word of mouth marketing research paper

Word-of-mouth in business-to-business marketing: a systematic review and future research directions

Journal of Business & Industrial Marketing

ISSN : 0885-8624

Article publication date: 10 January 2023

Issue publication date: 18 December 2023

The purpose of this study is to review and analyze the status of word-of-mouth (WOM) research in the business-to-business (B2B) context and discuss and identify new possible future directions.

Design/methodology/approach

A systematic review was conducted and 36 articles on B2B WOM were collected to evaluate the current state of the literature and clarify possible future research directions.

This thematic analysis categorize these articles into three themes: WOM generation, WOM usage and reference marketing. Under each theme, the authors reveal research findings unique to B2B research and different from business-to-consumer (B2C) WOM research. This study identifies several research questions that should be addressed by future research.

Originality/value

Both academic researchers and business practitioners recognize that WOM plays an essential role in B2B marketing. However, no review paper focuses on WOM in the B2B context. Findings in the B2C WOM literature suggest that WOM substantially influences firms’ performance, but that managers cannot simply attempt to extrapolate B2C findings to the B2B arena. By synthesizing and assessing prior research on WOM in the B2B context, this study contributes to a better understanding of the B2B WOM phenomenon and facilitates future research on this topic.

• Business-to-business marketing
• Recommendation
• Systematic review
• Word-of-mouth

Ishii, R. and Kikumori, M. (2023), "Word-of-mouth in business-to-business marketing: a systematic review and future research directions", Journal of Business & Industrial Marketing , Vol. 38 No. 13, pp. 45-62. https://doi.org/10.1108/JBIM-02-2022-0099

Emerald Publishing Limited

Copyright © 2022, Ryuta Ishii and Mai Kikumori.

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode .

1. Introduction

In the field of business-to-consumer (B2C) marketing, it is widely accepted that word-of-mouth (WOM) has a meaningful influence on consumers’ buying decisions. Whether face-to-face or electronic, WOM has a more substantial impact on sales than other elements of the marketing mix, such as advertising and personal selling ( Kim and Hanssens, 2017 ; You et al. , 2015 ). The volume of consumer reviews on a particular product improves product awareness and drives consumers to purchase it ( Babić Rosario et al. , 2016 ; Chevalier and Mayzlin, 2006 ; Zhu and Zhang, 2010 ). Both positive and negative WOM can improve product evaluations and purchase intentions ( Allard et al. , 2020 ; Berger et al. , 2010 ). Furthermore, from a long-term perspective, consumers acquired through WOM bring about twice as much value to a company as other consumers ( Villanueva et al. , 2008 ).

WOM has a considerable influence on purchasing decisions, not only in B2C but in business-to-business (B2B) marketing as well ( Money, 2004 ). For example, purchasing managers in buying firms often obtain WOM information from their internal coworkers (e.g. salespersons and other purchasing managers) or external partners (e.g. exchange partners and business friends) when searching for a new supplier or evaluating a novel industrial product ( Money et al. , 1998 ; Tóth et al. , 2020 ). B2B buyers have begun forming online communities and use electronic WOM from other buyers in the community ( Steward et al. , 2018 ). Given that WOM plays a vital role in the purchasing decisions of buyer firms, seller firms proactively use it to promote their products and services. For example, they ask their existing customers to recommend their products to potential customers ( Hada et al. , 2013 ; Hada et al. , 2014 ) and post customer reviews of their products on their websites as case studies ( Jaakkola and Aarikka-Stenroos, 2019 ; Jalkala and Salminen, 2009 ). This practice, referred to as reference marketing or referral marketing, is widely used in business markets.

Therefore, the topic of WOM has attracted the attention of marketing managers and academic researchers because of its key influence on both B2C and B2B marketing. Indeed, to date, many reviews have been published on WOM ( Babić Rosario et al. , 2020 ; Berger, 2014 ; de Matos and Vargas Rossi, 2008 ; Donthu et al. , 2021 ; King et al. , 2014 ). However, all these reviews focus on WOM in the B2C context and not in the B2B context. Findings in the B2C WOM literature suggest that WOM substantially influences firms’ performance, but that managers cannot simply attempt to extrapolate B2C findings to the B2B arena. Thus, it is essential to synthesize research findings and identify future research directions on the role of WOM in B2B marketing.

Therefore, the purpose of our study is to review and analyze the status of WOM research in the B2B context, synthesize research findings to date and identify possible future directions using a systematic review method. This method differs from a traditional narrative review in that it removes the subjective bias of the researcher. It ensures exhaustive and comprehensive literature searches through a replicable, scientific and transparent process.

The rest of the paper is structured as follows. We first define and clarify the concept of WOM along with relevant concepts, such as referrals, recommendations and references in the Section 2. Next, we describe the systematic review method and the data collection procedure in the Section 3. Subsequently, we conduct descriptive and thematic analyses of the reviewed articles in the Sections 4 and 5. Finally, we present managerial implications, discuss our analysis, and show possible directions for future research in the Sections 6 and 7.

2. Word-of-mouth in the business-to-business context

WOM is defined as:

An oral or written communication process between a sender and an individual or group of receivers, regardless of whether they share the same social network, with the purpose of sharing and acquiring information on an informal basis ( Barreto, 2014 , p. 647).

Marketing scholars have used various terms to refer to the WOM phenomenon in the B2B context, such as WOM ( Faroughian et al. , 2012 ; Kim, 2014 ), referral ( Hartmann and de Grahl, 2011 ; Wallenburg, 2009 ) and recommendation ( Olaru et al. , 2008 ). Several authors have even used a combination of these terms, such as WOM referrals ( Money et al. , 1998 ; Roth et al. , 2004 ) and WOM recommendation ( Chenet et al. , 2010 ). However, these terms are often used interchangeably in the B2B WOM literature ( Aarikka-Stenroos and Sakari Makkonen, 2014 ; Tóth et al. , 2020 ). Thus, we only use the term “WOM” here. However, we need to draw a clear line between the terms WOM and reference. As discussed earlier, in B2B marketing, selling firms often use customers’ WOM as a marketing and sales tool. Such seller-initiated active utilization of customers’ WOM is referred to as reference marketing. Although reference marketing is included in the WOM phenomenon, B2B marketing scholars distinguish between “WOM,” which is informal communication among customers wherein the seller does not intervene, and “reference,” which is communication using WOM in which the seller intervenes.

Based on the above discussion, the WOM phenomenon in B2B marketing can be classified into two categories: “pure WOM” and “reference marketing.” As shown in Figure 1 , “pure WOM” is the process where a sender (e.g. an existing buyer or a salesperson) sends WOM to a receiver (e.g. a potential customer or an internal colleague). Suppliers do not directly intervene in this process, but they can be indirectly involved by incentivizing a sender to generate WOM about themselves or their offerings. “Reference marketing” is the process where a supplier uses WOM from a sender (i.e. reference customer) to provide information to a receiver (e.g. a potential customer). Suppliers can intervene in this process by choosing the sender as a reference customer.

WOM sender;

WOM receiver; and

A WOM sender (e.g. an existing buyer or reference customer) sends positive or negative WOM to internal colleagues or external buyers or provides experiential information related to suppliers. A WOM receiver (i.e. a potential customer) receives and processes WOM information from the senders and uses it for purchase-related decision-making. A supplier encourages existing customers to send WOM to prospective customers or to use WOM information from reference customers as a marketing tool. In the next section, we conduct a systematic review while considering these terminologies and classifications.

3. Methodology

We adopted the systematic review method to analyze the status quo of B2B WOM research. The advantages of this method are described in recent studies published in the Journal of Business & Industrial Marketing ( Chawla et al. , 2020 ; Minerbo and Brito, 2021 ; Yaghtin et al. , 2021 ) and others ( Hulland and Houston, 2020 ; Transfield et al. , 2003 ). We searched and reviewed articles based on the procedure established by Transfield et al. (2003) . First, we developed a review protocol, which included a review question, the focus of this research and the data collection strategy for relevant articles. We searched, collected and assessed the quality and relevance of the identified articles based on this protocol. We then conducted both descriptive and thematic analyses to reveal specific and detailed information on reviewed articles and summarized the key findings of the literature. Finally, we synthesized the findings into an integrated conceptual framework to investigate the WOM phenomenon in the B2B context and identified possible directions for future research. In this section, we describe the process of data collection and synthesis.

3.1 Review question

A systematic review is driven by a review question from which search strings for scientific database searches are defined, criteria for inclusion or exclusion are specified, and an overall process for collecting relevant literature is established. As stated earlier, we aim to synthesize research findings and identify future research directions on the role of WOM in B2B marketing. Therefore, we set two review questions: (1) “What do we know about WOM in B2B marketing?” and (2) “What do we not know about WOM in B2B marketing?”

3.2 Database and search terms

EBSCO Business Source Complete;

Science Direct; and

These databases have a worldwide reputation as reliable platforms; cover most of the published articles on business and marketing; and allow us to search for articles using the title, abstract and keywords.

Given that the review questions are about the findings and research gaps in B2B WOM, it is necessary to choose articles focusing on the context of business markets or B2B marketing. Therefore, we set two groups of keywords: the first group focused on WOM, including four keywords: “WOM,” “referral,” “customer reference” and “customer review”; and the second group was about B2B, also including four keywords: “business-to-business,” “industrial markets,” “industrial marketing” and “supplier.” We used the three databases to search for published articles containing WOM-related keywords in the first group and B2B-related keywords in the second group, either in the title, abstract or keywords. We conducted our initial search in January 2021 with no publication time limit. As shown in Figure 2 , 141 articles were obtained as the set of initial samples: 71 from EBSCO Business Source Complete, 32 from Science Direct and 38 from Emerald. After removing duplicate articles, 111 articles remained.

3.3 Inclusion and exclusion criteria

To ensure an unbiased selection of literature for our review, we established clear inclusion and exclusion criteria. We focused on peer-reviewed, full-text accessible, original research articles published in English. Therefore, non-peer-reviewed business articles and editorials were excluded. We included journals from two widely recognized international journal lists: the Academic Journal Guide (Chartered Association of Business Schools) and the Journal Quality List (Australian Business Deans Council). We included articles that address the WOM phenomenon as the explained object (e.g. studies that treat WOM as the dependent variable in quantitative studies) and articles that use WOM to explain a specific phenomenon (e.g. quantitative studies that have WOM as an independent variable in quantitative studies). We excluded articles that focused on the B2C context rather than B2B. We decided to include articles that considered WOM in both B2B and B2C contexts (e.g. comparing WOM effects in B2B and B2C contexts). We also decided to exclude articles that discussed WOM in general, since, at least in the academic field, WOM refers to B2C WOM, not B2B WOM. A key term associated with WOM is social media. Although communication among customers on social media can be viewed as a WOM phenomenon, the use of social media by firms is difficult to capture as a WOM phenomenon. Hence, studies focusing on WOM in social media were included in the review, whereas studies on social media usage were excluded.

3.4 Selection of relevant articles

Two researchers reviewed 111 literature summaries. Based on the inclusion and exclusion criteria, they screened the articles relevant to our review questions. However, for several references, it was difficult to determine whether to include them in our review based solely on reading the abstracts. In those cases, we manually read the full text to obtain the information needed to decide. Disagreements between the two researchers were resolved through consultation.

Most of the 111 references focused on WOM in a B2C context and the use of social media by B2B firms. Based on the inclusion/exclusion criteria, these references were excluded. Similarly, applying that criterion, editorial and economic articles were also excluded. Among the 111 articles, many focused on WOM in the B2C context and social media in the B2B context. Because the latter studies focused on the usage, design and management of social media by B2B companies, they were also removed, and 33 articles were extracted. Finally, by examining the citations of these 33 articles, 3 additional important articles were identified. Occasionally, review articles that focused on WOM in general were also cited; however, we did not add them as key references because the review articles implicitly focused on the B2C context (e.g. individual consumer reviews, informal communication among consumers). Consequently, there were 36 studies in total.

3.5 Extraction, analysis and synthesis

After determining the literature to be included in the review, the last step in the data collection process was to create a data extraction form. To extract the data, we used a Microsoft Excel spreadsheet. This sheet contained the following information for the collected literature: title, authors, publication journal, year of publication, article type, sample size, industry context, country, major research findings, type of WOM, etc. To reduce subjective bias as much as possible, each author reviewed all 36 references and completed the required fields in the spreadsheet. When disagreements arose among the authors regarding coding and classification, decisions were made through discussion. The final spreadsheet was helpful in conducting the descriptive and thematic analysis that followed.

4. Descriptive analysis

Literature on WOM in B2B marketing emerged in the 1970s, when academic scholars paid great attention to industrial buying behaviors and investigated the difference between B2B and B2C marketing strategies ( Sheth, 1973 ; Webster and Wind, 1972 ). The pioneering works of Martilla (1971) and Webster (1970) revealed that WOM is generated either by internal colleagues (i.e. intrafirm WOM) or external firms (i.e. interfirm WOM) and is an essential factor that influences business organizations’ decision-making processes. For almost three decades after these works, very little research focused on WOM in B2B marketing. Since the 2000s, however, more than 30 WOM-related articles have been published. Specifically, 2 articles (5.6%) were published between 2001 and 2005, 9 (25%) between 2006 and 2010, 11 (30.6%) between 2011 and 2015 and 11 (30.6%) between 2016 and 2020. There were at least three causes of the widespread recognition among researchers and the gradual increase in the number of WOM-related articles. First, online review websites have increased in B2B marketing, and WOM communication among buyers has influenced purchasing decisions. Second, in the context of B2B marketing, the use of social networking services has become commonplace, and communication about products and services has become active in buyer communities and professional networks. Third, the spread of the internet has increased the need for companies to establish their own websites and to post customer feedback as a form of testimonials on those websites.

As shown in Table 1 , the 36 articles included in this review were published in 15 separate journals. Of the 15 journals, 11 were rated three and above in the Academic Journal Guide (AJG; Chartered Association of Business School, 2021 ). According to the ABDC Journal Quality List (JQL), eight were A* journals, five were A and two were B ( Australian Business Deans Council, 2019 ). In the Scimago Journal Rank indicator, most journals (80%) belonged to the Q1 category. These results indicate that the articles included in this review are of good quality and that the editors and reviewers of top-level journals are paying attention to this topic. Regarding the number of articles, approximately half the articles (44%) were published in the two leading journals specializing in B2B marketing: Industrial Marketing Management (31%, n = 11) and Journal of Business & Industrial Marketing (14%, n = 5). This suggests that B2B marketing scholars have contributed considerably to our understanding of the WOM phenomenon in the B2B context. Other journals that feature in our study and are of international repute include Journal of Marketing (6%, n = 2), Journal of Marketing Research (6%, n = 2), European Journal of Marketing (8%, n = 3), Journal of Supply Chain Management (8%, n = 3) and Journal of Services Marketing (6%, n = 2). Other articles were also published in internationally recognized journals in the field of marketing and business, such as the Journal of the Academy of Marketing Science and Journal of Business Research . Most of these journals are general journals on marketing and business. The appearance of articles on B2B WOM in such journals suggests that various marketing researchers are interested in this topic.

Figure 3 shows the trend over time and current proportion of each methodology used by the selected articles. According to the present proportion of methodologies used, of the 36 articles, most were empirical studies (94%, n = 34), with the most common method being quantitative analyses with data collection by mail or an online survey (47%, n = 17). This trend is similar to that of other topics in B2B marketing. The qualitative interview method (25%, n = 9) was also often used by the selected articles. Compared to quantitative methods, qualitative methods are used in the early stages of a particular research field because they are better at examining new and complex phenomena in an exploratory manner ( Granot et al. , 2012 ; Woodside and Wilson, 2003 ). Indeed, several articles in our review stated that they use qualitative methods because there are few studies on B2B WOM, and there is an insufficient description of the phenomenon and elaboration of the concepts ( Jaakkola and Aarikka-Stenroos, 2019 ; Jalkala and Salminen, 2010 ). Therefore, a relatively large proportion of qualitative studies in the selected articles suggests that the study on B2B WOM is in its early stages.

No literature reviews (e.g. systematic reviews or meta-analyses) were found. Notably, the time-series trends indicate a gradual increase in the number of experimental methods in recent years. This is because B2B marketing is beginning to pay more attention to experimental methods: the use of experimental stimuli in a B2B context is difficult because the purchase of B2B products/services involves multiple persons, and the buying process is a long one. Hence, experimental methods tend to be shunned in B2B marketing research. However, the experimental method is a valuable gold standard for analyzing causal relationships ( Hada, 2021 ). In fact, experimentation is used extensively in B2C WOM research.

Figure 4 shows the loci of the empirical studies analyzed in this review. Of the 34 empirical studies, 25 explicitly indicated the country where data were collected. The two major regions were Europe (32%, n = 8, three studies in the UK, two in Germany, two in a particular European country, and one in Finland) and the USA (28%, n = 7). Four studies were conducted in China and one each in Australia, Canada and India. Moreover, three studies collected data from multiple countries (i.e. USA and Japan) to compare the organizational buying behaviors. Overall, most extant literature has focused on organizational behaviors of developed Western countries. Such overall trends indicate that researchers in the USA and Western Europe are the main contributors to research on B2B WOM. Additionally, we should be cautious about applying such research findings to WOM behaviors in other regions such as Asia and Africa.

Table 2 shows the industries that the empirical studies in this review considered as the research context. Overall, most studies focused on B2B services, which, unlike tangible industrial products, are characterized by their intangible and variable nature, making it difficult to assess their quality before buying or experiencing them. Therefore, WOM information plays a crucial role in the evaluation and purchase of B2B services. Previous studies ( Faroughian et al. , 2012 ; Hada et al. , 2014 ; Jalkala and Salminen, 2009 ; Money, 2004 ) have often focused on three services: “IT and software procurement,” “logistics and transportation” and “financial service.” In the information technology (IT) and logistics service industries, it has been found that sellers and buyers actively use WOM, the latter in making purchasing decisions. Several studies have focused on reference marketing in the context of IT procurement or logistics services. This suggests that in the IT and logistics industries, selling firms actively use WOM information as a marketing tool, whereas buying firms rely on it to make purchasing decisions. Further, start-up companies often face purchasing decisions regarding logistics and financial services ( Money et al. , 1998 ; Roth et al. , 2004 ). Other services that frequently appear in empirical studies are telephone and food services, which were investigated in two studies. Other services include printing, advertising and packaging. Some studies have focused on the transactions of tangible industrial goods rather than services. Specifically, they have examined the role of WOM in the purchasing decisions of pharmaceuticals, electronic machinery and processing equipment.

5. Thematic analysis

WOM generation;

WOM usage; and

reference marketing.

Table 3 presents an overview of research findings from the reviewed articles. This section offers the contributions and discusses the main research findings for each theme.

