SciELO - Scientific Electronic Library Online

 
vol.25 issue1Systematic literature review on the ways of measuring the of reverse logistics performance author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

Share


Gestão & Produção

Print version ISSN 0104-530XOn-line version ISSN 1806-9649

Gest. Prod. vol.25 no.1 São Carlos Jan./Mar. 2018  Epub Feb 05, 2018

https://doi.org/10.1590/0104-530x2244-16 

Original Article

Brand community or electronic word-of-mouth: what’s the goal of company presence in social media?

Michel Lens Seller1 

Fernando José Barbin Laurindo1 

1Departamento de Engenharia de Produção, Escola Politécnica, Universidade de São Paulo – USP, Av. Prof. Almeida Prado, 128, Butantã, CEP 05508-070, São Paulo, SP, Brazil, e-mail: michelseller@usp.br; fjblau@usp.br


Abstract

The growing usage of social media has been changing the relationship between companies and customers. Social media opens a two-way communication channel between companies and customers, as well as enables interaction among customers. According to the literature, companies pursue two objectives on social media: to increase brand trust and loyalty through building brand communities and to influence the purchase decision of an empowered customer through engendering positive word-of-mouth for their products. This article studies the approach used by two companies (from the pharmaceutical and fashion industries) on their Facebook fan pages. Evidence of shared consciousness and practice of traditions gathered from a netnographic study reveals a brand community on the pharmaceutical company’s page. Analysis of electronic word-of-mouth metrics reveals that motivating this form of communication is what the fashion firm seeks through its fan page. The study also discusses mechanisms to stimulate word-of-mouth on fan pages and the presence of weak ties as a factor of consumer engagement in word-of-mouth on social media. Managerial implications, limitations, and future research suggestions are presented.

Keywords:  Brand community; Word-of-mouth; Social media; Social network; Information diffusion

Resumo

O uso crescente de mídias sociais vem alterando o relacionamento entre empresas e clientes. As mídias sociais abrem um canal de comunicação bidirecional entre a organização e seus consumidores, assim como promove a interação entre estes. De acordo com a literatura, são dois os objetivos perseguidos pelas empresas neste ambiente: aumento de confiança e lealdade à marca por meio de comunidades de marca; e influência na decisão de compra do cliente pela promoção de comunicação boca a boca positiva sobre seus produtos. O presente artigo estuda a abordagem utilizada por duas empresas (dos segmentos farmacêutico e de varejo de moda) em suas fan pages no Facebook. Evidências de consciência comum e prática de rituais e tradições obtidas a partir de um estudo netnográfico revelam uma comunidade de marca na página da empresa farmacêutica. A análise de métricas de boca a boca eletrônico revela que o estímulo a esta forma de comunicação é o que busca a indústria de moda por meio de sua página. O estudo ainda discute mecanismos para estimular o boca a boca em fan pages e a presença de vínculos fracos como fator de engajamento de consumidores nesta prática. Implicações gerenciais, limitações e sugestões de pesquisas futuras são apresentadas ao final.

Palavras-chave:  Comunidade de marca; Boca a boca; Mídia social; Rede social; Difusão de informações

1 Introduction

The rise and popularization of social media changed the relationship between company and customer. Prior to the popularization of social media, these relationships existed through one-way channels such as TV, radio, and the print media with little opportunity for interaction between companies and their customers. Social media opened a dialogue between companies and consumers, and permitted the customers to exchange information among themselves. Two phenomena in this process are of particular interest: the convenience provided by social media, and in particular by social networks, in developing brand communities, usually sponsored by the companies, and facilitating the existence of word-of-mouth communication by consumers of the brand or product.

Through brand communities, companies aim to strengthen the relationship with their customers and thus acquire trust, and ultimately, the loyalty of their customers.

Word of mouth is the main factor behind 20 to 50 percent of buying decisions (Bughin et al., 2010). This type of communication finds its own ground in social media, and is the modality known as eWOM (electronic word-of-mouth).

If, on the one hand, eWOM has a much broader coverage than traditional word-of-mouth, on the other, it requires that companies pay special attention to the features of social media to make effective use of it. The company does not have total control over eWOM management with respect to its brands or products, given that the simple introduction of a new product into the market makes it a candidate for interaction among consumers via social media. This dynamic simultaneously brings risks, such as the circulation of negative information, as well as representing an opportunity to gain competitive advantages through collaboration with customers.

