analysis is about paying attention to the stories that people tell – and more importantly, the way they tell them.
Of course, the narrative approach has its weaknesses , too. Sample sizes are generally quite small due to the time-consuming process of capturing narratives. Because of this, along with the multitude of social and lifestyle factors which can influence a subject, narrative analysis can be quite difficult to reproduce in subsequent research. This means that it’s difficult to test the findings of some of this research.
Similarly, researcher bias can have a strong influence on the results here, so you need to be particularly careful about the potential biases you can bring into your analysis when using this method. Nevertheless, narrative analysis is still a very useful qualitative analysis method – just keep these limitations in mind and be careful not to draw broad conclusions . If you’re keen to learn more about narrative analysis, the video below provides a great introduction to this qualitative analysis method.
QDA Method #3: Discourse Analysis
Discourse is simply a fancy word for written or spoken language or debate . So, discourse analysis is all about analysing language within its social context. In other words, analysing language – such as a conversation, a speech, etc – within the culture and society it takes place. For example, you could analyse how a janitor speaks to a CEO, or how politicians speak about terrorism.
To truly understand these conversations or speeches, the culture and history of those involved in the communication are important factors to consider. For example, a janitor might speak more casually with a CEO in a company that emphasises equality among workers. Similarly, a politician might speak more about terrorism if there was a recent terrorist incident in the country.
So, as you can see, by using discourse analysis, you can identify how culture , history or power dynamics (to name a few) have an effect on the way concepts are spoken about. So, if your research aims and objectives involve understanding culture or power dynamics, discourse analysis can be a powerful method.
Because there are many social influences in terms of how we speak to each other, the potential use of discourse analysis is vast . Of course, this also means it’s important to have a very specific research question (or questions) in mind when analysing your data and looking for patterns and themes, or you might land up going down a winding rabbit hole.
Discourse analysis can also be very time-consuming as you need to sample the data to the point of saturation – in other words, until no new information and insights emerge. But this is, of course, part of what makes discourse analysis such a powerful technique. So, keep these factors in mind when considering this QDA method. Again, if you’re keen to learn more, the video below presents a good starting point.
QDA Method #4: Thematic Analysis
Thematic analysis looks at patterns of meaning in a data set – for example, a set of interviews or focus group transcripts. But what exactly does that… mean? Well, a thematic analysis takes bodies of data (which are often quite large) and groups them according to similarities – in other words, themes . These themes help us make sense of the content and derive meaning from it.
Let’s take a look at an example.
With thematic analysis, you could analyse 100 online reviews of a popular sushi restaurant to find out what patrons think about the place. By reviewing the data, you would then identify the themes that crop up repeatedly within the data – for example, “fresh ingredients” or “friendly wait staff”.
So, as you can see, thematic analysis can be pretty useful for finding out about people’s experiences , views, and opinions . Therefore, if your research aims and objectives involve understanding people’s experience or view of something, thematic analysis can be a great choice.
Since thematic analysis is a bit of an exploratory process, it’s not unusual for your research questions to develop , or even change as you progress through the analysis. While this is somewhat natural in exploratory research, it can also be seen as a disadvantage as it means that data needs to be re-reviewed each time a research question is adjusted. In other words, thematic analysis can be quite time-consuming – but for a good reason. So, keep this in mind if you choose to use thematic analysis for your project and budget extra time for unexpected adjustments.
QDA Method #5: Grounded theory (GT)
Grounded theory is a powerful qualitative analysis method where the intention is to create a new theory (or theories) using the data at hand, through a series of “ tests ” and “ revisions ”. Strictly speaking, GT is more a research design type than an analysis method, but we’ve included it here as it’s often referred to as a method.
What’s most important with grounded theory is that you go into the analysis with an open mind and let the data speak for itself – rather than dragging existing hypotheses or theories into your analysis. In other words, your analysis must develop from the ground up (hence the name).
Let’s look at an example of GT in action.