5.1 Theme I: word-of-mouth generation

The first theme is WOM generation and focuses on the sender or source of WOM; 16 (44%) of the 36 studies in this review come under this theme, where the research question is, “Why do customer firms send positive or negative WOM messages?” These studies investigate the antecedents of WOM communication. This theme has two characteristics: first, prior research on this theme has often treated positive WOM messages, such as recommendations and referrals, as positive outcome indicators, along with repurchase intention, satisfaction, loyalty and relationship continuity. By stating that “a widely studied outcome variable within the relationship marketing literature is word-of-mouth,” Brock and Yu Zhou (2012 , p. 372) emphasized the importance of WOM as a performance indicator in B2B research. Second, 13 (81%) of the 16 studies used a quantitative survey as the empirical method. Most of these survey studies focused on B2B services, such as logistics, IT, and finance. This suggests that B2B service marketers emphasize WOM generation.

Prior research on B2C marketing identifies satisfaction, loyalty, quality, perceived value and trust as essential antecedents of WOM generation ( de Matos and Vargas Rossi, 2008 ). WOM studies in B2B marketing extend these research findings of B2C WOM by identifying moderating variables specific to B2B marketing. Olaru et al. (2008) showed that the effect of service value on positive WOM generation is moderated by organization type (government versus private firm) and contract length (long versus short). Anaza and Rutherford (2014) considered both individual and organizational levels of the interorganizational relationship between seller and buyer. They found that positive WOM is created by loyalty to individual salespersons and satisfaction with seller firms.

Studies under this theme have identified the antecedents of WOM generation, such as firm strategy, organizational capabilities, strategic orientation and interfirm relationships, which have not been assessed in WOM research in the B2C context. Hartmann and de Grahl (2011) focused on the concept of organizational flexibility and indicated that logistics service providers can promote customer referrals by responding flexibly to customers’ needs and changes in the environment. Mo et al. (2020) found that an increase of out-of-the-channel-loop perception, which means a channel member’s perception of exclusion from a supplier’s distribution channel networks, decreases positive WOM generation.

Prior research has also investigated the generation of negative WOM messages when B2B service failure occurs. Wang and Huff (2007) identified the conditions under which buyers generate negative WOM when a seller violates the buyer’s trust by failing to meet the buyer’s confident expectations. Specifically, they showed that buyers in the early stages of trust development and/or those who perceive a high likelihood of repeated violation respond negatively and sensitively to a violation of trust.

Overall, prior studies have shown that firm characteristics and interfirm factors generate WOM or moderate the effects of WOM. However, there has been no attempt to examine who generates WOM within a firm or what happens to buyer firms and purchasing managers as a result of WOM generation. These are research questions to be addressed in the future, and we discuss them in detail in the next section.

5.2 Theme II: word-of-mouth usage

Research under the theme of WOM usage has addressed the following questions: What types of WOM messages do customer firms use? Why do customer firms use WOM messages as a source of information for purchase decision-making? What are the consequences of WOM usage? These questions are rarely addressed in B2C WOM research and are specific to the field of B2B marketing.

As shown in Table 4 , WOM information used by customer firms is classified into four types based on the sender–receiver relationship (within-firm versus between-firm) and communication mode (face-to-face versus internet). The first type is the intrafirm offline WOM . Martilla (1971) conducted exploratory interviews with 66 managers in the paper industry and found that there are opinion leaders in each company who have a considerable influence on the purchasing decisions for industrial products through WOM communication within the company. The second type is the intrafirm online WOM . Steward et al. (2018) showed that sellers’ scorecards (performance appraisal systems) available on company intranets can be regarded as WOM information within a company and that they influence purchasing decisions in B2B markets. The third is interfirm offline WOM , which has been the focus of many studies. Money et al. (1998) and Roth et al. (2004) found that start-up firms often refer to WOM information from relatives, friends, and business acquaintances when they make purchase decisions for B2B services such as logistics, advertising and finance. Hada et al. (2014) also focused on the face-to-face WOM prompted by suppliers (i.e. face-to-face reference) in B2B markets and showed that B2B marketers often use such reference information from other companies in the purchase process. Fourth is interfirm online WOM . According to Steward et al. (2018) , professional B2B buyers have formed online communities in recent years and refer to other buyers’ reviews of B2B products and services. Many studies in this review examine online reference marketing, where sellers post buyers’ WOM reviews on their own website and use it as a marketing tool ( Jalkala and Salminen, 2009 ; Terho and Jalkala, 2017 ). They show that online WOM from other companies (i.e. interfirm online WOM) is often used in B2B marketing.

Previous studies also address the research questions: Why do customer firms use WOM messages as sources of information for purchase decision-making? What are the consequences of WOM usage? These studies investigate the antecedents and consequences of WOM usage. The former focuses mainly on firm characteristics as a factor influencing WOM usage. For example, Money et al. (1998) conducted exploratory interviews with purchasing managers of 48 start-up firms in Japan and the USA and showed that organizational culture plays a vital role in selecting B2B service providers. Specifically, Japanese companies are more likely to use WOM information sources than US companies because Japanese companies have a strong culture of collectivism and uncertainty avoidance. In addition, Yang et al. (2017) found that firms performing above expectations tend to choose suppliers based on partners’ referrals because they are more inclined to maintain the status quo and are less willing to take risks.

Existing studies focusing on the consequences of WOM usage investigate the effects of WOM usage and WOM type on outcome variables such as satisfaction and relationship continuity. In thesecases, the supplier is selected through WOM information. For example, Money (2004) indicated that buyer firms’ switching behaviors are influenced by the use of WOM and tie strength between the sender and receiver (buyer firms). Specifically, firms that use WOM information to select B2B service providers are less likely to switch to existing suppliers than those that do not. In addition, Japanese firms in Japan do not tend to change service providers when they consult WOM sources with high likability and/or expertise. Furthermore, Kim (2014) found that the higher the expertise of the WOM source and the more similar the buyer and the WOM source, the more likely that the buyer will establish a strong relationship and continue business with a supplier.

In summary, prior research has shown that using WOM to select business partners allows firms to form strong relationships with them and reduce the likelihood of switching to other firms in the future. In addition, prior research has shown that firms use WOM to reduce uncertainty and maintain their current favorable performance. However, there is insufficient empirical evidence on the relationship between WOM usage and firm performance. Insights are needed on how firms should use different types of WOM and under what conditions WOM usage is effective.

5.3 Theme III: reference marketing

Studies on reference marketing have addressed the question of how a B2B firm implements reference marketing. What are the consequences of this? Compared to Themes I and II, this theme is more recent in B2B marketing research. Approximately 70% of the studies under this theme have been published within the past 10 years. Since almost half (44.4%) of these studies use qualitative interviews, this topic is characterized by being in its early stages and is oriented toward theory building.

the supplier (i.e. selling firm);

reference customer (i.e. WOM source, WOM sender); and

potential customer (i.e. WOM receiver).

Figure 5 shows how the three parties are involved, depending on whether the communication mode is online (internet) or offline (face-to-face). In offline reference marketing, the supplier first asks the reference customer to spread positive WOM about the products or the supplier. The reference customer then shares their experience with the supplier’s brand with potential customers ( Hada et al. , 2014 ; Jaakkola and Aarikka-Stenroos, 2019 ). In the case of online reference marketing, the supplier posts the reference customer’s reviews on their website as success stories or testimonials. The website is then used to encourage potential customers to initiate a business relationship with the supplier and buy the brand ( Jalkala and Salminen, 2010 ; Tóth et al. , 2020 ).

supplier-focused;

reference customer-focused; and

potential customer-focused research.

Supplier-focused research investigates how B2B firms implement reference marketing and whether such practices lead to high firm performance. Jalkala and Salminen (2010) conducted exploratory interviews with 38 companies in the information and communication industry and showed that B2B firms use WOM (online references) collected from reference customers in two ways: the external use of customer references to promote sales and enhance the firm’s reputation and the internal use of customer references for employee training and customer understanding. Terho and Jalkala (2017) , using quantitative survey data collected from 220 B2B firms, found that both external and internal uses of customer references lead to high sales performance (e.g. new customer acquisition and large market share). Reference customer-focused research is limited: Jaakkola and Aarikka-Stenroos (2019) conducted interviews with 76 B2B firms in the knowledge-intensive services industry and examined the value of reference marketing to the supplier, reference customer and potential customer. They showed that reference customers try to strengthen their business relationships with suppliers by sharing their experiences with potential customers, but they also experience the risk of leaking information that could potentially harm the reference. Potential customer-focused research has been conducted to understand B2B customer behaviors. Hada et al. (2014) examined how reference valence and source credibility affect potential customers’ evaluation of suppliers. Through multiple experiments, they found that the effect of a positive reference is more meaningful when prospective buyers and source firms (i.e. reference customers) have previous business experience. They also showed that source credibility plays an important role only when the reputation of reference customers is high.

In sum, prior research has investigated the effectiveness of reference marketing from the perspective of three parties: suppliers, reference customers and potential customers. Although these studies have advanced our understanding of reference marketing, further work is needed to examine its impact on firm performance. New insights are required on what references firms should use and how to encourage their own salespeople to use references.

6. Managerial implications

By identifying three themes and summarizing the findings in each theme, we offer some useful suggestions for business managers. Specifically, we provide practical insights to sales managers of firms who sell goods/services and purchasing managers who buy them, respectively.

Sales managers of suppliers or selling firms should refer to research findings on decision-making regarding how existing customers communicate WOM (Theme I), how WOM is evaluated (Theme 2), and how reference customers’ WOM is leveraged (Theme 3). For example, the following suggestions can be drawn from prior literature. According to previous research on WOM generation ( Anaza and Rutherford, 2014 ), the loyalty of the purchasing manager toward the sales manager triggers positive WOM. Hence, salespeople should treat loyal customers with care, not only in terms of their large direct contribution to sales, but also in terms of their indirect contribution to sales through sales promotions to other companies. Research findings on WOM usage ( Yang et al. , 2017 ) indicate that in a highly competitive environment, high-performing firms are more likely to select business partners based on WOM; therefore, firms in a highly commoditized and highly competitive environment should place importance on existing customers as WOM generators. Furthermore, according to the research findings of reference marketing in Theme 3 ( Terho and Jalkala, 2017 ), firms should use customers’ opinions and success stories not only as a promotional tool but also as a learning material for sales representatives.

Purchasing managers in buyer firms should refer to research findings on decision-making regarding what benefits firms can obtain from sending WOM to other firms (Themes 1 and 3) and when firms should use WOM as a source of information (Theme 2). Jaakkola and Aarikka-Stenroos (2019) show that the dissemination of WOM as a customer reference allow firms not only to build close business relationships with supplier firms, but also to form strong relationships with potential customers. Kim (2014) reveals that using the WOM of other firms that have high expertise and are similar to one’s own firm to select business partners reduces the likelihood of switching business partners; thus, WOM from such firms should be considered important in making purchasing decisions.

Throughout this review, we indicated that WOM has a considerable influence on purchasing decisions in the B2B context. Although some B2B marketing managers may underestimate the role of WOM, online review websites for B2B products/services are widespread and online communities among purchasing managers are formed. Considering these trends, it is anticipated that WOM is more and more likely to drive purchasing decisions in the B2B context, just as WOM is a powerful influence in B2C marketing. Therefore, B2B marketing managers are required to use WOM as a strategic tool for firm success.

7. Discussion and future research directions

We conducted a systematic literature review of 36 articles to determine the current state of research on WOM in the B2B context. The following section discusses the future research directions for WOM research within all the three themes; that is, WOM generation, WOM usage and reference marketing. For each theme, we identify several research questions that should be addressed in future works. In addition to the three themes above, we identify promising research directions in two emerging themes not addressed by previous studies: collecting and managing WOM information about the supplier’s brand.

7.1 Word-of-mouth generation

Although B2B WOM research has examined the antecedents of WOM generation, it has only considered WOM generation as a positive outcome, along with other outcome indicators such as satisfaction and loyalty. Therefore, future research needs to address why buyers talk about selling firms and seller brands. Buyer firms probably send WOM messages to others to maintain their reputation in the market and to develop trust with their suppliers. It would be useful to assess such relationship drivers.

It is also helpful to focus on the WOM generation behaviors of individual purchasing managers in buyer firms. Some purchasing managers frequently send WOM to other buyers, while others generate none. Based on the findings of WOM research in the B2C context ( Berger, 2014 ; Donthu et al. , 2021 ; King et al. , 2014 ), psychological propensities such as altruism, self-enhancement and product involvement motivate buyers to send WOM. Additionally, purchasing managers with a vast informal network of contacts outside their firms are likely to generate WOM messages to maintain their networks. Therefore, it is essential to conduct qualitative and quantitative studies to examine the WOM communication behaviors of buyer firms.

To our surprise, no study has focused on the consequences of WOM generation. To deepen our understanding of WOM generation behaviors, it is necessary to investigate not only its antecedents but also its consequences. Future research should address the following research question: What are the consequences of WOM generation? For example, considering individual buyers, those who often send WOM to other buyers may obtain useful WOM information from other buyers in return. Consequently, the buyer can have a high level of knowledge about the market and its competitors. Providing such empirical evidence on the behaviors of buyer organizations and purchasing managers would contribute to the advancement of WOM research in the B2B context.

It is necessary to conduct qualitative and quantitative studies on the role of a supplier in generating WOM about their products or services. What kind of behavior is adopted by the suppliers in the first place? Although academic scholars, mainly in northern Europe, have assessed the online reference marketing activities of suppliers, other WOM activities have not been investigated. For example, how do suppliers make efforts to generate WOM about their offerings? What kind of firms focus on activities to induce WOM communication about their products? How supplier–sender relationships drive WOM generation? Future research should address these questions.

7.2 Word-of-mouth usage

Many studies have focused on factors that influence WOM usage behaviors. These studies address the question of when and why buyer firms use WOM information. While existing research has shown that organizational culture and performance affect WOM usage behaviors, there are many unanswered questions. For example, what product characteristics drive B2B firms to use WOM information? It is possible that B2B firms are more likely to use WOM when purchasing complex or innovative products. Future research should provide further empirical evidence on this topic.

B2B firms use various types of information sources: online and offline WOM, customer references, advertisements, salespeople and catalogs. Prior research has begun to address the use of WOM combined with other information sources ( Steward et al. , 2018 ; Tóth et al. , 2020 ). However, there is room for further investigation. Examples include the following: Which has a more substantial influence: online or offline WOM? How do salespeople’s explanations and external WOM information influence buyers’ purchase decisions? How much and what kind of WOM is used by B2B firms in the purchase decision-making process? Although pioneering research on WOM in the B2B context has addressed the latter questions ( Martilla, 1971 ), little research has focused on WOM in organizational purchase behavior since then. How much importance do purchasing managers give to WOM information from inside and outside the organization (i.e. intrafirm and interfirm WOM)? How do opinion leaders in an organization influence the purchase decision-making process? What are the characteristics of opinion leaders in an organization? Further research is needed to address these research questions.

One of the main questions on this topic is, “Does WOM usage lead to positive outcomes?” According to previous studies, WOM usage reduces uncertainty about suppliers and B2B offerings and enables firms to search for suitable exchange partners. Consequently, a mismatch of exchange partners can be prevented, thereby improving satisfaction and relationship continuity with the supplier. However, there is no satisfactory evidence on this topic. Intuitively, WOM communication is expected to increase satisfaction in an uncertain environment. Thus, future research can consider environmental factors. Furthermore, Money et al. (1998) showed that the effect of WOM usage on the intention of relationship continuity varies across nations. They focused only on collectivism and uncertainty avoidance among Hofstede’s six cultural dimensions, but how do other cultural dimensions affect WOM usage behaviors? Further research is required to investigate the role of organizational culture.

The following questions about WOM usage can be considered: What types of WOM improve supplier evaluation? How does WOM valence, a concept often used in WOM research in the B2C context, affect B2B offerings? Can negative WOM enhance supplier evaluations? Further, the effects of online reviews remain unclear: What types of online reviews are helpful for B2B firms? Future research should address these questions and provide empirical evidence.

7.3 Reference marketing

The most important consequence is firm performance, such as in sales, profits and market share. Thus, B2B marketers are interested in the impact of reference marketing on firm performance. Terho and Jalkala (2017) found that reference marketing, which consists of both external and internal use of online references, leads to high performance (e.g. new customer acquisition and market share). However, the effectiveness of reference marketing depends on various conditions and situations. Under what conditions is reference marketing effective? Which firms should invest in reference marketing? What type of reference marketing will improve firm performance? The number and type of references, the content of the references and the profile of the reference customers should impact firm performance.

A further exciting topic is the use of references in sales strategy, which has long been used in B2B marketing to promote the sales of a firm’s offerings. In B2B marketing, customer references are not an alternative for a salesperson but rather a supplementary means. Thus, B2B firms need to combine customer and salesperson references to improve their performance. However, little is known about the relationship between sales management and customer references. How does a salesperson use customer references as a sales tool? Do salespeople who use references achieve higher sales than those who do not? How does a sales force respond to potential customers who receive WOM messages about the firm? These questions are of great academic and practical relevance. Therefore, future research should address these questions.

Examining the motivations of existing customers to serve as reference customers can yield rich managerial implications because it can provide selling firms with guidelines regarding the selection and recruitment of reference customers. Intuitively, one of the motivations for a customer to become a reference customer at a supplier’s request would be to strengthen their relationship with the supplier. However, little empirical evidence is provided on reference customer behaviors. Why does a reference customer send WOM for their suppliers? How does becoming a reference customer lead to a close relationship with suppliers? Future studies are encouraged to investigate these research questions.

7.4 Word-of-mouth collection

The theme of WOM collection addresses how firms collect WOM information about their own brands. Prior research in this review assumes that existing customers’ WOM about the supplier’s brand is valuable information for potential customers (e.g. potential customers can rely on WOM information to make accurate purchase decisions). However, it is also beneficial to the supplier itself. WOM information about a supplier’s brand represents the customer’s honest evaluation of the supplier’s products, which allows the supplier to understand the strengths and weaknesses of its own brand, the uniqueness of its own products, and points to be improved in its services. This is a valuable source of information for the supplier. Therefore, firms should actively collect such WOM information about their B2B products/services to develop product innovations and understand the appeal of their brands.

However, according to this systematic review, no studies focused on supplier WOM behavior regarding supplier branding and collection behavior by suppliers. Therefore, future research should address this topic. For example, how can firms collect WOM information about their products from existing customers? It would not be so easy to collect face-to-face WOM information from existing customers. Collecting negative WOM from existing customers is challenging because they do not want to communicate it directly to suppliers. However, suppliers need to collect such information because negative WOM contains information on what needs to be improved in their brands and what customers need. How can firms collect negative WOM? Perhaps, it might be more efficient to collect it indirectly from intermediaries rather than directly from customers ( Ishii, 2021 ).