This article evaluates, through a case study involving two companies with very distinctive characteristics regarding their social network presence and sector of activity, the existence of brand communities and the intensity of the generation of eWOM on social networks and the motives behind the companies opting for one approach or another. Facebook was selected as the social network for the study, due to its wide popularity, international availability, and because it hosts a large number of brand-related communities that are candidates for categorization into brand communities according to the criteria proposed by Muniz & O'Guinn (2001).

The first is a Brazilian company, active in feminine fashion retail, with a highly popular brand; its social network presence includes over 3.5 million Facebook followers. The second company is a multinational pharmaceutical industry, which also has a strong brand and wide popularity. However it does not interact directly with the final consumer since it distributes its products through pharmacies. It has a little over 100,000 Facebook followers.

Research on the formation of brand communities on social networks is done with a method known as netnography, or the ethnography of the internet (Kozinets, 2002). This method consists of collecting and analyzing public conversations generated in the online community studied. This marketing research technique is used to obtain insights on consumers less intrusively, more cheaply, and more quickly. Netnography is used to identify on the company’s Facebook page evidence of consciousness of kind, practice of rituals and traditions, and a sense of moral responsibility, which are the three main characteristics of brand communities according to Muniz & O'Guinn (2001).

The intensity of eWOM generation is assessed by the rate of engagement, which reflects the interactions between Facebook company pages and their fans.

The result points to a difference in the predominance of eWOM and brand communities on the company pages studied. Analysis of the motives that led to adopting one or the other approach can provide information to help define the social media strategies of other companies.

The article is structured as follows: the theoretical background section reviews the existing literature on the relationship between companies and consumers in the social media context, emphasizing the creation of brand communities and word-of-mouth communication. The methodology section discussed the netnography, or internet ethnography, technique used to assess the intensity of electronic word-of-mouth. This is followed by a presentation of the results, discussing the managerial implications, the limitations on the work, and suggestions for future research.

2 Theoretical background

In recent years, social media has become a new component in the set of marketing tools, allowing companies to establish new ways of relating to their clients. The recent popularization of social media has resulted from a combination of greater access to wide band, dissemination of tools that permit users to generate content, and to the arrival of young people with expertise in information technology tools to the consumer market (Kaplan & Haenlein, 2010).

Historically, the relationship between companies and customers has occurred via one-way channels, such as the printed press, radio, TV and, more recently, the internet itself, where carefully controlled persuasive messages proliferate with little opportunity for responses (Larson & Watson, 2011). The advent of social media altered this scenario and opened a dialogue between organizations and their customers, as well as facilitating interaction among clients. This new dynamic allows customers to create and share information on company products and services, and this process involves risks, such as negative word-of-mouth, as well as opportunities, such as gaining competitive advantages through collaboration with customers (Tapscott, 2008).

Kaplan & Haenlein (2011) define social media as a group of internet-based applications that allows for the creation and exchange of user-generated content. Social media encompasses a broad set of applications, including social networks (Facebook, for example), site for sharing creative material (for example, YouTube), sites for generating collaborative content (Wikipedia, for example), and blogging and micro-blogging tools (Twitter, for example).

Social networks, of special interest in this work, can be defined as internet-based services that allow users to: create a public or semi-public profile within a system; make a list of other users with whom a connection is shared (“friends”); and visualize and cross check that list of connections with those created by others in the system (Boyd & Ellison, 2008). These characteristics are unfavorable to the traditional use of pseudonyms and increase the authenticity of interactions among users. In addition to text-based information, social network profiles incorporate visuals, audio, and video. Blogging, instant messaging, chatting, updated profile notifications of connections (“friends”), and event planning are some resources commonly found on social networks. More recently, resources such as sponsoring and participating in research and checking-in at public and private places have been incorporated into the tools. The above cited elements comprise what is conventionally called Web 2.0 and are used for socialization, sharing content, and entertainment (Messinger et al., 2009).