Assume you’re interested in developing a theory about what factors influence students to watch a YouTube video about qualitative analysis. Using Grounded theory , you’d start with this general overarching question about the given population (i.e., graduate students). First, you’d approach a small sample – for example, five graduate students in a department at a university. Ideally, this sample would be reasonably representative of the broader population. You’d interview these students to identify what factors lead them to watch the video.
After analysing the interview data, a general pattern could emerge. For example, you might notice that graduate students are more likely to read a post about qualitative methods if they are just starting on their dissertation journey, or if they have an upcoming test about research methods.
From here, you’ll look for another small sample – for example, five more graduate students in a different department – and see whether this pattern holds true for them. If not, you’ll look for commonalities and adapt your theory accordingly. As this process continues, the theory would develop . As we mentioned earlier, what’s important with grounded theory is that the theory develops from the data – not from some preconceived idea.
So, what are the drawbacks of grounded theory? Well, some argue that there’s a tricky circularity to grounded theory. For it to work, in principle, you should know as little as possible regarding the research question and population, so that you reduce the bias in your interpretation. However, in many circumstances, it’s also thought to be unwise to approach a research question without knowledge of the current literature . In other words, it’s a bit of a “chicken or the egg” situation.
Regardless, grounded theory remains a popular (and powerful) option. Naturally, it’s a very useful method when you’re researching a topic that is completely new or has very little existing research about it, as it allows you to start from scratch and work your way from the ground up .
QDA Method #6: Interpretive Phenomenological Analysis (IPA)
Interpretive. Phenomenological. Analysis. IPA . Try saying that three times fast…
Let’s just stick with IPA, okay?
IPA is designed to help you understand the personal experiences of a subject (for example, a person or group of people) concerning a major life event, an experience or a situation . This event or experience is the “phenomenon” that makes up the “P” in IPA. Such phenomena may range from relatively common events – such as motherhood, or being involved in a car accident – to those which are extremely rare – for example, someone’s personal experience in a refugee camp. So, IPA is a great choice if your research involves analysing people’s personal experiences of something that happened to them.
It’s important to remember that IPA is subject – centred . In other words, it’s focused on the experiencer . This means that, while you’ll likely use a coding system to identify commonalities, it’s important not to lose the depth of experience or meaning by trying to reduce everything to codes. Also, keep in mind that since your sample size will generally be very small with IPA, you often won’t be able to draw broad conclusions about the generalisability of your findings. But that’s okay as long as it aligns with your research aims and objectives.
Another thing to be aware of with IPA is personal bias . While researcher bias can creep into all forms of research, self-awareness is critically important with IPA, as it can have a major impact on the results. For example, a researcher who was a victim of a crime himself could insert his own feelings of frustration and anger into the way he interprets the experience of someone who was kidnapped. So, if you’re going to undertake IPA, you need to be very self-aware or you could muddy the analysis.
How to choose the right analysis method
In light of all of the qualitative analysis methods we’ve covered so far, you’re probably asking yourself the question, “ How do I choose the right one? ”
Much like all the other methodological decisions you’ll need to make, selecting the right qualitative analysis method largely depends on your research aims, objectives and questions . In other words, the best tool for the job depends on what you’re trying to build. For example:
- Perhaps your research aims to analyse the use of words and what they reveal about the intention of the storyteller and the cultural context of the time.
- Perhaps your research aims to develop an understanding of the unique personal experiences of people that have experienced a certain event, or
- Perhaps your research aims to develop insight regarding the influence of a certain culture on its members.
As you can probably see, each of these research aims are distinctly different , and therefore different analysis methods would be suitable for each one. For example, narrative analysis would likely be a good option for the first aim, while grounded theory wouldn’t be as relevant.
It’s also important to remember that each method has its own set of strengths, weaknesses and general limitations. No single analysis method is perfect . So, depending on the nature of your research, it may make sense to adopt more than one method (this is called triangulation ). Keep in mind though that this will of course be quite time-consuming.