Regardless of whether WOM is positive or negative, it is valuable information for a firm. It is also precious for an individual salesperson. This is because salespeople who understand the firm’s brand and capture customer needs through WOM can achieve better sales performance than other salespeople. Therefore, salespeople may hesitate to inform other salespeople or their supervisors about WOM about their brand and may keep the information confidential. If this is true, a key factor for WOM collection is establishing a system to gather WOM information from the in-house salespersons. The collection of WOM information, if regarded as the generation of market information, is included in market-oriented behavior ( Ishii, 2020 ; Mostafiz et al. , 2021 ; Powers et al. , 2020 ). It would be interesting to provide empirical evidence on whether the collection of WOM information enhances firm outcomes.

7.5 Word-of-mouth management

The second is the management of WOM about the firm’s brand. Prior studies generally focus on the role of positive WOM, such as sending out positive WOM and posting positive WOM on the company’s website. While previous studies ( Gruber et al. , 2010 ; Homburg and Fürst, 2005 ) have addressed how B2B firms respond to customer complaints (i.e. a type of negative WOM), to the authors’ knowledge, no research has addressed how they respond to negative electronic WOM. This is because, as mentioned above, negative WOM is not often received by suppliers. However, now that social networking services have become widespread, and B2B purchasing managers have formed connections through LinkedIn, Facebook, etc. and informal communication in closed networks has become more accessible, negative WOM can spread quickly among customers. Therefore, how a company responds to negative WOM may impact its survival.

For example, how should B2B firms respond to negative WOM on online review websites? Currently, online review websites for B2B brands are becoming popular. Owing to the source’s anonymity, negative WOM is more likely to be communicated online than in person. Therefore, it will become increasingly critical for B2B marketers to manage negative WOM. Another unanswered question is how B2B marketers should respond to negative WOM on social networking sites. Some B2B brand firms have their own social networking accounts and may receive complaints or requests for improvement on their timelines or through direct messages. How should companies respond to such customer feedback to maintain their high evaluation by their customers? Academic researchers in the field of B2B marketing are expected to make efforts to address these research questions.

8. Conclusion

Both academic researchers and business practitioners have recognized that WOM plays an essential role in B2B marketing. In fact, many B2B studies have examined WOM and reference marketing during the past 20 years. However, no reviews focus on WOM in the B2B context. Since various findings have been presented on this topic, it is imperative to assess the current state of WOM research and clarify unaddressed research questions. This study aims to synthesize the findings from existing studies on WOM in the B2B context, propose an integrated conceptual framework and identify potential research directions.

Through a systematic review, 36 articles on B2B WOM were selected. We then described the published journals, the countries used as the subject of the empirical analysis, and the methods used by these articles. Our thematic analysis categorized these articles into three themes:

Under each theme, we summarized research findings unique to B2B research different from B2C WOM research. We identified several research questions that should be addressed by future research. By synthesizing and assessing prior research on WOM in the B2B context, we hope to have contributed to a better understanding of the B2B WOM phenomenon and facilitated future research on this topic.

WOM phenomenon

Search strategy

Research methods used in selected articles

Researched contexts in selected articles

WOM flowchart in reference marketing

Journals included in the analysis

Overview of the findings from the reviewed articles

Four types of WOM

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Acknowledgements

The authors would like to thank the Editor-in-Chief, Dr. Wesley Johnston, and anonymous reviewers for providing valuable insights and constructive comments.

Funding : This work was financially supported by JSPS KAKENHI Grant Number JP18K12883.

Corresponding author

About the authors.

Ryuta Ishii is an Associate Professor of Marketing at the College of Business Administration, Ritsumeikan University, Japan. His research interests focus on business-to-business relationships, channel management and international marketing. His work has been published in Industrial Marketing Management , International Marketing Review , Marketing Intelligence & Planning and other journals.

Mai Kikumori is an Associate Professor of Marketing at the College of Business Administration, Ritsumeikan University, Japan. Her research interests focus on digital marketing and social interactions, particularly in word-of-mouth, online review and social media usage.

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MINI REVIEW article

A literature review of word of mouth and electronic word of mouth: implications for consumer behavior.

• Economía Española e Internacional, Econometría e Historia e Instituciones Económicas, University of Castilla-La Mancha, Albacete, Spain

The rise and spread of the Internet has led to the emergence of a new form of word of mouth (WOM): electronic word of mouth (eWOM), considered one of the most influential informal media among consumers, businesses, and the population at large. Drawing on these ideas, this paper reviews the relevant literature, analyzing the impact of traditional WOM and eWOM in the field of consumer behavior and highlighting the main differences between the two types of recommendations, with a view to contributing to a better understanding of the potential of both.

Introduction

Consumers increasingly use online tools (e.g., social media, blogs, etc.) to share their opinions about the products and services they consume ( Gupta and Harris, 2010 ; Lee et al., 2011 ) and to research the companies that sell them. These tools are significantly changing everyday life and the relationship between customers and businesses ( Lee et al., 2011 ).

The rapid growth of online communication through social media, websites, blogs, etc., has increased academic interest in word of mouth (WOM) and electronic word of mouth (eWOM) (e.g., Hennig-Thurau et al., 2004 ; Brown et al., 2007 ; Cheung and Thadani, 2012 ; Hussain et al., 2017 ; Yang, 2017 ). Specifically, the present paper will review the literature on how these two media have evolved, the main differences between them, and the degree to which they influence both businesses and consumers, now that they have become some of the most influential information sources for decision-making.

Word of mouth is one of the oldest ways of conveying information ( Dellarocas, 2003 ), and it has been defined in many ways. One of the earliest definitions was that put forward by Katz and Lazarsfeld (1966) , who described it as the exchanging of marketing information between consumers in such a way that it plays a fundamental role in shaping their behavior and in changing attitudes toward products and services. Other authors (e.g., Arndt, 1967 ) have suggested that WOM is a person-to-person communication tool, between a communicator and a receiver, who perceives the information received about a brand, product, or service as non-commercial. Likewise, WOM has been defined as communication between consumers about a product, service, or company in which the sources are considered independent of commercial influence ( Litvin et al., 2008 ). These interpersonal exchanges provide access to information related to the consumption of that product or service over and above formal advertising, i.e., that goes beyond the messages provided by the companies and involuntarily influences the individual’s decision-making ( Brown et al., 2007 ). WOM is widely regarded as one of the most influential factors affecting consumer behavior ( Daugherty and Hoffman, 2014 ). This influence is especially important with intangible products that are difficult to evaluate prior to consumption, such as tourism or hospitality. Consequently, WOM is considered the most important information source in consumers’ buying decisions ( Litvin et al., 2008 ; Jalilvand and Samiei, 2012 ) and intended behavior. For example, tourist satisfaction is of utmost importance because of its influence on behavioral intentions, WOM and purchasing decisions. In other words, overall satisfaction leads to the possibility of revisiting and recommending the destination ( Sotiriadis and Van Zyl, 2013 ).

Similarly, previous research indicates that consumers regard WOM as a much more reliable medium than traditional media (e.g., television, radio, print advertisements, etc.) ( Cheung and Thadani, 2012 ). It is thus considered one of the most influential sources of information about products and services ( Lee and Youn, 2009 ). Users generally trust other consumers more than sellers ( Nieto et al., 2014 ). As a result, WOM can influence many receivers ( Lau and Ng, 2001 ) and is viewed as a consumer-dominated marketing channel in which the senders are independent of the market, which lends them credibility ( Brown et al., 2007 ). This independence makes WOM a more reliable and credible medium ( Arndt, 1967 ; Lee and Youn, 2009 ).

Today’s new form of online WOM communication is known as electronic word-of-mouth or eWOM ( Yang, 2017 ). This form of communication has taken on special importance with the emergence of online platforms, which have made it one of the most influential information sources on the Web ( Abubakar and Ilkan, 2016 ), for instance, in the tourism industry ( Sotiriadis and Van Zyl, 2013 ). As a result of technological advances, these new means of communication have led to changes in consumer behavior ( Cantallops and Salvi, 2014 ; Gómez-Suárez et al., 2017 ), because of the influence they enable consumers to exert on each other ( Jalilvand and Samiei, 2012 ) by allowing them to obtain or share information about companies, products, or brands ( Gómez-Suárez et al., 2017 ).

One of the most comprehensive conceptions of eWOM was proposed by Litvin et al. (2008) , who described it as all informal communication via the Internet addressed to consumers and related to the use or characteristics of goods or services or the sellers thereof. The advantage of this tool is that it is available to all consumers, who can use online platforms to share their opinions and reviews with other users. Where once consumers trusted WOM from friends and family, today they look to online comments (eWOM) for information about a product or service ( Nieto et al., 2014 ).

As a result of ICT, today consumers from all over the world can leave comments that other users can use to easily obtain information about goods and services. Both active and passive consumers use this information medium (eWOM). Individuals who share their opinions with others online are active consumers; those who simply search for information in the comments or opinions posted by other customers are passive consumers ( Wang and Fesenmaier, 2004 ).

Electronic word of mouth also provides companies with an advantage over traditional WOM insofar as it allows them both to try to understand what factors motivate consumers to post their opinions online and to gauge the impact of those comments on other people ( Cantallops and Salvi, 2014 ). However, consumers’ use of technology to share opinions about products or services (eWOM) can be a liability for companies, as it can become a factor they do not control ( Yang, 2017 ). To counteract this, businesses are seeking to gain greater control of customers’ online reviews by creating virtual spaces on their own websites, where consumers can leave comments and share their opinions about the business’s products and services ( Vallejo et al., 2015 ). By way of example, in the field of tourism, companies are starting to understand that ICT-enabled media influence tourists’ purchasing behavior ( Sotiriadis and Van Zyl, 2013 ).

Understandably, companies view both types of recommendations – WOM and eWOM – as a new opportunity to listen to customers’ needs and adjust how they promote their products or services to better meet them, thereby increasing their return. A negative or positive attitude toward the product or service will influence customers’ future purchase intentions by allowing them to compare the product or service’s actual performance with their expectations ( Yang, 2017 ).

In the field of consumer behavior, some previous studies (e.g., Park and Lee, 2009 ) have shown that consumers pay more attention to negative information than to positive information ( Cheung and Thadani, 2012 ). For example, the customers most satisfied with a product or service tend to become loyal representatives thereof via positive eWOM ( Royo-Vela and Casamassima, 2011 ), which can yield highly competitive advantages for establishments, businesses, or sellers, especially smaller ones, which tend to have fewer resources. Some studies have suggested that traditional WOM is the sales and marketing tactic most often used by small businesses.

Additionally, eWOM offers businesses a way to identify customers’ needs and perceptions and even a cost-effective way to communicate with them ( Nieto et al., 2014 ). Today, eWOM has become an important medium for companies’ social-media marketing ( Hussain et al., 2017 ).

WOM vs. eWOM

While many authors (e.g., Filieri and McLeay, 2014 ) consider eWOM reviews to be electronic versions of traditional WOM reviews, this paper aims to summarize and explain the main differences between the two concepts (Table 1 ). The first such difference is credibility as an information source ( Cheung and Thadani, 2012 ; Hussain et al., 2017 ), since it can influence consumers’ attitudes toward products or services ( Veasna et al., 2013 ), for example, with regard to the purchase of tourism services, which are considered to be high-risk ( Sotiriadis and Van Zyl, 2013 ). Luo et al. (2013) have suggested that the anonymity of online messages could have a negative effect on their credibility. In contrast, other studies (e.g., Hussain et al., 2017 ) have argued that consumers use eWOM more to reduce risk when decision-making. Likewise, eWOM tends to be more credible when the consumer using it has previous experience ( Sotiriadis and Van Zyl, 2013 ).

TABLE 1. Differences between WOM and eWOM.

Message privacy is another feature that sets the two media apart, since with traditional WOM information is shared through private, real-time, face-to-face dialogs and conversations. In contrast, information shared through eWOM is not private and can sometimes be seen by anonymous people who do not know each other. Furthermore, reviews can be viewed at various points in time ( Cheung and Thadani, 2012 ). Indeed, because eWOM reviews are written, consumers and companies can check them at any time; this stands in contrast to traditional WOM, where once the message has reached the receiver, it tends to disappear.

Another salient difference between the two media is the speed of diffusion of the message; eWOM statements spread much faster than WOM statements because of where they are published, i.e., on the Internet ( Gupta and Harris, 2010 ). Online platforms for sharing information (social media, websites, blogs, etc.) are what set eWOM apart from traditional WOM ( Cheung and Thadani, 2012 ). First, they make the reviews accessible to more consumers ( Cheung and Thadani, 2012 ; Sotiriadis and Van Zyl, 2013 ). Second, because they are written, they persist over time ( Hennig-Thurau et al., 2004 ; Cheung and Thadani, 2012 ).

This paper has reviewed the literature with a view to providing a clearer understanding of WOM and eWOM in the context of consumer information searches.

To this end, the review found that, in keeping with numerous studies, WOM is both the oldest medium for sharing opinions about products or services and the one most likely to influence consumer behavior, due to the high reliability and credibility transmitted by family and friends. In contrast, few studies have examined the interaction between perceived risk and eWOM source credibility ( Hussain et al., 2017 ).

Notwithstanding the above, the review of the theoretical framework also revealed a gap in the literature on WOM credibility in situations involving multiple or many communicators and receivers and how this ultimately affects the end consumer. This would include, for instance, situations in which one person communicates a message to another, who acts as an intermediary, both receiving the original message and passing it along to a third party, i.e., the end consumer. In such cases, the original message can be altered or distorted, chipping away at the credibility of the WOM review as a source of information. This lends much more strength to written comments and reviews, such as eWOM, which can ultimately reduce risk and increase consumer confidence.

Another feature that distinguishes eWOM from traditional WOM is the speed with which it spreads and the ease of access to it. In this regard, when consumers need information about a product or service, they ultimately turn to online media (eWOM) for two reasons. First, they can get the information more quickly, as there is no need to wait for someone else – a friend or family member – to offer an opinion about what they wish to consume. Second, if they have already received WOM reviews, they can use eWOM to corroborate the information received. Therefore, credibility and speed are the two main features not only distinguishing the two media, but also influencing consumer behavior.

Finally, the analysis of the review showed that these two concepts – WOM and eWOM – while seemingly the same, are at the same time very different. The Internet has transformed traditional WOM into eWOM. The communication of opinions is no longer done interpersonally (i.e., person-to-person or face-to-face), but rather is mediated by ICT. However, the many studies conducted (e.g., Katz and Lazarsfeld, 1966 ; Brown et al., 2007 ; Daugherty and Hoffman, 2014 ; Yang, 2017 ) agree that they are the media most able to influence consumer behavior and the most often used to obtain information before, during, and after consuming a given product or service. For example, in the field of tourism, eWOM is considered the most influential pre-purchase source of travel information ( Sotiriadis and Van Zyl, 2013 ).

Author Contributions

This paper tries to offer a clearer understanding of the two concepts through a literature review and an exploration of how, as a result of advances in ICT, traditional WOM has given rise to eWOM. The author has made an important, direct, intellectual contribution to this paper and has approved it for publication.

This research was funded by the Spanish Ministry of Economy and Competitiveness under Research Project ECO2014-59688-R (“Planning and implementation of optimal management strategies for physical, online and mobile POSs based on ICT and innovation”).

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords : businesses, consumers, WOM, eWOM, communication

Citation: Huete-Alcocer N (2017) A Literature Review of Word of Mouth and Electronic Word of Mouth: Implications for Consumer Behavior. Front. Psychol. 8:1256. doi: 10.3389/fpsyg.2017.01256

Received: 31 March 2017; Accepted: 10 July 2017; Published: 25 July 2017.

Reviewed by:

Copyright © 2017 Huete-Alcocer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Nuria Huete-Alcocer, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Psychology of word of mouth marketing

Affiliations.

• 1 Miami Business School, University of Miami, 5250 University Drive, Coral Gables, FL 33124, United States. Electronic address: [email protected].
• 2 Miami Business School, University of Miami, 5250 University Drive, Coral Gables, FL 33124, United States.
• PMID: 31377578
• DOI: 10.1016/j.copsyc.2019.06.026

Given the importance of online word of mouth (WOM), there has been an increasing need to understand the psychological mechanisms that underlie WOM transmission (i.e. sharing of opinions) and reception (i.e. processing of received messages). The goal of the current paper is to review some of the most recent research in online WOM (focusing on the past two to four years) as well as make suggestions regarding future research. [For earlier syntheses on WOM senders and social media marketing, see King et al., 2014, Stephen, 2016, Whitler, 2014] [6-8].

Copyright © 2019 Elsevier Ltd. All rights reserved.

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17 Word-of-Mouth Marketing

Jillian C. Sweeney (PhD, Marketing, Curtin University, Australia) is Winthrop Professor of Marketing at the University of Western Australia. Her research interests focus on the customer’s role in services and include word of mouth effectiveness in marketing, customer co-creation of value in health and financial services, and enhancing sustainable energy-saving behavior through communication.

• Published: 08 May 2018
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Word of mouth (WOM) reflects informal communication between private individuals that evaluates goods and services ( Anderson, 1998 ). It provides a highly credible means of persuasion because the communicator is not seen as having a vested interest in selling the recommended product or service. In this chapter, WOM is conceptualized as a type of advice between private parties (typically consumers), focused on goods or services, and not necessarily purposeful or directive. WOM is a very powerful tool, especially given the relatively new focus in marketing on customer engagement and the customer’s role in value co-creation in the context of market offerings. However, over the decades, a number of myths have developed surrounding the effects of WOM. These myths are challenged within a review of the research literature. Suggestions for future research directions, research methods to capture WOM, and some best practices are also discussed.

Organizations recognize the importance of striving for new ways to achieve and retain a competitive edge within an increasingly complex market. At the same time, customers are becoming more discerning and steadily taking a more active role in product and service delivery, with a corresponding reduction in consumer trust of both organizations and advertising. In this climate, word of mouth (WOM) offers a way to obtain a significant competitive advantage (International WOM Marketing Conference, 2005; Sweeney, Soutar, & Mazzarol, 2008 ).

The ability of individuals to influence other peoples’ opinions is of particular interest to marketers. The topic of this chapter, WOM, is defined as “informal communication between private parties concerning evaluations of goods and services” ( Anderson, 1998 , p. 6). At its core, WOM is a process of personal influence through which interpersonal communication between a sender and a receiver can change the receiver’s behavior or attitudes ( Merton, 1968 ). WOM provides a highly credible means of persuasion because the communicator is not seen as having a vested interest in selling the recommended product or service and is likely to convey information in a meaningful way ( Herr, Kardes, & Kim, 1991 ; Silverman, 2001 ).

Despite significant interest in and research on the topic, several commonly accepted myths have developed around WOM in the practitioner and the academic literature. These myths have become accepted through repetition and mention in informal communication and books, even textbooks, and include:

WOM is most effective when spread by opinion leaders.