Study of social networks reveals that, within this phenomenon, subgroups which have a focus on specific topics develop and have a stricter scope compared to the diversity of social networks (Zaglia, 2013). On the LinkedIn social network, for example, users join groups focused on business events or common interests, or even groups of alumni from a university. On Facebook, users can join groups or fan pages.

A Facebook fan page can be imagined as a site related to a certain brand or company. Facebook members become page fans by hitting the like button. According to Facebook itself, the goal of a fan page is to disseminate information in an official public way to people who choose to connect to it. In this same tool, a group is a space for people to share interest in and express opinions on a given subject. Groups can be open, closed, or secret, while fan pages are always public. Generally, groups tend to have fewer members than fan pages. Fan pages tend to be company sponsored, while groups tend to be the product of consumer initiative.

In a more detailed way the relationship between companies and customers on social media can be structured as seen in Figure 1 below.

Figure 1 The company-customer relationship in the social media context (adapted from Larson & Watson, 2011). 

The relationship identified as number 1 represents a traditional internet marketing model, through which the companies broadcast advertising messages to their customers via the web and interested customers respond by visiting a commercial electronic site or going to a physical store. Moreover, under this component of the company-customer relationship model we find messages originating by the company notifying customers of problems, such as recalls or interruption of services.

The companies offer their customers diverse systems, complemented by human activities that allow them to request support for their products or services. Included there are call centers, self-service systems and email correspondence. This component of company-customer relations is identified by number 2 in the Figure 1 below.

Building brand communities is one of the opportunities for companies that opened up with the advent of social media. The strategy used to construct a brand community must take into account the company’s capabilities and objectives. One of the alternatives is the laissez-faire approach, by which the company renounces attempting to direct the behavior of its customer base on social media and instead exploits the content created by participants, which also tends to assure the authenticity of such content. The second approach has a more dominating nature; from the start the company tries to mold its customers’ social media, thus running the risk of negative conduct generated by dissatisfied customers. There seems to be consensus that companies which are successful in the social media environment are those that cede space to customers, despite the risks inherent to abdicating control. Development of brand community is represented by number 3 in the Figure 1 above.

The companies can be involved in online word-of-mouth whether or not they intend to enter this domain. In fact, once a product in introduced to the marker, it becomes a possible subject for customers’ social media interactions. Thus, the portfolio of social media tools associated with a brand or product includes components that are beyond company control, complemented by others the company might use. Interaction among customers around a brand or product is generally outside company control (Larson & Watson, 2011). In the Figure 1 above, word-of-mouth among customers on social media is represented by relationship number 4.

If, on the one hand, interactions among customers on social media are beyond company control, on the other, companies have available a large mass of public data from monitoring these interactions which can be used to assess customer preferences. The literature suggests that this intra-group dialogue can provide insights about customers, as well as market intelligence (Larson & Watson, 2011). Monitoring customer interactions can also allow companies to intercede in negative conversations, thus preventing their content from going viral and minimizing potential damage to their image. Monitoring word-of-mouth among customers is represented by number 5 in Figure 1.

2.1 Brand communities

The concept of brand communities arose much earlier than social media. They can be defined as a particular form of social group organized around a brand with a demonstrated consciousness of kind, observes traditions and practices rituals, and has a sense of moral responsibility (Muniz & O'Guinn, 2001). The advent of social media permitted companies to develop brand communities in less time and a lower cost (Zaglia, 2013).

The first of the three characteristics of a brand community, consciousness of kind, refers to the community members’ sense of connection to each other and separate from those outside the group (Bagozzi & Dholakia, 2006). Thus, they serve one of the most basic human motivations, the desire to belong to a wider group of peers with a similar mentality, to fit in and be accepted. One visible manifestation of this characteristic is, for example, the use of pronouns such as “us” to refer to the community, demonstrations of emotional connection, and pride in group belonging.

With brand consumption as the unifying element and the ease of connection provided by social media, companies have an unprecedented platform to exploit motivation such as “belonging” in order to conquer consumer loyalty and benefit their brands (Fournier & Avery, 2011).

The second feature of a brand community is the practice of rituals and traditions, which refers to creating a proprietary meaning for the community experience. Celebrating history or exchanging stories involving the brand are indicators of this characteristic (Muniz & O'Guinn, 2001). Moreover, community members hold a common set of values and display similar behaviors, such as using jargon.