As we’ve seen, all of the qualitative analysis methods we’ve discussed make use of coding and theme-generating techniques, but the intent and approach of each analysis method differ quite substantially. So, it’s very important to come into your research with a clear intention before you decide which analysis method (or methods) to use.
Start by reviewing your research aims , objectives and research questions to assess what exactly you’re trying to find out – then select a qualitative analysis method that fits. Never pick a method just because you like it or have experience using it – your analysis method (or methods) must align with your broader research aims and objectives.
Let’s recap on QDA methods…
In this post, we looked at six popular qualitative data analysis methods:
- First, we looked at content analysis , a straightforward method that blends a little bit of quant into a primarily qualitative analysis.
- Then we looked at narrative analysis , which is about analysing how stories are told.
- Next up was discourse analysis – which is about analysing conversations and interactions.
- Then we moved on to thematic analysis – which is about identifying themes and patterns.
- From there, we went south with grounded theory – which is about starting from scratch with a specific question and using the data alone to build a theory in response to that question.
- And finally, we looked at IPA – which is about understanding people’s unique experiences of a phenomenon.
Of course, these aren’t the only options when it comes to qualitative data analysis, but they’re a great starting point if you’re dipping your toes into qualitative research for the first time.
If you’re still feeling a bit confused, consider our private coaching service , where we hold your hand through the research process to help you develop your best work.
Psst… there’s more (for free)
This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project.
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I wonder it so clear for understand and good for me. can I ask additional query?
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This has been very well explained in simple language . It is useful even for a new researcher.
Great to hear that. Good luck with your qualitative data analysis, Pramod!
This is very useful information. And it was very a clear language structured presentation. Thanks a lot.
Thank you so much.
very informative sequential presentation
Precise explanation of method.
Hi, may we use 2 data analysis methods in our qualitative research?
Thanks for your comment. Most commonly, one would use one type of analysis method, but it depends on your research aims and objectives.
You explained it in very simple language, everyone can understand it. Thanks so much.
Thank you very much, this is very helpful. It has been explained in a very simple manner that even a layman understands
Thank nicely explained can I ask is Qualitative content analysis the same as thematic analysis?
Thanks for your comment. No, QCA and thematic are two different types of analysis. This article might help clarify – https://onlinelibrary.wiley.com/doi/10.1111/nhs.12048
This is my first time to come across a well explained data analysis. so helpful.
I have thoroughly enjoyed your explanation of the six qualitative analysis methods. This is very helpful. Thank you!
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i need a citation of your book.
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Hi Derek, What other theories/methods would you recommend when the data is a whole speech?
Keep writing useful artikel.
It is important concept about QDA and also the way to express is easily understandable, so thanks for all.
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Very helpful .Thanks.
Hi there! Very well explained. Simple but very useful style of writing. Please provide the citation of the text. warm regards
The session was very helpful and insightful. Thank you
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Very insightful. Please, which of this approach could be used for a research that one is trying to elicit students’ misconceptions in a particular concept ?
This is Amazing and well explained, thanks
What do we call a research data analysis method that one use to advise or determining the best accounting tool or techniques that should be adopted in a company.
Informative video, explained in a clear and simple way. Kudos
Waoo! I have chosen method wrong for my data analysis. But I can revise my work according to this guide. Thank you so much for this helpful lecture.
This has been very helpful. It gave me a good view of my research objectives and how to choose the best method. Thematic analysis it is.
Very helpful indeed. Thanku so much for the insight.
This was incredibly helpful.
Nicely written especially for novice academic researchers like me! Thank you.
choosing a right method for a paper is always a hard job for a student, this is a useful information, but it would be more useful personally for me, if the author provide me with a little bit more information about the data analysis techniques in type of explanatory research. Can we use qualitative content analysis technique for explanatory research ? or what is the suitable data analysis method for explanatory research in social studies?
that was very helpful for me. because these details are so important to my research. thank you very much
I learnt a lot. Thank you
Relevant and Informative, thanks !