WOM is most likely to be given about high-risk or high-involvement products

Negative WOM is more common and more influential than positive WOM.

Negative WOM is always detrimental.

WOM or electronic WOM (eWOM) is the best form of promotion; traditional advertising is redundant.

These myths will be challenged throughout this chapter, which is organized as follows. First, the concept of WOM is discussed in detail, including its relationship to advice and the core differences between WOM and eWOM. This is followed by a discussion of situational factors, such as the type of person who may give WOM and the types of products for which WOM is given. Differences between the impact of positive and negative WOM are then examined, including commonality and impact as well as the link between WOM and advertising. Later in the chapter, we focus on incentivized WOM from the viewpoints of both the giver and the receiver. The chapter concludes with a discussion of possible future research; methods used in WOM research, including some novel approaches; and points for best practice.

Conceptualizing WOM

Often, researchers view WOM as a binary concept—that is, a person gives it or does not. Hence, measures of WOM typically rely on counting how many mentions are made of a firm or offering, based on recall (e.g., Anderson, 1998 ; Bowman & Naryandas, 2001 ; Westbrook, 1987 ), while future intent is captured via measures of the likelihood of providing WOM (e.g., Hartline & Jones, 1996 ). However, WOM is far more nuanced than a mere “utterance.” It incorporates both verbal and nonverbal behavior and varies in the detail provided (e.g., Bone, 1992 ), all of which have a bearing on the strength and delivery of WOM ( Anderson, 1998 ; Mazzarol, Sweeney, & Soutar, 2007 ).

Among modern day researchers, Anderson (1998) was one of the earliest to recognize the importance of WOM’s communication aspects, suggesting these can vary in vividness, pleasantness, and novelty. WOM may convey a giver’s experiences favorably (i.e., positive WOM) or may focus on unpleasant experiences, denigrating products via rumors or private complaining (i.e., negative WOM; Anderson 1998 ). Sweeney, Soutar, and Mazzarol (2012) identified three dimensions of WOM: (1) cognitive content (i.e., clarity and reliability of information content), (2) richness of content (i.e., vividness or elaborateness of information), and (3) strength of delivery (i.e., power of words or gestures). Those researchers also derived a measure of these three aspects, each of which contributes to message persuasiveness for both positive and negative WOM messages. Customer-perceived service quality, satisfaction, and an enjoyable experience increased the chances of giving WOM with these characteristics. Further, receiving a message rated highly on each of these characteristics was also more likely to change the receiver’s evaluations with respect to the product or service.

Both Anderson’s (1998) and Sweeney et al.’s (2012) research emphasizes the richness and variation of the behavior encompassed by the WOM concept. Overall, WOM is a highly persuasive form of communication. Further, due to its consumer-to-consumer nature, it is ubiquitous, persuasive, credible, and of great interest to marketers across commercial, government, and not-for-profit organizations.

WOM and Advice

It is useful to consider how WOM relates to advice, the topic of this Handbook. Communication scholars have defined advice as recommendations about what might be thought, said, or done to manage a problem ( MacGeorge, Feng, & Thompson, 2008 ; see also Chapter 1 ). Consistent with this definition, it is often operationalized as a relatively explicit recommendation ( MacGeorge, Feng, & Guntzviller, 2016 ). Communication theorists have also emphasized that advice functions both as a form of social support, intended to reduce recipients’ distress and enhance their coping, and as social influence, persuading recipients to take action to solve their problems ( MacGeorge, Guntzviller, Hanasono, & Feng, 2016 ). Further, advice can be exchanged between virtually any pair of actors (or group of actors) in a network (see Chapter 6 ).

In several respects, WOM is a narrower construct than advice. It always takes place between customers, though this can be one-to-one or one-to-many, such as via social media. In addition, it is always related to products (whether goods or services). Whereas advice is often conceptualized as intentional behavior (i.e., support or influence), WOM is not necessarily purposeful and may occur serendipitously. Importantly, WOM may or may not include a specific recommendation for action. Indeed, there has been considerable debate about whether WOM involves an active recommendation or is merely a positive or negative discussion about a product or other offering. Clearly, a distinction exists between simply recounting experiences with an organization, which may imply a recommendation, and actively recommending that organization. Recent research indicates that approximately one-third of WOM contains an active recommendation ( East, Uncles, Romaniuk, & Dall’Olmo Riley, 2015 ). In all, WOM can be regarded as a variant of advice, with a particular profile of advisors, advisees, and advice content and considerable range in the explicitness of recommendation.

WOM Versus eWOM

Social media is now regarded as an essential channel for communicating with customers, with organizations setting up Facebook and Twitter accounts in pursuit of connecting with consumers. In fact, most researchers assert that the majority of WOM is currently via electronic channels, with the volume of online WOM (i.e., eWOM) dominating offline ( Lovett, Peres, & Shachar, 2013 ), although this is disputed by Keller and Fay (2102), who argue that 90% of WOM is either face-to-face or via the telephone. Nonetheless, many of the principles of WOM and eWOM overlap, and for the purposes of subsequent sections of this chapter, the discussion is related to both unless specifically stated.

Some basic differences, however, have implications for marketing strategy. First, given the multiple interactions possible online, eWOM’s volume and reach are almost unlimited compared to face-to-face WOM ( King, Racherla, & Bush, 2014 ). Second, eWOM communication is largely asynchronous and visually displayed, such as via Facebook or an online review site, with the “evidence” lasting for quite some time. Therefore, the communication is visually memorable and can be revisited on multiple occasions. In many cases, this communication is available on-demand to other consumers seeking information, which enables contacts between weak ties and dispersion of WOM through a more extensive network than would be obtained via traditional WOM channels and generating future eWOM. Third, given the relative anonymity of online communication, there is greater opportunity for fake reviews and online deception ( King et al., 2014 ). This includes other businesses attempting to knock down competitors or create fake positive reviews for their own brands, and consumers denigrating brands for vengeance or fun. This highlights the need for brand managers and consumers to behave ethically and for strong norms of user behavior. Further, and not least, eWOM platforms support clusters of individuals in creating nongeographically bound communities on topics of mutual interest. Thus, the traditional firm-customer engagement model is now mediated by an intermediary level comprising communities that inherently have their own culture and norms. Marketers may then strategically communicate with such communities in order to reach individuals.

Addressing the Five WOM Myths

This section addresses the five commonly held myths discussed in the introduction and finds evidence to refute each. Overall, a considerable, more recent body of work has built up around WOM, dispelling the myths developed in earlier times.

Who Gives WOM?

Early researchers, realizing that people may be more influenced by each other than they are by the media, theorized a two-step flow model of influence. In this model, a small number of opinion leaders convey information from the media to the rest of society. Opinion leaders are defined by Katz and Lazarsfeld (1955) as individuals who are likely to influence other persons in their immediate environment. Burt (1999) explains this as a two-step process of (1) moving information from the media to opinion leaders and (2) moving the information from opinion leaders to followers based on the opinion leaders’ influence and connections. This two-step model became core to discussions on the diffusion of innovations and was lauded as a key formulation in the behavioral sciences. However, more recent research has emphasized that WOM is “everyone’s” domain, rather the purview of an influential few ( Gladwell, 2002 ). Sociologists agree: Watts and Dodds (2007) , for example, find evidence that “most social change is driven not by influential people, but by easily influenced individuals influencing other easily influenced individuals” (p. 442). This refutes Myth 1—that WOM is most effective when spread by opinion leaders.

Types of Products Discussed in WOM

Although WOM communication can be very influential in any purchase decision, it is particularly important in a service context. This is because services are intangible and, thus, difficult to evaluate before purchase. Further, services are typically neither covered by a guarantee nor standardized and so are associated with higher risk than are goods (e.g., Mangold, Miller, & Brockway, 1999 ). While this may suggest that high-risk, such as high-price, products are the most common topics of WOM, and also more likely to benefit from it, this is often not the case. In a study of the most talked about US National brands, Lovett et al., (2013) found that telecommunications, department stores, technology, cars, and beverages were the brand types most talked about offline. In the case of online WOM, these same brand categories, as well as brands associated with sports and hobbies, along with media and entertainment were the most typical. For example, the most mentioned brands online were Google, Facebook, iPhones, and YouTube, and the most mentioned brands offline were Coca-Cola, Verizon, Pepsi, and Walmart ( Lovett et al., 2013 ). These product and service brands are largely not high risk or expensive. Products and information that evoke the most interest, arouse more emotion, and contain useful information are more likely to be discussed, supporting the idea that that interesting information and stories in general, and not specifically those relating to high risk products, are most likely to be shared ( Chen & Berger, 2016 ). Myth 2—that WOM is most likely with regard to high-risk or high-involvement products—is therefore not supported.

Positive and Negative WOM

WOM can be both positive and negative. In fact, most WOM messages are very positive or very negative ( Anderson, 1998 ; Maxham & Netemeyer, 2002 ). Negative WOM is anecdotally regarded as more common, and until recently, marketing textbooks have cited this belief, quoting ratios of two or more to one when comparing negative to positive. However, recent research refutes this claim. In a study across a variety of products and services, East, Hammond, and Wright (2007) found that the positive WOM penetration among users (percentage of users giving positive WOM about a brand in that product category) was 2.7 times higher than the negative WOM penetration among users (46% vs. 17%), while the frequency of a giver giving positive or negative WOM was similar. In essence, most customers are satisfied; hence, the opportunity for positive WOM is greater than negative. Thus, contrary to the first part of Myth 3—that negative WOM is more common—recent evidence shows that positive WOM has a higher penetration and occurs more often.

Considering influence, many early WOM researchers suggested negative product information had more impact on consumers’ decision making than did positive WOM, which has also turned into an often-quoted maxim with limited evidence. Arndt (1967) found unfavorable WOM was more effective in changing purchase intentions. However, that study addressed only one brand, which was a new brand in a food category, limiting the generalizability of the finding. Later, Mizerski (1982) found negative product information led to stronger performance attributions, belief strength, and affect. However, more recent research suggests positive WOM has greater influence. For example, East, Hammond, and Lomax (2008) found 64% of receivers felt that positive WOM influenced their purchase decisions, while 48% felt that negative WOM did (the difference was significant at p < .01). Further, the shift in their resulting purchase probability following receipt of WOM was +.20 for positive WOM, but only −.11 for negative WOM, such that positive WOM had a significantly greater absolute impact on purchase probability ( p < .05). Positive messages have also been found to be more influential on willingness to use a service ( Sweeney, Soutar, & Mazzarol, 2014 ).

Because positive WOM is more common ( East et al., 2007 ), a person receiving a message may expect a sender in general to be moderately positive ( Skowronski & Carlston, 1989 ). Also, people generally receive more positive than negative information so that most WOM message receivers probably have an initially positive attitude ( East et al., 2008 ). Social judgment theory argues that assimilation mechanisms influence how people respond to messages ( Maio & Haddock, 2007 ), which people compare with their prior position or attitude. Messages reflecting a position similar to the receiver’s fall into a latitude of acceptance that is close to the recipient’s existing position, so these messages are assimilated and change attitudes. In contrast, divergent messages fall into a latitude of rejection, do not get assimilated, and are often contrasted away from the recipient’s initial attitude, creating little or no attitude change ( Sherif, Taub, & Hovland, 1958 ). Thus, it can be argued that positive messages are likely to be more similar to the receiver’s position and accepted by the receiver, while negative messages are more divergent and more likely to be rejected. Further, consumers tend to be forgiving of negative events, and receipt of negative WOM has been found to change service evaluations less in absolute terms than receipt of positive WOM ( Sweeney et al., 2012 ). These arguments are contrary to the second part of Myth 3—that negative WOM is more influential than positive WOM.

It is also important to note that negative WOM, while often detrimental to the brand, can at times have a positive influence. Liu (2006) , for example, found that WOM from movie-goers offered significant explanatory power for both aggregated and weekly movie box office revenue, and that this was mainly a result of the volume of WOM (combined positive and negative), not its valence. This was particularly true for the opening week, but the effect persisted for up to six weeks. Indeed, valence did not statistically contribute to the revenue at any stage. Moreover, in some cases, negative WOM alone can have a significant positive effect; for example, Reimer and Benkenstein (2016) found that in the case of online reviews, a negatively valenced one has a positive effect on purchase intention when the review information is perceived as highly untrustworthy. They termed this the boomerang effect , which refers to the reactance of the receiver in response to feeling some form of external pressure, such as when the recommender has ulterior motives. This occurs when the receiver wants to react against the biased persuasion attempt.

While managers may regard negative WOM as harmful and to be moderated to reduce its impact, it is worth noting that positive and negative WOM are often generated by the same people. Given that a person is likely to take into account the needs of the receiver, they may give positive WOM to one person and negative WOM to another about the same brand (e.g., East et al., 2008 ). Indeed East et al. (2007) found an average correlation between a person’s positive and negative WOM frequency of .26 across a range of products and services. Overall, both positive and negative WOM volume have been found to correlate with market share across a range of product categories ( Uncles, East, & Lomax, 2010 ). This may not be surprising since more consumers are aware of leading brands and have direct experience of these brands (as buyers and/or users). It would also seem that both positive and negative WOM volume depends on brand size. These findings suggest that WOM may function in terms of creating awareness, whether the WOM is positive or negative. Thus, Myth 4—that negative WOM is always detrimental—is rebutted.

WOM and Advertising

As people become more educated and informed, they may be less likely to trust businesses and be influenced by traditional advertising ( Urban, 2004 ). It would appear that traditional media is losing its effectiveness ( Sweeney et al., 2012 ; Trusov, Bucklin, & Pauwels, 2009 ) while social media has made the dissemination of WOM more rapid and pervasive ( Wien & Olsen, 2014 ). Early studies suggested that WOM is nine times as effective as traditional advertising in converting unfavorable or neutral predispositions into positive attitudes (e.g., Day, 1971 ). However, is this effect really so pronounced?

Approximately one in four WOM offline conversations about products involve a reference to traditional media, such as TV advertising ( Keller & Fay, 2012 ). Such conversations relate primarily to entertainment, technology, personal care, automotive, telecommunications, retail outlets, and household products. Similarly, 32% of online conversations contain an advertising reference. The increase may be because online communication facilitates access to advertising material (e.g., images and videos) that are readily disseminated and likely to generate discussion. WOM relating to advertising is more likely to trigger a specific recommendation to buy or try a brand than other WOM about the brand ( Keller & Fay, 2009 ). For example, strong recommendations were made by the giver in 47% of advertising-related messages on entertainment, compared to 36% in non-advertising-related WOM. The authors found similar effects for other industries, including financial services, home products, and sports and recreation.

The extent to which WOM complements and extends advertising has been quantified. Hogan, Lemon, and Libai (2004) showed that WOM can triple the effectiveness of advertising when estimating customer lifetime value, which includes consideration of a customer spreading positive WOM leading to new customers for the organization and, iteratively, of these newly recruited customers similarly spreading positive WOM. Simultaneously, Hogan, Lemon, and Libai (2004) take into account customers defecting over time and, thus, explain the overall model as a “ripple effect.” Further evidence of the interrelationship of different forms of marketing communications is offered by Bayus (1985) , who found in the context of military recruiting that traditional advertising, WOM, and sales (recruitment) were interrelated, such that traditional marketing efforts were associated with WOM. For example, traditional marketing efforts, including advertising and the recruiter salesforce, stimulated potential recruits who had not decided whether to enlist to seek further information and opinions (i.e., WOM) from family and friends. Bayus summarized this in a model in which traditional marketing efforts stimulate not only sales but WOM, which leads to sales, which can in turn generate further WOM. Indeed, a recent study by Hewett, Rand, Rust, and van Heerde (2016) demonstrates the strong positive interrelationships between old and new media, including traditional media news stories, online WOM, and firm-generated communications (e.g., press releases and Twitter posts). This research shows that organizations need to optimize trade-offs across the strengths of each form of media to achieve the required market position and deliver a consistent message. Thus, we reject Myth 5—that WOM or eWOM has become the best form of communication and that traditional advertising is not needed.

Motivations for WOM

Naturally occurring motivations.

Many consumer evaluative factors increase the chances of giving WOM, including satisfaction, service quality, and perceived value with respect to the product or service ( Sweeney, Soutar, et al., 2014 ). Personal factors, such as brand familiarity, the relationship between the giver and receiver, and the self-confidence of the giver, have also been shown to have an influence. Specific motivations for giving WOM include product involvement, concern for others, seeking social approval, and venting. Hennig-Thurau, Gwinner, Walsh, and Gremler (2004) summarized this literature and extended it to eWOM through a study of consumer opinion platforms. The key motivation in terms of visiting or writing a comment on the site was social benefits, such as interacting with like-minded people, followed by positive self-enhancement and also concern for other consumers. Lovett et al. (2013) found that social motivations were key in eWOM, followed by functional factors, such as product details. Thus, the prime motivations for eWOM are not unique to eWOM but are also highly relevant to offline WOM.

Customer Referral Programs

Although customers’ intrinsic motivations are important drivers of WOM, companies increasingly regard WOM as a marketing tool to be used and managed through customer referral programs. These customer referral programs can be defined as “deliberately initiated, actively managed, continuously controlled firm activities aimed to stimulate positive word of mouth among existing customer bases” ( Garnefeld, Eggert, Helm, & Tax, 2013 , p. 17). In other words, current customers are encouraged to recommend the brand or organization to others. In a variation on these programs, some companies or marketing firms may recruit “WOM agents” specifically to make recommendations to their social networks. Generally, care is exerted to recruit people who have a passion and interest in the brand and so are genuine enthusiasts of the product or service. Their incentive is usually provided in terms of free samples of the product rather than a direct cash incentive (e.g., Carl, 2006 ). The mechanisms by which reward programs work have only recently started to be explored. For example, who should be rewarded? Does the level of reward matter? Is a customer recruited through a reward program more valuable to the organization?

Ryu and Feick (2007) investigated the difference in rewarding the existing customer for a referral (i.e., “reward me”) or the potential new customer (i.e., “reward you”), finding differences in referral outcomes as a function of tie strength. Strong ties are between individuals with a close relationship, while weak ties are between individuals who do not see each other often, such as acquaintances. Weak ties are important in the WOM process since they bridge the gap between different social groups. Ryu and Feick found that in the case of strong ties between the giver and receiver, there is a sense of caring and of the giver responding to the receiver’s need. In this context, givers are likely to be satisfied that they are helping others without expecting any reward. Hence, who receives the award is of less consequence for strong ties, though the tentative recommendation is to reward the new customer or both. In the case of weak ties, equity theory suggests the reward increases the chance of the giver making a referral since the giver views this as a favor done for the organization or new customer. Similarly, a reward increases the chance of a weaker brand (i.e., one with lower perceived quality) being recommended since weaker brand users are likely to be price-focused and to see a higher economic value from the reward—and, correspondingly, to find the reward program and making referrals more attractive. In recommending to weaker ties, consumers are more motivated by self-interest. So, a referral program targeted at the existing customer is most beneficial for weaker brands and weaker ties.