A sense of moral responsibility is the last of the three main characteristics of brand communities. This refers to the moral commitment of community members to each other and to the community as a whole. Practical manifestations of this include integrating and retaining members, support for product use and assistance in general (Zaglia, 2013).

According to McAlexander et al. (2002), a community is comprised of its entities and the relationships among them. Thus, for this author a brand community includes the product and the company entities in addition to the brand itself and its customers. This model is known as a customer-based brand community, represented graphically by Figure 2.

Figure 2 Customer-centered brand community model (adapted from McAlexander et al., 2002). 

Based on this model, the brand community encompasses a.) The relationship between customer and product; b) The relationship between customer and brand; c) the relationship between customer and company; and d) The relationship among customers (Laroche et al., 2013)

In a social media context, community members typically explore the company’s pages, comment, share experience, interact with the company, ask questions about the brand or product or respond to others’ comments, and thus exercise all the relationships in the model.

2.2 Trust and loyalty

According to the literature on loyalty and trust, trust is one of the main precursors of loyalty (Zhou et al., 2012). Considering that online communities, as social structures, have a positive effect on trust and loyalty (Ba, 2001) we can assume that strengthening the relationships in the consumer-based brand community increases trust in the brand, which in turn has a positive effect on brand loyalty. In other words, trust in the brand measures the translation of the effects of brand communities on loyalty and trust. The relationship within brand communities, trust and loyalty can be examined in Figure 3 below.

Figure 3 Trust and loyalty model generated based on brand communities (adapted from Laroche et al., 2013). 

The relationship between brand community, trust, and loyalty can be examined in Figure 3 below.

Research conducted by Laroche et al. (2013) found that in the social media context, brand communities have a positive effect on customer/product. Customer/brand, customer/company relationships and among customers, which in turn have positive effects on trust in the brand which positively influences loyalty to the brand. Nevertheless, the relationship among customers is what most influences increased brand trust and loyalty. This is consistent with one of the main characteristics of social media which is user-generated content. Also for this reason social media is also called the “people’s media”, which implies that the main objective of social media is to get people together and facilitate interactions among them (Fournier & Avery, 2011). One practical consequence of the research conclusions is that companies, within all the brand community relationships on social media, preferentially stimulate the relationship among customers as a way to increase trust and loyalty to their brands (Laroche et al., 2013)

Some actors categorize brand communities as a tool for marketing relationships (Miller & Lammas, 2010). Contrary to transactional marketing, the marketing of relationships aims to develop long-term relationships with customers, generating trust and creating the conditions to develop customer loyalty.

Specifically with respect to brand communities on social media, fan pages and groups display characteristics of brand communities although with some differences. Consciousness of kind is more intense in groups than on fan pages; members of groups also display a greater sense of moral responsibility. Fan pages are used as a platform to forward complaints and suggestions to the company more frequently than from groups. Based on these aspects, groups characterize identify themselves as brand communities more intensely than fan pages as brand communities.

2.3 Word-of-mouth communication

The concept of word-of-mouth communications also predates the rise of social media, and can be defined as the act of exchanging information among consumers, which is capable of changing consumer perspective with respect to products and services (Katz and Lazarfeld, 1955 cited in Chu & Kim, 2011). Because word of mouth information is generated and transmitted by a source considered more reliable than the persuasive messages generated by business (Feick & Price, 1987), many consumers base their decisions on it when seeking information for making buying decisions. Its influence is greater when the consumer is buying a product for the first time or when the product is relatively expensive, factors that tend to make people do more research, seek more opinions and deliberate longer than they usually would (Bughin et al., 2010).

Bughin et al. (2010) identify three forms of word-of-mouth communication: experiential, consequential, and intentional.

Experiential word-of-mouth is the most common and powerful, typically representing from 50 to 80% of word-of-mouth in any product category. This results from customers’ direct experiences with the product, including situations in which experience does not meet their expectations.

Consequential word-of-mouth occurs when consumers directly exposed to traditional marketing campaigns broadcast messages about them or about the brand they sponsor.

The least common word-of-mouth is intentional. For example, using celebrity endorsements to provoke the generation of positive messages about the product.