Well-planned and organized, thanks much! 🙂
I have reviewed qualitative data analysis in a simplest way possible. The content will highly be useful for developing my book on qualitative data analysis methods. Cheers!
Clear explanation on qualitative and how about Case study
This was helpful. Thank you
This was really of great assistance, it was just the right information needed. Explanation very clear and follow.
Wow, Thanks for making my life easy
This was helpful thanks .
Very helpful…. clear and written in an easily understandable manner. Thank you.
This was so helpful as it was easy to understand. I’m a new to research thank you so much.
so educative…. but Ijust want to know which method is coding of the qualitative or tallying done?
Thank you for the great content, I have learnt a lot. So helpful
precise and clear presentation with simple language and thank you for that.
very informative content, thank you.
You guys are amazing on YouTube on this platform. Your teachings are great, educative, and informative. kudos!
Brilliant Delivery. You made a complex subject seem so easy. Well done.
Thanks a lot
Is there a video the captures the practical process of coding using automated applications?
Thanks for the comment. We don’t recommend using automated applications for coding, as they are not sufficiently accurate in our experience.
content analysis can be qualitative research?
THANK YOU VERY MUCH.
Thank you very much for such a wonderful content
do you have any material on Data collection
What a powerful explanation of the QDA methods. Thank you.
Great explanation both written and Video. i have been using of it on a day to day working of my thesis project in accounting and finance. Thank you very much for your support.
very helpful, thank you so much
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83 Qualitative Research Questions & Examples
Qualitative research questions help you understand consumer sentiment. They’re strategically designed to show organizations how and why people feel the way they do about a brand, product, or service. It looks beyond the numbers and is one of the most telling types of market research a company can do.
The UK Data Service describes this perfectly, saying, “The value of qualitative research is that it gives a voice to the lived experience .”
Read on to see seven use cases and 83 qualitative research questions, with the added bonus of examples that show how to get similar insights faster with Similarweb Digital Research Intelligence.
What is a qualitative research question?
A qualitative research question explores a topic in-depth, aiming to better understand the subject through interviews, observations, and other non-numerical data. Qualitative research questions are open-ended, helping to uncover a target audience’s opinions, beliefs, and motivations.
How to choose qualitative research questions?
Choosing the right qualitative research questions can be incremental to the success of your research and the findings you uncover. Here’s my six-step process for choosing the best qualitative research questions.
- Start by understanding the purpose of your research. What do you want to learn? What outcome are you hoping to achieve?
- Consider who you are researching. What are their experiences, attitudes, and beliefs? How can you best capture these in your research questions ?
- Keep your questions open-ended . Qualitative research questions should not be too narrow or too broad. Aim to ask specific questions to provide meaningful answers but broad enough to allow for exploration.
- Balance your research questions. You don’t want all of your questions to be the same type. Aim to mix up your questions to get a variety of answers.
- Ensure your research questions are ethical and free from bias. Always have a second (and third) person check for unconscious bias.
- Consider the language you use. Your questions should be written in a way that is clear and easy to understand. Avoid using jargon , acronyms, or overly technical language.
Types of qualitative research questions
For a question to be considered qualitative, it usually needs to be open-ended. However, as I’ll explain, there can sometimes be a slight cross-over between quantitative and qualitative research questions.
These allow for a wide range of responses and can be formatted with multiple-choice answers or a free-text box to collect additional details. The next two types of qualitative questions are considered open questions, but each has its own style and purpose.
- Probing questions are used to delve deeper into a respondent’s thoughts, such as “Can you tell me more about why you feel that way?”
- Comparative questions ask people to compare two or more items, such as “Which product do you prefer and why?” These qualitative questions are highly useful for understanding brand awareness , competitive analysis , and more.
These ask respondents to choose from a predetermined set of responses, such as “On a scale of 1-5, how satisfied are you with the new product?” While they’re traditionally quantitative, adding a free text box that asks for extra comments into why a specific rating was chosen will provide qualitative insights alongside their respective quantitative research question responses.