Examining how much reward should be offered, Ryu and Feick (2007) found that although offering any reward significantly increased the likelihood of a referral, there was no difference in the effect of a 10% and a 20% discount (off the given cost of an MP3 player). However, Garnefeld et al. (2013) found that a larger reward in terms of monetary value (i.e., 50 vs. 5 Euros) in the context of a telecom provider enhanced the attitudinal and behavioral loyalty of the giver. Conclusions are hard to deduce here, but possibly, the high level of reward in the case of the telecom ($50) acted as a strong, tangible signal to recommend an intangible service, as the costs to the consumer are less known or less visible than in the case of a durable good.

Value of program participants.

Managers are eager to understand the financial benefit of stimulating WOM and, in particular, the benefit from an average new customer acquired in this way. Research has begun to address the attractiveness of customers acquired through WOM. Work by Villaneueva, Yoo, and Hanssens (2008) found that different acquisition strategies attract different “qualities” of customers. Their study was conducted in the context of an Internet provider offering free Web hosting in a 70-week period. Specifically, customers acquired through traditional forms of advertising (e.g. banner ads and TV) increased short-term revenue compared to customers acquired through WOM and were 11.9% more valuable within the first 10 weeks. However, in the longer term, the reverse was true: WOM customers became more than twice as valuable. The authors attributed this to WOM customers being more likely to stay with the organization, leading to greater value over time. Schmitt, Skiera, and Van den Bulte (2011) similarly found that referred customers exhibit a higher contribution margin and retention rate and, overall, offer greater value both the short and long term.

Various reasons have been put forth as to why customers acquired through WOM are more valuable. For example, consumers recruited through standard promotional deals may be attracted for the short-term gain and then lose motivation. Schmitt et al. (2011) suggest effects driven by filtering and similarity. Specifically, the principles of triadic balance suggest that existing customers will bring in others who they believe would be a good match to the firm’s offerings; thus, existing customers act as a filter on behalf of the organization. In addition, the value of WOM-acquired customers may be due to the tendency of people to interact with people like themselves (Schmidtt et al. 2011). Existing customers are a good match to the organization by default, so others to whom they may recommend the organization are also likely to match the organization’s customer profile better than customers acquired by other means. In both cases, existing customers act as screeners for potential customers acquired through WOM, enhancing this matching process.

Given the minimal cost of WOM compared to other forms of advertising, Villanueva et al.’s (2008) study showed that the net value of a customer acquired through WOM was more than 12 times that of a customer acquired through traditional means, considering the acquisition marketing costs of the latter. Estimating the costs of acquiring a customer through various means as well as the potential net value of the customer can inform the promotion investment decisions of managers. Moreover, the “buzz” effect—that is, the exponential effect of communication across social media and the like—also should be considered. In Villanueva et al.’s study, customers acquired through WOM brought in 3.64 future customers throughout their lifetime, compared to 1.77 in the case of customers acquired through traditional marketing. For a new organization setting up, if a large volume of new customers is needed quickly, then a high acquisition budget but also a high retention budget will be needed to maintain such customers. If, however, the organization can afford to be patient in recruiting customers and can generate customers more slowly through WOM, such customers will be more profitable and cost less to maintain.

While the target of customer referral programs is typically the receiver, the actual process of recommending also seems to have a significant effect on the giver of the message. Using a field experiment in the context of prepaid cell phones, Garnefeld et al. (2013) examined the churn rate (defined as the proportion leaving the company within a given time) of existing customers participating in a customer referral program versus those who did not. They found that the churn rate of customers who became active in the customer referral program reduced over a year from 19% to 7%, while they also became more profitable to the company, with their average monthly revenue increasing by 11.4%. These findings are explained through the commitment-consistency principle in that a recommendation is a form of public commitment. Hence, a customer, having given a recommendation, would find it difficult to change his or her position and be likely to behave consistently with the expressed view.

Effects of ulterior motives.

If WOM receivers know that WOM givers are receiving financial rewards for their referrals, receivers may reasonably question if the WOM is driven by genuine care for the receiver or by the ulterior, financial incentive. Indeed, Verlegh, Ryu, Tuk, and Feick (2013) found that the receiver knowing the recommender was being rewarded led to perceptions of an ulterior motive and, subsequently, unfavorable receiver responses, particularly in the case of weak ties. However, when the receiver asks for advice, rather than receiving unsolicited WOM, this effect was attenuated. Overall, balancing the control of WOM while avoiding WOM receivers’ perceptions of givers as having ulterior motives based on self-interest is a perpetual challenge for marketers adopting WOM as a means of influencing customers.

Methods for Research on WOM

Studying offline wom.

Marketers largely view offline WOM as outside their control, since it is customer-to-customer and, at least when face-to-face, not readily observable or recordable. However, a variety of techniques have been used to determine the occurrence, or the likely occurrence, of WOM with respect to the sender and also the receiver. These include experiments, surveys, and critical incident forms.

Experiments, which are common in top-tier, experimentally oriented marketing journals, such as the Journal of Consumer Research , typically require respondents to read or view a scenario and then rate their likelihood of giving WOM as a consequence (e.g., Zhang, Feick, & Mittal, 2014 ). Experiments in WOM studies are most suited to examining the WOM receiver’s response, since the material or message given can readily be manipulated. However, as with all experiments, this approach is inherently artificial, especially in the context of WOM, which in its pure form is an organic process. Hence, concerns remain about the generalizability (i.e., external validity) of experimental results to the real world.

Surveys often do better in terms of external validity yet are necessarily retrospective or futuristic, since the WOM moment that is being reported has either passed or participants are projecting the likelihood of giving WOM in the future. In support of these methods, East et al. (2008) found that respondents reporting on hypothetical WOM impact gave results that were broadly consistent with recalled impact, supporting the use of retrospective surveys. Retrospective surveys have drawbacks, but they are a practical and inexpensive compromise when collecting data on phenomena like WOM that occur naturally ( East & Uncles, 2008 ).

A particularly useful form of retrospective survey is the critical incident form used in WOM incident recall, used, for example, by Sweeney, Soutar, et al. (2008) . In this approach, an extreme incident is recalled (i.e., when strong positive or negative WOM was given or received) and etched in the respondent’s mind through a series of initial questions. Subsequently, respondents are asked to describe various qualitative aspects of interest to the researcher, such as circumstances leading up to the event. Simple quantitative scales can be used to rate, for example, satisfaction with the incident.

Studying Online WOM

Online customer-to-customer interactions and discussions are visible to observers through media platforms and, therefore, provide readily available secondary data for WOM studies. Media and entertainment, sports, music, cars, food, toys, consumer electronics, technology and communications, travel, restaurants, beer, coffee, and many other products are widely discussed in online communities (e.g., Kozinets, 2002 ; Lovett et al., 2013 ). Such conversations offer insights into a rich, symbolic world that reflects needs, desires, and choices. Some commercial marketing agencies specializing in social media measure online WOM in terms of key factors, such as volume, sentiment, sharing, influence, and momentum (e.g., TotalSocial). Measuring and monitoring such WOM is a core business for organizations; however, such metrics also need to be researched in light of other activities or trends that may affect the impact of WOM. One important methodological direction is capturing customer-to-customer electronic communication in real time, in the relevant environment. Consumers now use social location-based services, such as Facebook’s “check in” to let friends know where they are and what they are doing, along with their experience in the context, such as with a coffee shop, art gallery, concert, or hotel ( Lucas, 2014 ). This behavior is reinforced when friends respond with a comment or a “like,” leading to a viral effect. “Likes” can also enable the service provider to share specific information, such as multimedia content. Capturing these exchanges could be extremely valuable to understanding WOM.

Given the volume of data available online, “Big Data” is increasingly used to study marketing, including the analysis of online user-generated content shared via social media sites. Big Data refers to data sets that are large or complex, requiring different means for data processing since traditional social science software may not handle data capture, storage, organization, integration, privacy, and other issues not least of which is the analysis itself. Recently, Big Data has been used in analyzing diverse topics related to WOM, such as the effect of emotions in eWOM on the stock price and trading volume of listed companies ( Kao, Shyu, & Huang, 2015 ) and the relationship between customer ratings and sales of mobile applications ( Hyrynsalmi et al., 2015 ). The consumer’s online decision-making process is no longer a linear process as customers move away from a sequence of awareness, interest, desire, and action (known as the AIDA model) toward a fluid series of steps involving forward and backward movements, in which options or alternative actions are considered and reconsidered. This iterative, multidirectional process is facilitated through the ubiquity and ease of use of online information sources. As such, a true quantitative study of the process in the context of Big Data requires complex dynamic modeling. For example, to quantify the relationship of the movie life cycle and eWOM, Liu (2006) constructed a set of log-linear models that account for (1) the dynamic relationship between daily box office revenue and WOM volume and (2) a multistage model of consumer decision making.

Given that customers, especially those recruited through WOM, generate further WOM through the network (e.g., Villanueva et al. 2008 ), understanding this iterative process is critical for marketers, yet it is clearly hard to follow how WOM travels across a network in practice. Simulation techniques lend themselves to this need. Agent-based modeling (ABM) is one of a class of computational models for simulating the actions and interactions of autonomous agents (both individuals or collective entities like organizations or groups) with a view to assessing their effects on the system as a whole ( Willenski & Rand, 2015 ). An important feature of ABM is that it is a simplified representation of a researcher’s constructed reality that evolves over time. ABMs are well suited to modeling diffusion of products and services in terms of purchase and include a range of parameters that are set by the researcher to reflect the range of different agents’ properties or attributes, such as the number of social ties, agents’ likelihood of being influenced by standard marketing activities, as well as their likelihood of influencing another actor in the network through word of mouth ( Nejad, Amini, & Sherrell, 2016 ). ABM examines the effect of such factors on a market as a whole, over multiple iterations, simulating a specific market over a period of time.

Focusing on qualitative user-generated content, netnography is becoming a well-established research methodology with which to study online communities. Netnography can be thought of as “ethnography on the Internet,” and it involves the qualitative data analysis of reflexive narratives that people publish online. This technique adapts some of the strengths of ethnographic research but is simpler and less time-consuming, largely because the data is readily available. It is arguably one of the best methods for studying the customer experience due to its immediate reporting and lack of an interviewer or observer in the reporting process. It has been applied in a variety of settings using Kozinets’s (2002) rigorous framework (e.g., Rageh, Melewar, & Woodside, 2013 ).

Future Research

As suggested by the reflections on methodology, there are many directions for research on WOM that would extend our knowledge of this fascinating and powerful form of interpersonal communication. Here, two of many are discussed briefly.

First, in the services marketing context, customers are increasingly viewed less as individual units operating alone, but rather as being integrated within systems of internal and external stakeholders, including service providers and others in the service network ( Friend & Malshe, 2016 ). This is consistent with the concept of value co-creation, defined as “benefit realized from integration of resources through activities and interactions with collaborators in the customer’s service network” ( McColl-Kennedy, Vargo, Dagger, Sweeney, & van Kasteren, 2012 , p. 370). This highlights the potential role of both the service provider and other actors in the network as influences on WOM. Specifically, research questions include the role of customer-facing employees in developing positive WOM, compared to the role of the brand or the organization, and their influence in moderating the development of negative WOM. Further, what is the impact of others in the network, such as suppliers or government agencies?

Second, customers have experiences each time they “touch” any element of the organization, such as the product, service, or brand. This can be across different channels and need not be restricted to face-to-face interactions. Touchpoints can also be experienced at different times across the service process. Touch points include “touching” the servicescape, technology, promotion, product elements, and customer interactions with the service provider or other customers ( Stein & Ramaseshan, 2016 ). Escalating managerial interest in experiences and touch points suggests research questions about their effect on WOM. For example, what effect do “social location-based” services such as Facebook’s “check in” have on WOM? And given the rise of “bots” that automate conversations between users and businesses (i.e., business to customer), what effect does interaction with a bot have on consumers production of and response to WOM?

Best Practices for WOM

Scholarship on WOM suggests a set of best practices for companies seeking to maximize its benefits. Turning first to myths discussed earlier in this chapter, marketing practitioners will be reassured that contrary to Myths 1 and 2, WOM is not the exclusive domain of opinion leaders but rather engages all consumers (e.g., Watt & Dodds, 2007 ) and, further, is relevant to all products and services, but particularly those that are associated with a good story, evoke interest, arouse emotion, and offer useful information ( Chen & Berger 2016 ). Indeed, good stories are not limited to fashionable, youth-oriented products and services (e.g., Keller & Fay, 2009 ). Moreover, contrary to Myth 3, positive WOM is both more common and has a greater impact on outcomes, such as change in purchase likelihood, than negative WOM ( East et al., 2008 ). Hence, not only is negative WOM not as impactful, but when negative WOM does occur, it is not always detrimental (contrary to Myth 4). For example, negative WOM can simply serve to increase brand awareness or can have a “boomerang effect” due to reactance in the receiver (e.g., Reimer & Benkenstein, 2016 ), Finally, WOM, while a powerful means of communication, does not make traditional forms of promotion redundant; indeed, both can work synergistically, reinforcing each other in the longer term, contrary to Myth 5 (e.g., Hogan et al., 2004 ). Thus, one best practice is a healthy skepticism about previous commonly accepted limitations of WOM. However, many challenges still remain for this important and powerful form of promotion, as evident in the trends in organizations’ management of WOM and other forms of promotion.

Brand communication (brand to consumer) has traditionally been one-to-many promotion, such as TV advertising, although one-to-one communication (e.g. direct mail, a personalized email, or Twitter communication) also has a role. WOM communication (consumer to consumer) has traditionally been one-to-one (e.g., face-to-face), yet new one-to-many channels have emerged (e.g., social media). Thus, WOM can complement brand-to-consumer communication in several ways. Often, however, organizations do not have a clear strategy in mind; hence, their promotion efforts are fragmented. Typically, an organization’s promotion budget focuses on traditional media. Yet WOM is not rooted in the marketing of a particular organization, brand, product, or service but in everyday relationships, conversations, and relevant activities of people discussing a variety of matters. Thus, the “vehicle” is naturally occurring events that generate naturally occurring conversation (International WOM Marketing Conference, 2005). Offline conversations may occur in our kitchens and, living rooms, at churches and sporting events, or around the coffee machine at work. Consumer-generated conversations, of course, can occur online, but online conversations tend to be deliberative—for example, commenting on a particular product or topic such as travel (e.g., TripAdvisor) or in P2P (i.e., patient-to-patient) communities such as Cancer Connections ( https://onlinecommunity.cancercouncil.com.au/ ). In their daily lives, consumers are not always looking for or thinking of specific goods or services, suggesting that marketers need to be where the audiences are, rather than expecting audiences to come to them (Marketing in the Digital Age Webinar, 2014). Therefore, the most successful future business model is likely to focus on people, rather than on technology, as the core of the communication strategy.

The emphasis of firms’ efforts in generating WOM should be on exciting the current base of customers to give them something new to “evangelize” about. WOM disseminates naturally when the “vehicle” is interesting. This can involve catchy ideas associated with everyday conversation. For example, Jeep, the four-wheel drive manufacturer, offers a Jeep Jamboree weekend each year to established customers and new customers. The discussion of Jeeps at such an event is not surprising, as veterans pass on their experience to “newbies,” and attendees later talk to others about the fun time and pass on positive WOM about the brand ( McAlexander, Schouten, & Koenig, 2002 ). Marketers should “mix and match” communication options to build brand equity—that is, choose a variety of different communication options that share common meaning and content but also offer different, complementary advantages so that the whole is greater than the sum of the parts ( Keller, 2009 ). For example, continuing with the Jeep example above, traditional TV advertising may be used to create interest in a new model Jeep, while YouTube videos, a website, and the Jamboree may continue and embellish the theme, the latter offering strong experiential support. A personal story may be developed in this process, particularly with the Jamboree or the YouTube video, leading to WOM.

The constantly evolving nature of WOM communication and the availability of large amounts of online data such as social media sites and new tools available to measure and monitor WOM demand that marketing managers reconsider their brand communication strategies. A starting point in planning communications strategy is an audit of the potential interactions a customer in the target market may have with the organization and its products and services ( Keller, 2009 ). In the Jeep example, the potential customer might see the TV ad, talk to other four-wheel drive owners, view the manufacturer’s website, and attend the Jamboree as a spectator, or some a combination of these. Knowledge of this sequence would help Jeep understand the experiences of such a consumer and be better able to tailor its promotions, including allocation of the promotion budget for different sequence stages.

WOM is one of the most powerful influences on consumption and has significant potential to influence consumer behavior. This is especially true given the move from the goods-dominant logic of marketing, reflecting largely a selling and goods focus and where the concept of exchange dominates, to a service-dominant logic, where the focus is on how customers integrate their own and other parties’ resources to create value for themselves and become engaged in the service process ( Skålén, Aal, & Edvardsson, 2015 ). The focus on the customer’s active role and importance in the service network, including other consumers in this new paradigm, highlights the important role of WOM and eWOM in the future of marketing.

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The current state of research of word-of-mouth in the health care sector

• Original Article
• Open access
• Published: 08 February 2022
• Volume 20 , pages 125–148, ( 2023 )

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• Gerlinde Pauli   ORCID: orcid.org/0000-0003-2894-193X 1 ,
• Sebastian Martin 1 &
• Dorothea Greiling 2  

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Health information plays a significant role in the health behavior of individuals. Word-of-mouth (WOM) is essential in this context. In recent years, new forms of online communication have greatly expanded the possibilities for seeking information and, in consequence, significantly changed communication behavior. Similarly, the doctor-patient relationship has gradually evolved and the traditional asymmetry of medical knowledge is increasingly being corrected as today’s health care consumers are becoming more well-informed. A key source of information is either in-person or online WOM. A research gap exists in terms of analyzing the current state of research of WOM in health care. Although various studies highlight the influence of WOM on health behavior, to the best of our knowledge there exists no systematic literature review that summarizes the current state of research on WOM in health care. Therefore, this paper presents a comprehensive systematic literature review on WOM in health care. The literature review investigates existing WOM studies in the health care sector based on a systematic search for articles in a twenty-year timeframe from January 2000 to December 2019. The resulting total of 34 articles constitutes the basis of this paper. These studies are analyzed using a model of WOM in health care and – based on the theory of cognitive dissonance, the theory of the strength of weak ties, and the theory of perceived risk – clustered into the creation, spread, and impact of WOM. The investigated studies emphasize the importance of the staff in the service process. Furthermore, negative reviews have a stronger impact than positive ones, with service quality representing the main reason for negative WOM. In addition, the importance of electronic word-of-mouth (eWOM) is underlined, as online reviews are gaining popularity for patient decision-making processes. Although some studies have addressed WOM in health care, research gaps remain. For example, there are few studies on eWOM and some medical disciplines in private practice are neglected in WOM research. By systematically presenting and analyzing the literature on WOM in health care, this paper represents an important starting point for future research and also provides insights into the role of WOM in health care practice.