The rise of internet-based media favored the development of online word-of-mouth or electronic word-of-mouth, also called eWOM (electronic Word-of-Mouth), a term we will use in this work. Hennig-Thurau et al. (2004) define eWOM as any positive or negative comment made by potential customers, whether past or current, about the product or a company, which remains available to a large number of people through the internet. eWOM can manifest, for example, as product recommendations on a commercial electronic site or in tweets about a product experience. The social networks, in particular, represent an ideal vehicle for eWOM, since through them consumers can freely create and disseminate information about brands and products on their networks composed of friends, colleagues, and acquaintances.

The enormous amount of information presently available dramatically changed the power balance between consumers and companies (Bughin et al., 2010). At the same time that they have more information available to them, consumers have become more skeptical about the advertising and marketing created by the companies. This is reflected in the manner in which people actually make buying decisions. Once they decide to buy a product, consumers initially consider a set of brands due by experience with the product, recommendations or the influence of marketing. Consumers then evaluate these brands using information obtained from diverse sources, and then decide which brand to buy. According to Table 1 below, word-of-mouth has different degrees of influence at each stage of the buying cycle, but it is the only factor that appears as one of the three top influences at all stages.

Table 1 Three main factors that influence whether a product is considered at each stage of the buying process, example from the cellphone market in the US in 2010, %. 

Mature markets Developing markets
Stage 1 Advertising 30 Word-of-mouth 18
Initial consideration Prior use 26 Advertising 17
Word-of-mouth 18 Prior use 15
Stage 2 Information on the internet 29 Word-of-mouth 28
Evaluation Store visits 20 Advertising 26
Word-of-mouth 19 Prior use 13
Stage 3 Information on the internet 65 Word-of-mouth 46
Purchase time Store visits 20 Advertising 40
Word-of-mouth 10 Prior use 9

Values do not add 100% due to percentages for other factors not shown.

eWOM has two big differences from traditional word-of-mouth. The first is its broad coverage for disseminating new information. When word-of-mouth takes the traditional form – through interaction between two people – dissemination is limited by the size of the social network individuals maintain. Considering that on average people have a network no larger than 150 individuals (Hill & Dunbar, 2003), conventional word-of-mouth networks are quickly exhausted. In contrast, eWOM networks provide much greater coverage.

The second difference is the greater ease of monitoring the effects of eWOM compared to traditional word-of-mouth (Kaplan & Haenlein, 2010). This allows better analysis of the impact of eWOM initiatives on tangible business results, for example, sales and profits.

2.3.1 The impact of word-of-mouth communication

The impact of word-of-mouth consumer behavior is a reflection of the message’s content (what is said), of the characteristics of the transmitter (who says it), and the nature of the network to which the message is sent (where it was said). Moreover, it varies by product category (Bughin et al., 2010).

The impact of the message’s content will be greater the more it focuses on the characteristics that influence buying decisions. In a large number of product categories, design and usability are among the main factors. The transmitter’s identity also influences the impact of word-of-mouth communications. It is important for the receiver of the message to trust the transmitter and believe that they know the product in question. Finally, the environment in which word-of-mouth communication circulates is also a factor influencing its impact. Typically, messages that circulate on smaller networks with more trust among their members have a lesser reach but a greater impact than messages that circulate through disperse communities.

Figure 4 below illustrates factors related to the impact of word-of-mouth communication, that is, the power that a recommendation or dissuasion through this medium has to change consumer conduct.

Figure 4 Factors with impact on word-of-mouth communication (adapted from Bughin et al., 2010). 

2.3.2 Word-of-mouth marketing

In order to take advantage of word-of-mouth as a marketing tool, the first decision a company must make is what is the most important dimension for the product in question: the message content (what is said); the characteristics of the transmitter (who says it), or the characteristics of the network on which the message is broadcast (where it was said). For example, for beauty products, the content is the most important dimension, for a retail bank, the transmitter (Bughin et al., 2010).

This second decision is which form of word-of-mouth communication to use: experiential, consequential or intentional.