- Ranking questions get people to rank items in order of preference, such as “Please rank these products in terms of quality.” They’re advantageous in many scenarios, like product development, competitive analysis, and brand awareness.
- Likert scale questions ask people to rate items on a scale, such as “On a scale of 1-5, how satisfied are you with the new product?” Ideal for placement on websites and emails to gather quick, snappy feedback.
Qualitative research question examples
There are many applications of qualitative research and lots of ways you can put your findings to work for the success of your business. Here’s a summary of the most common use cases for qualitative questions and examples to ask.
Qualitative questions for identifying customer needs and motivations
These types of questions help you find out why customers choose products or services and what they are looking for when making a purchase.
- What factors do you consider when deciding to buy a product?
- What would make you choose one product or service over another?
- What are the most important elements of a product that you would buy?
- What features do you look for when purchasing a product?
- What qualities do you look for in a company’s products?
- Do you prefer localized or global brands when making a purchase?
- How do you determine the value of a product?
- What do you think is the most important factor when choosing a product?
- How do you decide if a product or service is worth the money?
- Do you have any specific expectations when purchasing a product?
- Do you prefer to purchase products or services online or in person?
- What kind of customer service do you expect when buying a product?
- How do you decide when it is time to switch to a different product?
- Where do you research products before you decide to buy?
- What do you think is the most important customer value when making a purchase?
Qualitative research questions to enhance customer experience
Use these questions to reveal insights into how customers interact with a company’s products or services and how those experiences can be improved.
- What aspects of our product or service do customers find most valuable?
- How do customers perceive our customer service?
- What factors are most important to customers when purchasing?
- What do customers think of our brand?
- What do customers think of our current marketing efforts?
- How do customers feel about the features and benefits of our product?
- How do customers feel about the price of our product or service?
- How could we improve the customer experience?
- What do customers think of our website or app?
- What do customers think of our customer support?
- What could we do to make our product or service easier to use?
- What do customers think of our competitors?
- What is your preferred way to access our site?
- How do customers feel about our delivery/shipping times?
- What do customers think of our loyalty programs?
Qualitative research question example for customer experience
- 🙋♀️ Question: What is your preferred way to access our site?
- 🤓 Insight sought: How mobile-dominant are consumers? Should you invest more in mobile optimization or mobile marketing?
- 🤯 Challenges with traditional qualitative research methods: While using this type of question is ideal if you have a large database to survey when placed on a site or sent to a limited customer list, it only gives you a point-in-time perspective from a limited group of people.
- 💡 A new approach: You can get better, broader insights quicker with Similarweb Digital Research Intelligence. To fully inform your research, you need to know preferences at the industry or market level.
- ⏰ Time to insight: 30 seconds
- ✅ How it’s done: Similarweb offers multiple ways to answer this question without going through a lengthy qualitative research process.
First, I’m going to do a website market analysis of the banking credit and lending market in the finance sector to get a clearer picture of industry benchmarks.
Here, I can view device preferences across any industry or market instantly. It shows me the device distribution for any country across any period. This clearly answers the question of how mobile dominate my target audience is , with 59.79% opting to access site via a desktop vs. 40.21% via mobile
I then use the trends section to show me the exact split between mobile and web traffic for each key player in my space. Let’s say I’m about to embark on a competitive campaign that targets customers of Chase and Bank of America ; I can see both their audiences are highly desktop dominant compared with others in their space .
Qualitative question examples for developing new products or services
Research questions like this can help you understand customer pain points and give you insights to develop products that meet those needs.
- What is the primary reason you would choose to purchase a product from our company?
- How do you currently use products or services that are similar to ours?
- Is there anything that could be improved with products currently on the market?
- What features would you like to see added to our products?
- How do you prefer to contact a customer service team?
- What do you think sets our company apart from our competitors?
- What other product or service offerings would like to see us offer?
- What type of information would help you make decisions about buying a product?
- What type of advertising methods are most effective in getting your attention?
- What is the biggest deterrent to purchasing products from us?