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1 Introduction

Health information plays a significant role in the health behavior of individuals. Patients increasingly want to have an active say in the choice of their physician and the treatment methods they choose (Dobele & Lindgreen, 2011 ; Liang & Scammon, 2011 ). However, such co-determination is only possible on the basis of sufficient information. Because the actual medical service is difficult for patients to assess, there is a growing demand for simple medical information they can understand (Argan, 2012 , 2016 ; Martin, 2017b ). In addition, the doctor-patient relationship has gradually evolved. The traditional asymmetry of medical knowledge is increasingly being corrected as today’s health care consumers are becoming well-informed (Loane & D’Allesandro, 2014 ). New forms of online communication have greatly expanded information-seeking options in recent years, significantly changing communication behavior (Cao et al., 2017 ; Drevs & Hinz, 2014 ; Gheorghe & Liao, 2012 ; Hinz et al., 2012 ; Liang & Scammon, 2011 ; Lin & Lin, 2018 ).

A key source of information is either in-person or online word-of-mouth (WOM), which is the noncommercial recommendations of individuals who have already used the health care service (Argan, 2012 , 2016 ; Dobele & Lindgreen, 2011 ; Martin, 2017b ). Patients draw on information from family members, friends, relatives, neighbors, or coworkers as a basis for choosing a new physician (Argan, 2016 ). It is important to keep in mind that when information is disseminated through WOM, there is a risk of misinterpretation or reinterpretation (Liberatore et al., 2019 ). The dissemination of information through social networks multiplies the number of recipients exponentially.

Although various studies highlight the influence of WOM on health behavior (Argan, 2012 , 2016 ; Drevs & Hinz, 2014 ; Ferguson et al., 2008 ; Hinz et al., 2012 ; Liang & Scammon, 2011 ; Martin, 2017b ), to the best of our knowledge there exists no systematic literature review that summarizes the current state of research on WOM in health care. A literature analysis on WOM in health care was published in 2017 (Martin, 2017a ), based on a research timeframe from 2005 to 2015. Since the literature analysis by Martin was explorative and did not systematically use prestigious databases, and the most recent studies it included are from 2015, an up-to-date literature review seems necessary to investigate the current state of research. Therefore, this paper investigates existing WOM and eWOM studies in the health care sector within a systematic literature review. This study aims to:

systematically compile the literature on WOM in health care and provide a current overview of studies in this research field

identify factors that influence WOM

reveal potential gaps in WOM research.

A study by Martin ( 2017b ) proposes a model of word-of-mouth in the health care sector. Since the model categorizes the different dimensions of WOM as well as influencing factors in the context of the health care sector, it serves as an anchor in this research field and is used to systematize the literature under review.

To answer the research objectives, the article proceeds as follows: following the introduction (section 1), section 2 describes the conceptual framework of the literature review. In this context, the model of WOM in health care is discussed. Section 3 illustrates the methodological approach. Section 4 presents the empirical findings of the review, clustering the results with respect to creation, spread, and impact of WOM. Section 5 presents the discussion, and section 6 outlines the conclusion and further research.

2 Conceptual framework

In the current literature review, an article by Martin ( 2017b ) warrants special attention. He presents a model of WOM in health care founded on three scientifically based theories: the ‘theory of cognitive dissonance’, the ‘theory of the strength of weak ties’, and the ‘theory of the perceived risk’. These scientific theories can be applied to WOM-related aspects in general and are not specifically related to the health care sector. Nevertheless, all three theories include various aspects that explain the creation, spread, or impact of WOM.

2.1 Relevant theories

The theory of cognitive dissonance describes psychological aspects that can be used to explain the creation of WOM (Festinger, 1957 ). According to this theory, every person has specific cognitive elements, opinions, and past behavior. When one cognitive element follows logically from another, they are said to be consonant to each other. They are dissonant to each other, when one does not logically follow from the other (Oshikawa, 1969 ). Dissonance can be reduced by attitude change, selective exposure, and WOM. Recommending a particular product or service to others and gaining their purchase support helps to convince actual consumers of their decision (O’Neill & Palmer, 2004 ; Wangenheim, 2005 ). Referring to health care, this means that if the chosen product or service is ranked as the best alternative, individuals may recommend health care providers or services in order to reduce or avoid cognitive dissonances (De Matos & Rossi, 2008 ). Further, WOM senders may recommend a health care provider or treatment because of uncertainty, in order to convince themselves of their own decision (O’Neill & Palmer, 2004 ; Wangenheim, 2005 ).

The theory of the strength of weak ties focuses on the spread and impact of information, emphasizing the strength of ties in interpersonal networks (Granovetter, 1973 ). Weak ties have a higher reach of information and recommendations, whereas strong ties have a lower reach but trust in information is higher (Brown & Reingen, 1987 ). Strong ties often exist between family members, close friends, or even good colleagues, while weak ties describe the relationship between acquaintances (Buchanan, 2002 ). Individuals form network clusters which are connected by strong and weak ties. In particular, individuals connected by strong ties are likely to engage in the same clusters. Weak ties connect different clusters, enabling cross-group information exchange (Granovetter, 1973 ). Weak ties are critical to the flow of recommendations across clusters. WOM spread by strong ties, on the other hand, is more likely to influence behavior, such as the use of a particular health service (Brown & Reingen, 1987 ).

In addition to Granovetter’s theory of the strength of weak ties, the theory of perceived risk by Bauer ( 1967 ) and Cox ( 1967 ) adds important aspects that help to understand the information sought by WOM and its implications. Perceived risk theory states that the degree of uncertainty plays a role in most purchases of services or goods (Bauer, 1967 ; Cox, 1967 ). Perceived risk is a key aspect of consumer behavior that strongly influences decision making (Bauer, 1967 ; Bettman, 1973 ; Cox, 1967 ; Gemünden, 1985 ; Taylor, 1974 ; Zhang et al., 2012 ). When perceived risk exceeds the subjective tolerance level, an individual is motivated to develop a risk reduction strategy (Bauer, 1967 ; Cox, 1967 ; Gemünden, 1985 ; Sheth & Parvatiyar, 1995 ). Such strategies may focus on limiting potential negative consequences or reducing uncertainty about the likelihood of such consequences. Strategies for reducing uncertainty include searching for, processing, and storing information (Gemünden, 1985 ). Relevant information can be obtained, inter alia, through the advice of family and friends. Therefore, WOM communication provides a common strategy for reducing perceived risk (Cox, 1967 ; Nießing, 2007 ; Roselius, 1971 ; Sheth & Parvatiyar, 1995 ).

2.2 WOM model in health care

Martin ( 2017b ) defines three dimensions in his WOM model that can be clustered as the creation, spread, and impact of WOM. With respect to creation, WOM senders can either be patients or family, relatives, friends, and acquaintances. Influencing factors of WOM creation can be clustered into medical factors and atmospheric factors as well as provider, sender, and admission characteristics, whereas the health care provider can only influence medical and atmospheric factors directly. Motives for the spread of WOM can be altruistic or egoistic. Communication by WOM depends on content, channel, anonymity, and network structure. In the dimension of impact, WOM may affect the individual’s knowledge, emotion, and behavior. The degree of such influence might depend on receiver characteristics. The theory of cognitive dissonance relates to the dimension of creation, because it describes psychological aspects that can be used to explain the creation of WOM. The theory of the strength of weak ties relates to the dimension of spread, since the strength of ties impacts the spread of information. However, it also relates to the dimension of impact, since WOM spread by strong ties is more likely to influence the behavior of WOM receivers. Especially concerning one’s own health, risk reduction plays a significant role. Individuals might share information about health services to reduce uncertainty. Therefore, the theory of perceived risk mainly pertains to the dimension of impact. In addition, the theory also relates to the dimension of spread, as relevant information is sought through different communication channels.

Since the model outlines more or less the entire process of WOM communication in the health care sector, it serves as a basis for systematizing the articles covered in this literature review. The model proposed by Martin was published in 2017 and is based on a literature analysis from 2005 to 2015. To the best of our knowledge, there exist no further literature reviews regarding the state of research on this topic. Figure 1 shows the model of WOM in the health care sector in Martin ( 2017b ).

Source: Martin, 2017b

A model of word-of-mouth in the health care sector.

3 Methodological approach

To gain a deeper understanding of WOM in health care, the following literature review investigates existing WOM studies in the health care sector based on a systematic search for articles in a twenty-year timeframe, from January 2000 to December 2019. WOM and eWOM articles are considered and analysed to get a more holistic view of word-of-mouth in a health care setting. In our model, various aspects concerning face-to-face and online WOM are added and compared, further differences identified. Therefore, the revised model of word-of-mouth in the health care sector provides a general overview of (electronic) WOM in the health care sector and indicates important aspects which need to be considered concerning the creation, spread and impact of both face-to-face as well as electronic WOM. We recognize that there are differences between WOM and eWOM, which need to be more closely considered in further research. We added this aspect to the limitations of this study. Nevertheless, we believe that WOM might frequently also appear in a combination of face-to-face and electronic recommendations. In this way, a holistic model for both face-to-face WOM as well as electronic WOM seems to be beneficial. With our study we suggest such a model that summarizes the state of art of WOM research and can be used as a scientific anker for future research. With respect to a broad field of marketing papers concerning WOM, only papers focusing on the health care sector were included in the literature review. The research databases EBSCOhost Business Source Premier and ScienceDirect were used to identify potentially relevant articles related to WOM and health care. The exact search string used was: (“word-of-mouth” OR “word of mouth” OR “WOM” OR “eWOM”) AND (“*health*” OR “clinic” OR “hospital” OR “emergency room” OR “*physician*” OR “*medical*”) in the fields “Title”, “Abstract” or “Author-specified keywords”. Only research articles in scholarly (peer-reviewed) journals were included in the literature search. The result of this advanced search was a total of 161 articles: 90 articles in the EBSCOhost database and 71 articles in the ScienceDirect database. All 161 articles were carefully read. Articles that did not address WOM and health care were excluded, as were non-academic articles with no scientific sources, like editorials. The remaining number of papers was 26 (first level). Furthermore, if the references of the selected articles contained the wording WOM and health care in the title, these articles were also included in the analysis. Eight additional articles were added (second level). A total number of 34 articles form the basis of the literature analysis. Figure 2 summarizes the review process.

Source: Own compilation

The process of the systematic literature review.

4 Empirical findings

4.1 general findings.

On the first level of journals, 26 articles concerning WOM in health care were identified by the authors. On the second level, an additional eight articles were included. Therefore, this research paper is based on a literature review of a total of 34 studies focusing on WOM in the health care sector. Regarding the methodology applied, most studies carried out surveys (n=14), followed by interviews (n=6). Four studies completed both surveys and interviews (n=4), and one study carried out a mix of survey, interview, and content analysis (n=1). A literature review was done by two studies (n=2), of which one literature review focused on leading scientific journals regarding WOM in health care, and one literature analysis dealt with buzz marketing related to antibiotic medication. Further, online reviews (n=2), messages, e.g., on social networking sites, forums and blogs (n=2) and websites (n=1) were analyzed. Additionally, one study completed both an online review and a survey (n=1), and one study carried out a survey comparing two studies (n=1). Concerning the WOM content/area, ten studies paid attention to hospitals, seven to outpatient care, and four to both inpatient and outpatient areas. Regarding outpatient care, studies focused on health care professionals for children, osteopaths, pharmacies, blood donation facilities, members of an obesity group, gay health centers, pregnant women, and mothers who had given birth. Some studies did not focus on a specific institution, area or group. Instead, these research articles focused on health behaviors and specific health illnesses/conditions (n=5). With respect to the country focus, most of the studies were conducted in Asia (n=13); both North America and Europe were studies in eight studies, while one study investigated South America and one Australia. Three studies focused on several countries. Regarding the channels of communication, 20 studies dealt with WOM and 13 studies with eWOM. One study addressed both WOM and eWOM. In addition, inasmuch as whether WOM is positive or negative may have a different influence of the creation, spread, and impact of WOM, the WOM type was considered, too. Six studies dealt with positive WOM, three studies dealt with negative WOM, and another six studies with both positive and negative WOM. All other studies used no further specification concerning the WOM type. Since Martin ( 2017b ) already carefully developed and clustered the dimensions of WOM in health care in his model, this clustering is adopted in the present article. With respect to the WOM dimensions, 20 studies were identified as related to WOM creation, five studies addressed WOM spread, and eleven studies addressed the WOM impact; only the study by Martin ( 2017b ) pertained to all three dimensions, i.e., creation, spread, and impact. In the case of articles relating to several dimensions, the respective article was assigned to the more significant dimension. Based on current literature, the authors give the following overview of research on WOM in health care, shown in Table 1 .

4.2 Creation of WOM

The creation dimension of WOM is explored by 20 articles. Five of these focus especially on eWOM. Eight studies were carried out in Asia, five in Europe, five in North America, and one in South America. In the study by Martin, WOM articles in health care are considered worldwide. The results of the literature analysis regarding the dimension of creation are summarized in Table 2 .

A research study by Pentescu et al. ( 2014 ) investigated modelling patient satisfaction in healthcare, which is important for WOM. This study identifies the perceived quality of the provided healthcare services, services’ rates, and personal factors as determinants of patient satisfaction and highlights the influence of patient satisfaction on patient loyalty, compliance with treatment, and the influence on positive WOM. Cheng et al. ( 2003 ) emphasize that interpersonal skills are equally or even more influential on patient satisfaction than clinical competence, and that technical competence is important for recommendations of patients. Further, the findings imply that a high degree of patient satisfaction in a hospital does not necessarily mean a high rate of recommendation. With regard to patient loyalty and positive WOM, both patients’ overall satisfaction and hospital personnel satisfaction are important, indicating that “high levels of satisfaction are required to create true ambassadors of a service organization” (Ferguson et al., 2008 , p. 60). To underline the importance of the staff, Chaniotakis and Lymperopoulos ( 2009 , p. 238) conclude that “in order to exploit the opportunities for having satisfied customers and creating positive word of mouth communications, they [practitioners] have to understand the importance of the staff in the service process”. Patient loyalty is linked to employee satisfaction and also influences the recruiting of new patients and new employees. Henthorne et al. ( 2009 ) emphasize that recommendations lead to preliminary loyalty, but only until patients make their own experiences.

Based on the model of WOM in the health care sector, Martin ( 2017b ) defines medical factors, atmospheric factors, provider characteristics, sender characteristics and admission characteristics as influencing factors for the WOM sender. According to this classification, the following medical factors are confirmed by this literature analysis: qualification of physicians (Bishop et al., 2013 ), perceived quality (Kemp et al., 2014 ; Pentescu et al., 2014 ; Tu & Lauer, 2008 ), perceived competence, and perceived credibility (Mannan et al., 2019 ), service quality (Cao et al., 2017 ; Mannan et al., 2019 ; Sivakumar & Srinivasan, 2010 ), interpersonal skills (Cheng et al., 2003 ), and customer-oriented behavior (Kemp et al., 2014 ). Investigating hospitals, Sivakumar & Srinivasan ( 2010 ) point out that the reliability and assurance of the service quality mainly influence the behavioral outcomes of patients.

Focusing on positive WOM for maternities, Chaniotakis and Lymperopoulos ( 2009 ) found that, besides satisfaction, empathy is the only service quality dimension which directly affects WOM. “In addition, ‘empathy’ affects ‘responsiveness’, ‘assurance’ and ‘tangibles’ which in turn have only an indirect effect to WOM through ‘satisfaction’” (Chaniotakis and Lymperopoulos, 2009 , p. 229). In contrast, Kitapci et al. ( 2014 ) demonstrate that empathy and assurance are important antecedents of satisfaction, and satisfaction also interrelates with WOM communication and repurchase. Regarding provider characteristics, technical skills (Cheng et al., 2003 ), website quality (Mannan et al., 2019 ), price (Pentescu et al., 2014 ; Tu & Lauer, 2008 ), communication style and consultation time (Mehra, 2018 ), and provider referrals (Gombeski et al., 2015 ) are factors influencing WOM.

As admission characteristics, convenience factors including waiting time for appointments and location (Tu & Lauer, 2008 ) are identified. In addition, satisfaction with hospital admissions depends on whether the hospital was chosen by patients chose themselves or patients’ agents (Drevs & Hinz, 2014 ). A health care provider is able to directly influence the medical and atmospheric factors, whereas the provider, sender, and admission characteristics can be influenced only partially or not at all (Drevs & Hinz, 2014 ). Trust (Kemp et al., 2014 ), disease knowledge and disease risk for online physician selection (Cao et al., 2017 ), first impressions (Bishop et al., 2013 ; Gombeski et al., 2015 ), and the disconfirmation of expectations (Kucukarslan & Nadkarni, 2008 ) are characteristics that influence the provision of WOM.

Focusing on eWOM, Lin and Lin ( 2018 ) investigate the demand for online platforms for medical WOM and found that sender characteristics like gender, age, educational level, and occupation group impact the likelihood of recommendations of an online evaluation platform. For instance, women are more willing to recommend a platform, and satisfaction with platforms decreases with age. Price perception, eHealth literacy, quality of reviews on social media and websites as well as website quality (Mannan et al., 2019 ) are important factors influencing the willingness to make use of online health services. Da Silva Terres et al. ( 2014 ) investigated antecedents of clients’ trust in low- and high-consequence decisions. They found that in high-consequence decisions affective aspects - such as emotions, care, concern, and attention - have a greater impact on consumer trust, whereas cognitive aspects – such as competence, efficiency, and effectiveness - have a greater impact on consumer trust in low-consequence decisions. Further, the more acute the consequences are, the greater is the impact of trust on positive WOM.

Motives cannot be clearly assigned to the creation and spread of WOM. Based on the current literature, Liberatore et al. ( 2019 ) deduced self-enhancement/-affirmation, altruism, social comparison, the need to belong, and information-sharing as social drivers for WOM in the context of public health campaigns. Hinz et al. ( 2012 , p. 18) investigated reviews on an online platform for hospital reviews and highlight that “altruistic motives override egoistic motives”. Moreover, the study shows that the reviews are more often positive than negative, but negative reviews include more detailed information on medical processes and care. In this way, motives and characteristics influence not only the reason a review is written, but also the content of the review. Helping or warning other patients is more important to reviewers than expressing positive or negative feelings, for both positive and negative experiences (Hinz et al., 2012 ). In addition, there are immense differences between the WOM of patients and their relatives (Drevs & Hinz, 2014 ). The positive result of a review is influenced by whether patients have chosen a hospital themselves or not. Other-directed patients are more likely to write negative online reviews than those who chose a hospital themselves (Drevs & Hinz, 2014 ).

4.3 Spread of WOM

The spread dimension of WOM is explored by two European, one North American, one Asian, one cross-national study between USA, Canada, UK, New Zealand, and Australia, and one worldwide study. Two studies focus on eWOM. In comparison to the other WOM dimensions, only a few studies deal with the spread dimension. A special focus of these studies is on the spread of health information. The results are summarized in Table 3 .

Um and Lau ( 2018 ) focus on dissatisfied patients and identify outcome quality, administrative quality, interaction quality, and environmental quality as factors influencing patient dissatisfaction, noting that service quality attributes mainly lead to dissatisfied patients and negative behaviors. Dissatisfied patients tend to be more active in negative WOM, complaining or switching to another health care provider. Lockie et al. ( 2015 ) underline the importance of better understanding the role of online reviews in patient decision-making processes, because they are gaining popularity in health services. Focusing on online reviews for general practitioners, the overall content is more important to readers than only the valence or rating of a review, and reviews with a more narrative and experiential style are perceived as more useful than very short or more fact-based reviews. Identifying and cultivating opinion leaders can help to increase WOM about a new product or service (Holdford, 2004 ). WOM works best when patients perceive benefits of an innovation, e.g., a clear vision of consequences of an innovation. In contrast, sponsored eWOM communications are not as effective because they lead to bias of customers (Kareklas et al., 2015 ). For the spread of public health campaigns, citizen co-creation can be an important and cost-effective tool (Liberatore et al., 2019 ).

4.4 Impact of WOM

The impact dimension of WOM is explored by eleven articles. The majority of the articles, namely four studies, were carried out in Asia, two in North America, two in Europe, one in Australia, one cross-national study was done between Austria, Belgium, and the UK, and in the study by Martin WOM articles in health care were considered worldwide. Five of the studies focus especially on eWOM. The results regarding the impact dimension are summarized in Table 4 .

Gheorghe and Liao ( 2012 ) examined the content of messages in an online gynecological community forum and emphasize that negative eWOM postings have a stronger impact linguistically than positive postings. Reasons for posting negative messages are often negative emotions like frustration, anger, uncertainty, disappointment, and sadness (Gheorghe & Liao, 2012 ; Lee & Wu, 2015 ). Venting, searching for advice, helping the receiver, and seeking revenge are identified by Lee and Wu ( 2015 ) as negative eWOM measures. Argan ( 2012 ) point out that three WOM dimensions tie strength and relationship, health knowledge and experience, and similarity and preference awareness directly and indirectly influence the satisfaction, encouragement, and discouragement of patients when selecting a physician.

WOM referrals are used by consumers to choose physician services. Communication skill, expertise, reputation and success, and institutional facilities influence patient satisfaction and “the relationships between physicians and patients have an indirect effect on potential patients” (Argan, 2012 , p. 191). To encourage the willingness to donate blood, WOM can help promote recommendations from blood donors and establish direct contact with potential donors (Tscheulin & Lindemeier, 2005 ). Dobele and Lindgreen ( 2011 ) investigated the consumer value in health care in the context of new mothers and identified the discussed value (including the quality of the experience, the friendliness and expertise of the staff, and the source credibility) as influencing factors. In addition, referrals are seen as supporting or confirming information, understanding options and reducing the anxiety and time spent for searching for information.

Regarding eWOM, patients have opportunities to gain and provide information and experience anonymously, twenty-four-seven and tailored to personal needs. It is not only the message that influences patients’ responses, but the reactions by commenters play an even more important role, and comments from experts have a greater impact on attitude and behavioral intention (Kareklas et al., 2015 ). Online comments influence purchase intentions, too (Lee et al., 2014 ). Beside informational support, online websites, forums or blogs can also give emotional support to support seekers (Liang & Scammon, 2011 ). In addition, through online support groups especially for chronic diseases, patients become educated and empowered health consumers and are able to act on a partnership level with the doctor, which may change the patient-doctor-relationship (Loane & D’Allesandro, 2014 ).

5 Discussion

The present literature review analyzes 34 WOM studies that focus on health care in a twenty-year timeframe. Most of the studies were conducted in Asia. Eight studies focused on hospitals, seven studies on physicians, seven on other health care providers, and six studies on online communities. Six other studies do not clearly identify the focus group. In terms of the WOM dimensions distinguished by Martin ( 2017b ), the creation dimension is the most researched category, followed by the impact dimension. Only five studies deal with the spread of WOM. Another clustering criterion is the focus on positive or negative WOM. This is a new aspect, which is not included in Martin’s research. The present literature review therefore explores possible differences between positive and negative WOM communication. Only about a third of the studies specify whether the focus is on positive or negative WOM. All studies regarding positive WOM concern the creation dimension, and all studies concerning negative WOM address in the impact dimension, excepting one study that focused on negative WOM in the spread dimension. Therefore, a direct comparison between positive and negative WOM within the dimensions is not possible. Nevertheless, this aspect is included in the model.

The importance of the staff in the service process is not only relevant for satisfied patients, patient loyalty, and creating positive WOM, but also for recruiting new patients and new employees (Ferguson et al., 2008 ; Chaniotakis & Lymperopoulos, 2009 ). In order to more actively use WOM for a service organization, the goal should be to create ambassadors, whereas caution is advised for sponsored WOM, as this is less effective and can quickly bring negative effects (Ferguson et al., 2008 ; Kareklas et al., 2015 ). The theory of the strength of weak ties implies that individuals form network clusters connected by strong and weak ties, with weak ties enabling a cross-group information exchange across different clusters (Granovetter, 1973 ; Brown & Reingen, 1987 ). Health care workers or the patients could act as ambassadors that spread their positive impressions of the health care service among their clusters of family, friends and acquaintances, through such strong and weak ties.

The differences between paid and unpaid WOM are not illustrated in Martin’s model of WOM in health care, which could be considered in the spread dimension. Further, negative reviews have a stronger impact than positive ones and include more detailed information on medical processes and care (Gheorghe & Liao, 2012 ; Hinz et al., 2012 ). The main reason for dissatisfied patients and negative behaviors, such as negative WOM, complaining or switching to another health care provider, is service quality, while empathy, reliability, and assurance of service quality can positively influence the behavioral outcomes of the patients (Chaniotakis & Lymperopoulos, 2009 ; Sivakumar & Srinivasan, 2010 ; Um & Lau, 2018 ). Drawing on the theory of cognitive dissonance, Festinger ( 1957 ) argues that dissonance can be reduced through attitude change, selective exposure, and WOM. This includes WOM about health care services and provides.

Most eWOM studies were conducted in the last six years. Online reviews are gaining popularity for patient decision-making processes, and patients are becoming educated and empowered health consumes, which may lead to a challenge in the patient-doctor-relationship. Therefore, it is important to better understand the role of online reviews (Loane & D’Allesandro, 2014 ; Lockie et al., 2015 ). For readers, the content of a review is more important than an isolated rating, and reactions from commenters play an even more important role (Kareklas et al., 2015 ; Lockie et al., 2015 ). Beside informational support, internet-based communication can also provide emotional help to support seekers (Liang & Scammon, 2011 ). In terms of the theory of perceived risk, patients seek health information from family, friends, or online to reduce their perceived risk. In comparison to WOM, information and experiences in eWOM are anonymous and available twenty-four-seven. Furthermore, eWOM communication usually involves multiple participants. Thus, trust and credibility play an even more significant role. Martin’s literature review, used here as basis for the model of WOM in health care, includes only six eWOM studies. The WOM model in health care also applies well to eWOM, although the fact that multiple participants communicate with each other could be represented better. Furthermore, in addition to trust, credibility is equally important.

Because the studies on which Martin’s model of WOM in health care is based have a strong focus on hospital recommendations, attention is paid to whether there are differences in WOM between inpatient and outpatient areas. In this literature review, all eight studies focusing on hospitals are in the creation dimension. However, no significant differences between inpatient and outpatient areas were found.

By analyzing in-depth the results of the literature review in the context of Martin’s model, most of the aspects are already included in the WOM model. However, the current literature identified some additional factors that should be added; these are presented in a revised version of the model in Figure 3 . Concerning the WOM sender, Martin distinguishes directly and indirectly affected senders. The directly affected sender refers to the actual patient, whereas the indirect senders are family, relatives, friends, and acquaintances who witnessed the health service. In addition to Martin’s account, staff is also an indirectly affected WOM sender; especially in terms of eWOM, review writers and commenters are also indirectly involved in the decision-making process and should not be underestimated.

A revised model of word-of-mouth in the health care sector (based on Martin 2017b )

In relation to the differentiation between sponsored and unpaid WOM, a distinction must be made, particularly with regard to eWOM. Sponsored WOM can quickly bring negative effects. The aspect ‘paid’ versus ‘earned’ content is outlined in the content attribute. The distinction between face-to-face and eWOM communication is included in the channel. Beside the anonymity and the network structure, the availability of information is also an important factor in the spread of WOM, and a distinction can be made here between short-term and long-term availability. Furthermore, no differentiation between positive and negative WOM could be made in the literature review, thus no results are included in the state-of-the-art model. Nevertheless, the distinction between positive and negative WOM is important and therefore taken into consideration in the revised model. In addition, credibility is just as important as trust for the WOM receiver, as shown in the revised model in Figure 3 .

Based on the literature review, the authors conclude that the simplified representation of WOM sender, WOM communication, and WOM receiver is the same for all forms of communication. However, especially with the increasing importance of eWOM, communication takes place more frequently online, usually involving more people in the communication process than in face-to-face conversations. Hence, the bar “bidirectional/multidirectional communication” illustrates the involvement of multiple discussion partners throughout the communication process. To further illustrate the differences in WOM and eWOM communication, the distinction between one-to-one, one-to-many and many-to-many communication is depicted separately in the figure. Figure 3 represents the revised version of the model of word-of-mouth in the health care sector.

6 Limitations

Based on the recent literature, the paper investigates the importance of WOM in health care and provides a revised model of word-of-mouth in the health care sector, including new aspects such as the clustering criterion on positive and negative WOM, the difference between paid and unpaid WOM and the clustering on short-term and long-term WOM effects, compared to the original model from Martin ( 2017b ). Nevertheless, the presented paper has some limitations. First of all, the applied theories do not have exclusive validity for the health care sector, but only describe WOM-related aspects in general. Furthermore, the results are based on a literature review of 34 articles on WOM with a specific focus on the health care sector. Therefore, this study may neglect WOM articles from other disciplines, such as retail. In addition, only the databases EBSCOhost Business Source Premier and ScienceDirect were used for the literature review. Databases such as PubMed or Medline were not part of the study and could provide further valuable input as they are specialized in collecting information in the health care field. Another limitation is that the paper presents WOM and eWOM in a combined model. To further validate both research streams and illustrate the differences even more, face-to-face and electronic word-of-mouth could additionally be considered separately in future studies.

7 Conclusion and further research

To the best of our knowledge, there exist no up-to-date literature reviews focusing on the state of WOM research in the health care sector. To provide an overview of the recent literature, the paper investigates the importance of WOM in the health care sector. Further, the importance of future research on this topic is outlined. Martin’s approach regarding the classification of the articles in terms of creation, spread, and impact dimensions is supported. With respect to the investigated articles and databases, this research is necessarily limited. The literature review identified 34 articles related to WOM and health care. Most of the studies concern the creation and impact of WOM, and only a few studies deal with the spread of WOM. Compared to the WOM content, the allocation between hospitals, physicians, health care providers, online communities, and others is rather balanced.

Nevertheless, several research gaps remain. For example, it is noteworthy that not a single study explicitly deals with prevention, despite the increasing importance of preventive health care. Because of this major research gap, WOM in preventive health care represents a future field of research. In addition, although a reasonable number of studies address WOM and eWOM, there are still fewer studies on eWOM, and no study has yet compared WOM and eWOM. The investigation of differences between WOM and eWOM communication is an important future research field and could be examined in future studies. Approximately half of the eWOM studies were conducted in Asia, while only few studies on this subject were carried out in North America and Europe, clearly indicating a need to catch up. Furthermore, only two studies involved a comparison between countries. Research into cultural differences could be more focused. Cultural components differ strongly, also in WOM. Therefore, additional WOM studies comparing countries would likely provide new scientific insights. Regarding medical disciplines, there exist few studies on general practitioners, gynecologists, and osteopaths, but no studies could be found on medical disciplines like dermatologists, ophthalmologists, otolaryngologists, and pediatricians, to mention only a few neglected fields.

Concerning the creation dimension, only one study by Drevs and Hinz ( 2014 ) investigated indirectly affected stakeholders, namely relatives, who may also play an important role in the creation of WOM. Future studies could examine additional stakeholders involved in the WOM creation process. For example, within eWOM, not only family members of patients are indirectly involved in the decision-making process, but also review writers and commenters of postings. In addition, most of the studies concerning the creation dimension were conducted on the inpatient area. Future studies could focus more on the outpatient area. With respect to the spread dimension, the circulation of WOM in personal networks could be examined in future studies. An interesting research field are, for example, the differences between the spread of positive and negative health-related WOM, the influence of the personal network structure, and the estimation of source credibility. Studies on the differences between paid and unpaid WOM also represent a future field of research. Regarding the impact dimension, due to the increasing prevalence of online communication, inaccurate and fake health care information are easily spread. Potential risks related to this development represent another future field of research.

For all future studies, the revised WOM model can be an important contribution inasmuch as it systematically presents existing studies on WOM in health care.

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Pauli, G., Martin, S. & Greiling, D. The current state of research of word-of-mouth in the health care sector. Int Rev Public Nonprofit Mark 20 , 125–148 (2023). https://doi.org/10.1007/s12208-022-00334-6

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A Literature Review of Word of Mouth and Electronic Word of Mouth: Implications for Consumer Behavior

The rise and spread of the Internet has led to the emergence of a new form of word of mouth (WOM): electronic word of mouth (eWOM), considered one of the most influential informal media among consumers, businesses, and the population at large. Drawing on these ideas, this paper reviews the relevant literature, analyzing the impact of traditional WOM and eWOM in the field of consumer behavior and highlighting the main differences between the two types of recommendations, with a view to contributing to a better understanding of the potential of both.

Introduction

Consumers increasingly use online tools (e.g., social media, blogs, etc.) to share their opinions about the products and services they consume ( Gupta and Harris, 2010 ; Lee et al., 2011 ) and to research the companies that sell them. These tools are significantly changing everyday life and the relationship between customers and businesses ( Lee et al., 2011 ).

The rapid growth of online communication through social media, websites, blogs, etc., has increased academic interest in word of mouth (WOM) and electronic word of mouth (eWOM) (e.g., Hennig-Thurau et al., 2004 ; Brown et al., 2007 ; Cheung and Thadani, 2012 ; Hussain et al., 2017 ; Yang, 2017 ). Specifically, the present paper will review the literature on how these two media have evolved, the main differences between them, and the degree to which they influence both businesses and consumers, now that they have become some of the most influential information sources for decision-making.

Word of mouth is one of the oldest ways of conveying information ( Dellarocas, 2003 ), and it has been defined in many ways. One of the earliest definitions was that put forward by Katz and Lazarsfeld (1966) , who described it as the exchanging of marketing information between consumers in such a way that it plays a fundamental role in shaping their behavior and in changing attitudes toward products and services. Other authors (e.g., Arndt, 1967 ) have suggested that WOM is a person-to-person communication tool, between a communicator and a receiver, who perceives the information received about a brand, product, or service as non-commercial. Likewise, WOM has been defined as communication between consumers about a product, service, or company in which the sources are considered independent of commercial influence ( Litvin et al., 2008 ). These interpersonal exchanges provide access to information related to the consumption of that product or service over and above formal advertising, i.e., that goes beyond the messages provided by the companies and involuntarily influences the individual’s decision-making ( Brown et al., 2007 ). WOM is widely regarded as one of the most influential factors affecting consumer behavior ( Daugherty and Hoffman, 2014 ). This influence is especially important with intangible products that are difficult to evaluate prior to consumption, such as tourism or hospitality. Consequently, WOM is considered the most important information source in consumers’ buying decisions ( Litvin et al., 2008 ; Jalilvand and Samiei, 2012 ) and intended behavior. For example, tourist satisfaction is of utmost importance because of its influence on behavioral intentions, WOM and purchasing decisions. In other words, overall satisfaction leads to the possibility of revisiting and recommending the destination ( Sotiriadis and Van Zyl, 2013 ).

Similarly, previous research indicates that consumers regard WOM as a much more reliable medium than traditional media (e.g., television, radio, print advertisements, etc.) ( Cheung and Thadani, 2012 ). It is thus considered one of the most influential sources of information about products and services ( Lee and Youn, 2009 ). Users generally trust other consumers more than sellers ( Nieto et al., 2014 ). As a result, WOM can influence many receivers ( Lau and Ng, 2001 ) and is viewed as a consumer-dominated marketing channel in which the senders are independent of the market, which lends them credibility ( Brown et al., 2007 ). This independence makes WOM a more reliable and credible medium ( Arndt, 1967 ; Lee and Youn, 2009 ).

Today’s new form of online WOM communication is known as electronic word-of-mouth or eWOM ( Yang, 2017 ). This form of communication has taken on special importance with the emergence of online platforms, which have made it one of the most influential information sources on the Web ( Abubakar and Ilkan, 2016 ), for instance, in the tourism industry ( Sotiriadis and Van Zyl, 2013 ). As a result of technological advances, these new means of communication have led to changes in consumer behavior ( Cantallops and Salvi, 2014 ; Gómez-Suárez et al., 2017 ), because of the influence they enable consumers to exert on each other ( Jalilvand and Samiei, 2012 ) by allowing them to obtain or share information about companies, products, or brands ( Gómez-Suárez et al., 2017 ).

One of the most comprehensive conceptions of eWOM was proposed by Litvin et al. (2008) , who described it as all informal communication via the Internet addressed to consumers and related to the use or characteristics of goods or services or the sellers thereof. The advantage of this tool is that it is available to all consumers, who can use online platforms to share their opinions and reviews with other users. Where once consumers trusted WOM from friends and family, today they look to online comments (eWOM) for information about a product or service ( Nieto et al., 2014 ).

As a result of ICT, today consumers from all over the world can leave comments that other users can use to easily obtain information about goods and services. Both active and passive consumers use this information medium (eWOM). Individuals who share their opinions with others online are active consumers; those who simply search for information in the comments or opinions posted by other customers are passive consumers ( Wang and Fesenmaier, 2004 ).

Electronic word of mouth also provides companies with an advantage over traditional WOM insofar as it allows them both to try to understand what factors motivate consumers to post their opinions online and to gauge the impact of those comments on other people ( Cantallops and Salvi, 2014 ). However, consumers’ use of technology to share opinions about products or services (eWOM) can be a liability for companies, as it can become a factor they do not control ( Yang, 2017 ). To counteract this, businesses are seeking to gain greater control of customers’ online reviews by creating virtual spaces on their own websites, where consumers can leave comments and share their opinions about the business’s products and services ( Vallejo et al., 2015 ). By way of example, in the field of tourism, companies are starting to understand that ICT-enabled media influence tourists’ purchasing behavior ( Sotiriadis and Van Zyl, 2013 ).