Qualitative research question example for service development
- 🙋♀️ Question: What type of advertising methods are most effective in getting your attention?
- 🤓 Insight sought: The marketing channels and/or content that performs best with a target audience .
- 🤯 Challenges with traditional qualitative research methods: When using qualitative research surveys to answer questions like this, the sample size is limited, and bias could be at play.
- 💡 A better approach: The most authentic insights come from viewing real actions and results that take place in the digital world. No questions or answers are needed to uncover this intel, and the information you seek is readily available in less than a minute.
- ⏰ Time to insight: 5 minutes
- ✅ How it’s done: There are a few ways to approach this. You can either take an industry-wide perspective or hone in on specific competitors to unpack their individual successes. Here, I’ll quickly show a snapshot with a whole market perspective.
Using the market analysis element of Similarweb Digital Research Intelligence, I select my industry or market, which I’ve kept as banking and credit. A quick click into marketing channels shows me which channels drive the highest traffic in my market. Taking direct traffic out of the equation, for now, I can see that referrals and organic traffic are the two highest-performing channels in this market.
Similarweb allows me to view the specific referral partners and pages across these channels.
Looking closely at referrals in this market, I’ve chosen chase.com and its five closest rivals . I select referrals in the channel traffic element of marketing channels. I see that Capital One is a clear winner, gaining almost 25 million visits due to referral partnerships.
Next, I get to see exactly who is referring traffic to Capital One and the total traffic share for each referrer. I can see the growth as a percentage and how that has changed, along with an engagement score that rates the average engagement level of that audience segment. This is particularly useful when deciding on which new referral partnerships to pursue.
Once I’ve identified the channels and campaigns that yield the best results, I can then use Similarweb to dive into the various ad creatives and content that have the greatest impact.
These ads are just a few of those listed in the creatives section from my competitive website analysis of Capital One. You can filter this list by the specific campaign, publishers, and ad networks to view those that matter to you most. You can also discover video ad creatives in the same place too.
In just five minutes ⏰
- I’ve captured audience loyalty statistics across my market
- Spotted the most competitive players
- Identified the marketing channels my audience is most responsive to
- I know which content and campaigns are driving the highest traffic volume
- I’ve created a target list for new referral partners and have been able to prioritize this based on results and engagement figures from my rivals
- I can see the types of creatives that my target audience is responding to, giving me ideas for ways to generate effective copy for future campaigns
Qualitative questions to determine pricing strategies
Companies need to make sure pricing stays relevant and competitive. Use these questions to determine customer perceptions on pricing and develop pricing strategies to maximize profits and reduce churn.
- How do you feel about our pricing structure?
- How does our pricing compare to other similar products?
- What value do you feel you get from our pricing?
- How could we make our pricing more attractive?
- What would be an ideal price for our product?
- Which features of our product that you would like to see priced differently?
- What discounts or deals would you like to see us offer?
- How do you feel about the amount you have to pay for our product?
Get Faster Answers to Qualitative Research Questions with Similarweb Today
Qualitative research question example for determining pricing strategies.
- 🙋♀️ Question: What discounts or deals would you like to see us offer?
- 🤓 Insight sought: The promotions or campaigns that resonate with your target audience.
- 🤯 Challenges with traditional qualitative research methods: Consumers don’t always recall the types of ads or campaigns they respond to. Over time, their needs and habits change. Your sample size is limited to those you ask, leaving a huge pool of unknowns at play.
- 💡 A better approach: While qualitative insights are good to know, you get the most accurate picture of the highest-performing promotion and campaigns by looking at data collected directly from the web. These analytics are real-world, real-time, and based on the collective actions of many, instead of the limited survey group you approach. By getting a complete picture across an entire market, your decisions are better informed and more aligned with current market trends and behaviors.
- ✅ How it’s done: Similarweb’s Popular Pages feature shows the content, products, campaigns, and pages with the highest growth for any website. So, if you’re trying to unpack the successes of others in your space and find out what content resonates with a target audience, there’s a far quicker way to get answers to these questions with Similarweb.
Here, I’m using Capital One as an example site. I can see trending pages on their site showing the largest increase in page views. Other filters include campaign, best-performing, and new–each of which shows you page URLs, share of traffic , and growth as a percentage. This page is particularly useful for staying on top of trending topics , campaigns, and new content being pushed out in a market by key competitors.
Qualitative research questions for product development teams
It’s vital to stay in touch with changing consumer needs. These questions can also be used for new product or service development, but this time, it’s from the perspective of a product manager or development team.
- What are customers’ primary needs and wants for this product?
- What do customers think of our current product offerings?
- What is the most important feature or benefit of our product?
- How can we improve our product to meet customers’ needs better?
- What do customers like or dislike about our competitors’ products?
- What do customers look for when deciding between our product and a competitor’s?
- How have customer needs and wants for this product changed over time?
- What motivates customers to purchase this product?
- What is the most important thing customers want from this product?
- What features or benefits are most important when selecting a product?
- What do customers perceive to be our product’s pros and cons?
- What would make customers switch from a competitor’s product to ours?
- How do customers perceive our product in comparison to similar products?
- What do customers think of our pricing and value proposition?
- What do customers think of our product’s design, usability, and aesthetics?
Qualitative questions examples to understand customer segments
Market segmentation seeks to create groups of consumers with shared characteristics. Use these questions to learn more about different customer segments and how to target them with tailored messaging.
- What motivates customers to make a purchase?
- How do customers perceive our brand in comparison to our competitors?
- How do customers feel about our product quality?
- How do customers define quality in our products?
- What factors influence customers’ purchasing decisions ?
- What are the most important aspects of customer service?
- What do customers think of our customer service?
- What do customers think of our pricing?
- How do customers rate our product offerings?
- How do customers prefer to make purchases (online, in-store, etc.)?
Qualitative research question example for understanding customer segments
- 🙋♀️ Question: Which social media channels are you most active on?
- 🤓 Insight sought: Formulate a social media strategy . Specifically, the social media channels most likely to succeed with a target audience.
- 🤯 Challenges with traditional qualitative research methods: Qualitative research question responses are limited to those you ask, giving you a limited sample size. Questions like this are usually at risk of some bias, and this may not be reflective of real-world actions.
- 💡 A better approach: Get a complete picture of social media preferences for an entire market or specific audience belonging to rival firms. Insights are available in real-time, and are based on the actions of many, not a select group of participants. Data is readily available, easy to understand, and expandable at a moment’s notice.
- ✅ How it’s done: Using Similarweb’s website analysis feature, you can get a clear breakdown of social media stats for your audience using the marketing channels element. It shows the percentage of visits from each channel to your site, respective growth, and specific referral pages by each platform. All data is expandable, meaning you can select any platform, period, and region to drill down and get more accurate intel, instantly.
This example shows me Bank of America’s social media distribution, with YouTube , Linkedin , and Facebook taking the top three spots, and accounting for almost 80% of traffic being driven from social media.
When doing any type of market research, it’s important to benchmark performance against industry averages and perform a social media competitive analysis to verify rival performance across the same channels.
Qualitative questions to inform competitive analysis
Organizations must assess market sentiment toward other players to compete and beat rival firms. Whether you want to increase market share , challenge industry leaders , or reduce churn, understanding how people view you vs. the competition is key.
- What is the overall perception of our competitors’ product offerings in the market?
- What attributes do our competitors prioritize in their customer experience?
- What strategies do our competitors use to differentiate their products from ours?
- How do our competitors position their products in relation to ours?
- How do our competitors’ pricing models compare to ours?
- What do consumers think of our competitors’ product quality?
- What do consumers think of our competitors’ customer service?
- What are the key drivers of purchase decisions in our market?
- What is the impact of our competitors’ marketing campaigns on our market share ? 10. How do our competitors leverage social media to promote their products?
Qualitative research question example for competitive analysis
- 🙋♀️ Question: What other companies do you shop with for x?