Understandably, companies view both types of recommendations – WOM and eWOM – as a new opportunity to listen to customers’ needs and adjust how they promote their products or services to better meet them, thereby increasing their return. A negative or positive attitude toward the product or service will influence customers’ future purchase intentions by allowing them to compare the product or service’s actual performance with their expectations ( Yang, 2017 ).

In the field of consumer behavior, some previous studies (e.g., Park and Lee, 2009 ) have shown that consumers pay more attention to negative information than to positive information ( Cheung and Thadani, 2012 ). For example, the customers most satisfied with a product or service tend to become loyal representatives thereof via positive eWOM ( Royo-Vela and Casamassima, 2011 ), which can yield highly competitive advantages for establishments, businesses, or sellers, especially smaller ones, which tend to have fewer resources. Some studies have suggested that traditional WOM is the sales and marketing tactic most often used by small businesses.

Additionally, eWOM offers businesses a way to identify customers’ needs and perceptions and even a cost-effective way to communicate with them ( Nieto et al., 2014 ). Today, eWOM has become an important medium for companies’ social-media marketing ( Hussain et al., 2017 ).

WOM vs. eWOM

While many authors (e.g., Filieri and McLeay, 2014 ) consider eWOM reviews to be electronic versions of traditional WOM reviews, this paper aims to summarize and explain the main differences between the two concepts ( Table ​ Table1 1 ). The first such difference is credibility as an information source ( Cheung and Thadani, 2012 ; Hussain et al., 2017 ), since it can influence consumers’ attitudes toward products or services ( Veasna et al., 2013 ), for example, with regard to the purchase of tourism services, which are considered to be high-risk ( Sotiriadis and Van Zyl, 2013 ). Luo et al. (2013) have suggested that the anonymity of online messages could have a negative effect on their credibility. In contrast, other studies (e.g., Hussain et al., 2017 ) have argued that consumers use eWOM more to reduce risk when decision-making. Likewise, eWOM tends to be more credible when the consumer using it has previous experience ( Sotiriadis and Van Zyl, 2013 ).

Differences between WOM and eWOM.

Message privacy is another feature that sets the two media apart, since with traditional WOM information is shared through private, real-time, face-to-face dialogs and conversations. In contrast, information shared through eWOM is not private and can sometimes be seen by anonymous people who do not know each other. Furthermore, reviews can be viewed at various points in time ( Cheung and Thadani, 2012 ). Indeed, because eWOM reviews are written, consumers and companies can check them at any time; this stands in contrast to traditional WOM, where once the message has reached the receiver, it tends to disappear.

Another salient difference between the two media is the speed of diffusion of the message; eWOM statements spread much faster than WOM statements because of where they are published, i.e., on the Internet ( Gupta and Harris, 2010 ). Online platforms for sharing information (social media, websites, blogs, etc.) are what set eWOM apart from traditional WOM ( Cheung and Thadani, 2012 ). First, they make the reviews accessible to more consumers ( Cheung and Thadani, 2012 ; Sotiriadis and Van Zyl, 2013 ). Second, because they are written, they persist over time ( Hennig-Thurau et al., 2004 ; Cheung and Thadani, 2012 ).

This paper has reviewed the literature with a view to providing a clearer understanding of WOM and eWOM in the context of consumer information searches.

To this end, the review found that, in keeping with numerous studies, WOM is both the oldest medium for sharing opinions about products or services and the one most likely to influence consumer behavior, due to the high reliability and credibility transmitted by family and friends. In contrast, few studies have examined the interaction between perceived risk and eWOM source credibility ( Hussain et al., 2017 ).

Notwithstanding the above, the review of the theoretical framework also revealed a gap in the literature on WOM credibility in situations involving multiple or many communicators and receivers and how this ultimately affects the end consumer. This would include, for instance, situations in which one person communicates a message to another, who acts as an intermediary, both receiving the original message and passing it along to a third party, i.e., the end consumer. In such cases, the original message can be altered or distorted, chipping away at the credibility of the WOM review as a source of information. This lends much more strength to written comments and reviews, such as eWOM, which can ultimately reduce risk and increase consumer confidence.

Another feature that distinguishes eWOM from traditional WOM is the speed with which it spreads and the ease of access to it. In this regard, when consumers need information about a product or service, they ultimately turn to online media (eWOM) for two reasons. First, they can get the information more quickly, as there is no need to wait for someone else – a friend or family member – to offer an opinion about what they wish to consume. Second, if they have already received WOM reviews, they can use eWOM to corroborate the information received. Therefore, credibility and speed are the two main features not only distinguishing the two media, but also influencing consumer behavior.

Finally, the analysis of the review showed that these two concepts – WOM and eWOM – while seemingly the same, are at the same time very different. The Internet has transformed traditional WOM into eWOM. The communication of opinions is no longer done interpersonally (i.e., person-to-person or face-to-face), but rather is mediated by ICT. However, the many studies conducted (e.g., Katz and Lazarsfeld, 1966 ; Brown et al., 2007 ; Daugherty and Hoffman, 2014 ; Yang, 2017 ) agree that they are the media most able to influence consumer behavior and the most often used to obtain information before, during, and after consuming a given product or service. For example, in the field of tourism, eWOM is considered the most influential pre-purchase source of travel information ( Sotiriadis and Van Zyl, 2013 ).

Author Contributions

This paper tries to offer a clearer understanding of the two concepts through a literature review and an exploration of how, as a result of advances in ICT, traditional WOM has given rise to eWOM. The author has made an important, direct, intellectual contribution to this paper and has approved it for publication.

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding. This research was funded by the Spanish Ministry of Economy and Competitiveness under Research Project ECO2014-59688-R (“Planning and implementation of optimal management strategies for physical, online and mobile POSs based on ICT and innovation”).

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Apr 8, 2024

A Guide to Word of Mouth Marketing

• Content Marketing
• Digital Marketing

The constant stream of ads and promotional messages has led to marketing fatigue among consumers. According to Optimove, 27% feel bombarded by the incessant messages and 66% want fewer ads. 

Worn down by all the advertising noise, consumers are turning to recommendations from friends, family, or online communities to inform their purchasing decisions. 

As a result, word of mouth marketing can help marketers cultivate brand advocates who actively promote products or services to their social media circles . 

Integrating this approach into the broader marketing mix not only enhances the visibility of a brand, but it also brings authenticity that can lead to sustained growth and customer retention.

In this blog, we will explore:

What is word of mouth marketing?

• What are the benefits of word of mouth marketing? 

How do you do word of mouth marketing?

How do you measure word of mouth marketing.

• 3  great examples of successful word of mouth marketing

Word of mouth marketing is a form of marketing that is shared organically by consumers. It happens when people ‘spread the word’ about a brand or product.  

This can be done in several ways and on different channels such as:

Online reviews

The core ingredient of word of mouth marketing, online reviews are how people share their recommendations (and warnings!) about products that they’ve used. Brands need to keep a close eye on these reviews to monitor brand sentiment.

User-generated content

By encouraging consumers to share user-generated-content, or  UGC (such as reviews, unboxing videos, or fun uses of the product), brands can foster closer connections with their audiences and build valuable creative relationships. This is also a great way to spread positive word of mouth.  

Social listening

Many people now share their thoughts about brands on social media, usually tagging the brand in their comments. Using social listening techniques , brands can get a good idea of what the ‘word on the street’ is about the brand. 

Influencer marketing

Although people are somewhat more skeptical of influencers today, brands can still foster rewarding relationships with carefully chosen influencers. By selecting influencers that they’re confident that their audience will trust, brands can increase reach by cultivating positive brand advocacy. 

Don’t underestimate the power of blogging in generating good buzz around a brand. Don’t just share promotional content with your audience. Establish thought leadership around your brand and encourage people to take part in an ongoing conversation. 

“90% of consumers are more likely to trust a brand that was recommended by others. 25% are likely to avoid a brand if a friend or family member shared a bad experience about that brand” Semrush

Traditional marketing channels often rely on paid advertisements or promotional campaigns. While word of mouth spreads organically by satisfied customers sharing their experiences with others. 

By leveraging positive online buzz and social influence, brands can generate awareness, cultivate customer loyalty, build credibility and trust, and ultimately drive sales. 

What are the benefits of word of mouth marketing?

Including word of mouth in your marketing strategy can bring several benefits:

• It is more cost-effective than traditional marketing or paid advertising. 
• It has persuasive power because it is built on personal endorsements.
• It builds brand credibility because it’s seen as being more authentic and ‘real’ than carefully crafted advertising copy. 
• It nurtures customer relationships by encouraging direct contact with the target audience. 
• It helps to protect brands by making social listening and sentiment analysis key parts of the marketing approach. 
• It enables brands to build a content library by encouraging UGC.

As Rand Fishkin said in his  recent podcast  with us, “Advertising is a terrible first way to reach somebody. It just does not perform versus organic brand mentions or word of mouth or from a trusted resource.”

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First things first, do you know your target audience? This is important because to attract the word of mouth that increases brand reach, you need to know who you are talking to. 

You can do this by analyzing data on how people interact with your website or how they use your product/service. Think about which platforms they are active on. Do they contribute to discussions on Reddit ?

LinkedIn can also be a valuable source of audience data. Many people put more personal information on there than on other social platforms. For example, you can find out a person’s:

• Role description
• Keywords of skills and interests

When you merge this data with other data sources, you can build up a comprehensive picture of a target audience. For example, you might discover that people who search for spaghetti bolognese recipes are 70% men! This can then inform how you best write content for that audience. 

Once you know your audience you can then implement a word of mouth marketing strategy. This requires you to focus on two key areas.

1. How you build the product/service

The best way to generate positive word of mouth around a product or service is to keep the user experience front of mind. 

So consider the design and features. Your product doesn’t have to look beautiful. It has to function beautifully. It has to be easy for people to use. 

Sometimes you have to compromise between product design and user experience . For example, an email inbox is not very pretty or ‘screenshotable’ but it's probably in its most useful form.

2. How you describe the product/service

Think about who your product or service is aimed at, and how you describe the product to that audience. 

What does the product do? Who is it positioned for? What need does it address for them? What problem does it solve? Once you know the answers to the most important questions, then you can create compelling marketing content around that. 

It can be difficult to track the effectiveness of word of mouth marketing without  large-scale, expensive market surveys. 

Instead, brands can pay close attention to online brand sentiment using tools like SparkToro or Talkwalker and respond proactively to any negative word of mouth content. 

You can also ask customers how they heard about your brand and use that as qualitative data. Email marketing can be helpful with this as you can send a message to existing customers or engaged prospects. 

If your brand has a loyalty program, you can track promo codes or UTMs to measure leads generated or revenue. 

3 great examples of word of mouth marketing

An effective word of mouth marketing campaign needs to be believable and shareable. You also need to be able to measure its effectiveness whether that’s through social media engagement or brand mentions. 

Let’s look at three great word of mouth marketing campaigns to give you some inspiration. 

1) Threadless

Threadless started out as a place to sell t-shirts and has evolved into a commerce marketplace for a range of products. Its success is down to its Artists Shop community where individuals make money by sharing their designs and selling products. 

With an audience that values creativity and embraces fun, the company hosts challenges and contests that pit artists' designs against each other. This encourages its audience to participate by voting, sharing the contest amongst its social circle and building a community around the brand. 

Sozy is a women’s clothing brand with a difference. It’s committed to making a difference and donates 10% of its profit to survivors of sexual violence and a further 10% going to other charitable and environmental initiatives (along with being environmentally responsible in its clothing production). 

For you B2B marketers , online graphic design tool Canva uses word of mouth to show how effective its platform is. They started off by targeting a specific audience - people with no design experience that wanted to create great designs. 

From there the company has grown by creating an active community (plus free sign-up to try the product). The word of mouth strategy that’s proved successful (in addition to customer reviews and UGC) is their ‘Design Stories’ series. 

This series shines a light on business owners who have succeeded using Canva. But it goes further than that by looking at the origins of these companies and the motivations of the founders to set them up. This series helps build brand affinity and engage its audience in a connected community. 

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Word-of-Mouth Marketing: Building a Strategy That Really Works

Last updated on November 22, 2023

Word of mouth marketing and testimonials are an extremely effective way to promote your products.

Let’s start with the facts. 92% of consumers will believe a recommendation from friends and family over any other type of advertising. That simple statistic casually hides one of the most powerful truths in marketing: Your biggest marketing asset is your existing customer base

Today, many businesses spend millions on advertising to new audiences, while completely neglecting the marketing potential of their existing customers. And while there are many different ways to harness your existing user base, few are as powerful as word of mouth marketing, and that’s the strategy we’ll be discussing today.

What Is Word of Mouth Marketing?

Word-of-mouth advertising (WOM advertising), also called word of mouth marketing, is the process of actively influencing and encouraging organic word of mouth discussion about a brand, organization, resource, or event.

To put it most simply, word of mouth marketers and advertisers seek to create something worth talking about and then actively encourage people to talk about it.

As we noted earlier, people love referrals  and they tend to trust the opinions of their friends when making purchasing decisions. Word of mouth advertising is essentially seeking to kickstart an exponential referral chain that drives continuous traffic, leads, and sales for the brand.

Word of Mouth Advertising Statistics: Why Does WOM Work So Effectively?

While some customer marketing tactics require a strong pitch, when it comes to word of mouth advertising, the statistics speak for themselves.

Just take a look at a few of the top statistics, and it doesn’t take long to see how powerful word-of-mouth marketing really is:

So what makes it work?

Essentially, it comes down to trust. People trust what others have to say, which means when they hear about something from a friend or previous consumer, they’re more likely to buy. But there’s more at work.

Studies by marketing expert Jonah Berger have found two driving factors that power WOM marketing content. These factors are social currency and triggers.

Top 2 Reasons Word-of-Mouth Marketing Works:

• Social Currency

Social currency relies on the idea of exclusivity. In short, we like to feel special. Hearing about an underground club or secret menu item triggers our need to belong to an exclusive group.

Accordingly, an easy way to encourage word of mouth discussion is through marketing strategies that pick up on the social currency factor, offering insider secrets or exclusive information (ex. secret menus). Triggers are a natural social mechanism that remind us about a brand or product even when we don’t see advertising.

For example, imagine your friend told you about a special happy hour deal on Tuesdays at a bar near your house. On Tuesday, when another friend mentions grabbing drinks after work, you will be triggered to remember the place you heard about with Tuesday specials. Tuesday becomes the trigger amplifying the effect of WOMM. In this way, word of mouth can also be a way to improve existing customer engagement strategies .

Word of mouth marketing & user-generated content

Another reason why word-of-mouth marketing works is because of the same principles that marketing with user-generated content is so successful.

User-generated content is voluntarily created and shared by everyday consumers, while word of mouth is the organic sharing of information or opinions about a product, company, or brand, from one consumer to the other.

One powerful type of user-generated content is reviews — and getting customers to write reviews is one way to facilitate the spread of word-of-mouth marketing. When potential shoppers read reviews, it builds customer trust by showing them that a verified customer offers their endorsement of your brand.

How to Build a Word of Mouth Marketing Strategy

Successful implementation of word of mouth campaigns can’t be accomplished via cookie cutter tactics.

There is an inherently creative element to the process that must be artfully and uniquely applied to each brand.

As I mentioned earlier, word of mouth promotion tends to incorporate two key components:

• Create something buzz-worthy
• Encourage the buzz

In other words, word of mouth promotion doesn’t simply attempt to get people excited about a business’ logistics, daily operations, or profit model.

The key to a successful word of mouth marketing strategy is to either identify something about a brand that can generate organic buzz OR create something that will generate that buzz.

To find out how to do this effectively, look to successful word of mouth marketing examples for inspiration.

Top 3 Word-of-Mouth Marketing Examples

One of the best ways to build a successful strategy of your own is by looking at what worked for other brands.

TOMS: Creating organic buzz by doing good

As you are no doubt aware, TOMS became a famous, massively profitably shoe company thanks to the viral popularity of their One-for-One business model.

When you buy one pair of shoes from TOMS, one pair is also donated to a child in need of shoes. This model was touted and received as a form of consumer-driven charity, and as a result, the company exploded, reaching a valuation of over $600 million in 2014.

In the cold reality of hard numbers, the Alpargatas shoes TOMS sells retail for around $2-5 in South America, indicating an incredibly low manufacturing cost.

With a price point of $60, its fair to say that TOMS shoes’ actual charity contributions are relatively marginal.

Despite this, TOMS realized that “company gives shoes to those in need every time you buy” made for a far more buzzworthy headline than “company donates money to poor people”.

As a result, the company focused its branding around this buzzworthy portion of its business model, and then blitzed the media with its message, generating tons of news coverage and hundreds of thousands of backlinks.

While TOMS opted to build its business model around something it could make buzzworthy, this isn’t an option for most businesses. Instead, these businesses have the opportunity to create something interesting that people will get excited about and then spread the word.

Chipotle: Creating WOM Buzz Through Storytelling

Casual dining chain Chipotle has somewhat distinguished itself being a national chain that sources its ingredients locally.

That said, “ingredients sourced locally” isn’t necessary something that is going to blow up anyone’s Facebook feed.

In order to spearhead word of mouth, Chipotle created a haunting video, with an accompanying iPhone app, depicting a dreary, over-processed world run by machinery.

The video and app combined have generated over 614 million media impressions, according to Cision, making it a major WOMM win for Chipotle.

You can make anything newsworthy with the right story. While local sourcing isn’t inherently newsworthy, the Chipotle marketing team made it newsworthy through a combination of art, storytelling, and a targeted media blitz.

Coca-cola “Share a Coke With Friends”: Omnichannel WOM

Coca-cola’s campaign asked for consumers to participate by sharing a personalized soda bottle with friends, in person and on social media.

Coca-cola even supported the campaign with events where consumers could create their own personalized Coke bottle.

Social media makes digital WOM marketing much easier, but real WOM marketing happens both on and off the web.

Build omnichannel WOM marketing with campaigns that encourage users to integrate information they gain about your product on and off the web.

Learning from these brands:

The processes from these examples can be repeated by virtually any company looking to generate grassroots word of mouth coverage of their brand.

When coming up with word of mouth marketing ideas, it’s important to see what worked for other successful brands.

Very few marketing strategies can match WOMM in terms of viral potential or cost-efficiency.

The right strategy can explode a company onto the scene for mere pennies, but it doesn’t just happen by itself.

Word of mouth marketing requires a genuine and meaningful customer engagement with the target audience. It’s a two-way participation.

Use the strategies we discussed here today, but remember that ultimately, it’s meaningful connection, rather than technique, that motivates customers to become brand ambassadors.

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