- 🤓 Insight sought: W ho are your competitors? Which of your rival’s sites do your customers visit? How loyal are consumers in your market?
- 🤯 Challenges with traditional qualitative research methods: Sample size is limited, and customers could be unwilling to reveal which competitors they shop with, or how often they around. Where finances are involved, people can act with reluctance or bias, and be unwilling to reveal other suppliers they do business with.
- 💡 A better approach: Get a complete picture of your audience’s loyalty, see who else they shop with, and how many other sites they visit in your competitive group. Find out the size of the untapped opportunity and which players are doing a better job at attracting unique visitors – without having to ask people to reveal their preferences.
- ✅ How it’s done: Similarweb website analysis shows you the competitive sites your audience visits, giving you access to data that shows cross-visitation habits, audience loyalty, and untapped potential in a matter of minutes.
Using the audience interests element of Similarweb website analysis, you can view the cross-browsing behaviors of a website’s audience instantly. You can see a matrix that shows the percentage of visitors on a target site and any rival site they may have visited.
With the Similarweb audience overlap feature, view the cross-visitation habits of an audience across specific websites. In this example, I chose chase.com and its four closest competitors to review. For each intersection, you see the number of unique visitors and the overall proportion of each site’s audience it represents. It also shows the volume of unreached potential visitors.
Here, you can see a direct comparison of the audience loyalty represented in a bar graph. It shows a breakdown of each site’s audience based on how many other sites they have visited. Those sites with the highest loyalty show fewer additional sites visited.
From the perspective of chase.com, I can see 47% of their visitors do not visit rival sites. 33% of their audience visited 1 or more sites in this group, 14% visited 2 or more sites, 4% visited 3 or more sites, and just 0.8% viewed all sites in this comparison.
How to answer qualitative research questions with Similarweb
Similarweb Digital Research Intelligence drastically improves market research efficiency and time to insight. Both of these can impact the bottom line and the pace at which organizations can adapt and flex when markets shift, and rivals change tactics.
Outdated practices, while still useful, take time . And with a quicker, more efficient way to garner similar insights, opting for the fast lane puts you at a competitive advantage.
With a birds-eye view of the actions and behaviors of companies and consumers across a market , you can answer certain research questions without the need to plan, do, and review extensive qualitative market research .
Qualitative research methods have been around for centuries. From designing the questions to finding the best distribution channels, collecting and analyzing findings takes time to get the insights you need. Similarweb Digital Research Intelligence drastically improves efficiency and time to insight. Both of which impact the bottom line and the pace at which organizations can adapt and flex when markets shift.
Similarweb’s suite of digital intelligence solutions offers unbiased, accurate, honest insights you can trust for analyzing any industry, market, or audience.
- Methodologies used for data collection are robust, transparent, and trustworthy.
- Clear presentation of data via an easy-to-use, intuitive platform.
- It updates dynamically–giving you the freshest data about an industry or market.
- Data is available via an API – so you can plug into platforms like Tableau or PowerBI to streamline your analyses.
- Filter and refine results according to your needs.
Are quantitative or qualitative research questions best?
Both have their place and purpose in market research. Qualitative research questions seek to provide details, whereas quantitative market research gives you numerical statistics that are easier and quicker to analyze. You get more flexibility with qualitative questions, and they’re non-directional.
What are the advantages of qualitative research?
Qualitative research is advantageous because it allows researchers to better understand their subject matter by exploring people’s attitudes, behaviors, and motivations in a particular context. It also allows researchers to uncover new insights that may not have been discovered with quantitative research methods.
What are some of the challenges of qualitative research?
Qualitative research can be time-consuming and costly, typically involving in-depth interviews and focus groups. Additionally, there are challenges associated with the reliability and validity of the collected data, as there is no universal standard for interpreting the results.
How to Conduct a Social Media Competitor Analysis: 5 Quick Steps
Industry Research: The Data-Backed Approach
How to Do a Competitive Analysis: A Complete Guide
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