The incentive for consumers to share positive experiences is the basic measure to generate experiential word-of-mouth. One of the mechanisms available for this is to involve consumers in product development, supported by online communities (Bughin et al., 2010). Due to the propensity of consumers to speak about a product in the early phases of its life cycle, launching new products or new versions of existing products is essential to the generation of positive word-of-mouth.

It is not always the factors that lead to customer satisfaction with a given product that generate the most experiential word-of-mouth. For example, for portable electronic products battery life is one of the major customer satisfaction factors, but this generates less word-of-mouth than factors such as design and usability. Thus, companies that desire to use their customers as a marketing vehicle have to identify the factors with the greatest potential to generate word-of-mouth communication for their products and seek to maximize the performance of these attributes as well (Bughin et al., 2010).

Generating consequential word-of-mouth involves analyzing the factors that impact this type of communication to maximize the return on conventional marketing activities. By understanding the word-of-mouth effect on the channels and content employed and allocating marketing activities according to this criterion, companies can make their customers disseminate marketing messages and increase their coverage and impact.

Using consequential word-of-mouth requires a good dose of interactivity and creativity. Products from low-innovation categories, which generally have difficulty attracting consumer attention, can benefit from this marketing modality which in the last instance is the result of integrating conventional marketing initiatives and online marketing to stimulate sales.

Intentional word-of-mouth campaigns involve identifying influencers who become defenders of the company brand and products. Companies whose business nature permits the individualized identification of customers (for example, cell phone operators or banks) have an easier time localizing influencers and directing their messages to them to be spread in the form of word-of-mouth through their social networks. Companies that cannot identify their customers individually can, for example, have recourse to hosting events with celebrities present to disseminate messages that later will be publicized through the guests’ social networks.

2.3.3 Engagement with eWOM

By publishing information on social networks, companies allow customers to interact socially by commenting, liking or sharing information on their contact networks. Through these interactions, customers voluntarily display the company’s brand or product along with their identification, usually name and photo) and this characterizes eWOM (Chu & Kim, 2011).

The same authors identified the intensity of the relationship (tie strength), affinity (homophily), trust, and interpersonal influences as the main social factors that influence consumer engagement in eWOM on social networks. The occurrence of eWOM on social networks is positively associated with the intensity of the relationship, trust and interpersonal influence and negatively associated with affinity (Chu & Kim, 2011). It is worth noting that the intensity of the relationship influences only the search behavior and broadcasting of opinions, and does not influence their emission. One explanation for this phenomenon is that by generating information, the social network members tend to share experiences on their entire network of contacts, which includes colleagues and acquaintances (weak ties) and friends (strong ties). Another possible explanation is that the social networks are apt to generate information quickly and easily; thus tie strength does not have a big influence when consumers provide information on products to other consumers.

The negative relation between eWOM occurrence and affinity is based on the fact in different situations people value the exchange of information with others with a different profile and formation than their own. This is in agreement with the importance Granovetter (1973) attributes to weak ties.

3 Method

3.1 Investigating the brand community phenomenon through netnography

One of the main objectives of market research is to identify and understand tastes, desires, and influence on consumers’ decision making process. The advent of the internet and online communities has provided new opportunities for market researchers to study consumer preferences, desires and needs through their online community interactions (Kozinets, 2002).

Kozinets (2002) defines netnography, or internet ethnography, as an online market research technique to provide insights on consumer behavior. In other words, netnography is ethnography adapted to the study of online communities. Netnography is quicker, less expensive and simpler than ethnography, as well as less intrusive than other techniques such as focus groups or interviews, and its raw material is the public information available on online communities.

The limitations of netnography lie in its strict focus on online communities, the need for researchers to use interpretive techniques and the lack of complete identification of participants in the online context which can lead to difficulties generalizing the results outside the online community studied. Researchers interested in generalizing the results of the netnography of a particular online group to others must apply assessments of similarity and employ diverse triangulation methods (Kozinets, 2002).

Ethnography is an anthropological method popular in sociology, cultural studies, marketing research, and various other social science fields. It includes both the field work, and the study of distinct meanings, practices, and artifacts of a certain social groups and the representations based on such a study. Ethnography is an inherently open-ended practice, based on the participation in, and observation of a certain cultural scenarios, as well as employing reflection on the researchers ’part. In other words, it depends importantly on the acuity of the researcher and is more visibly affected by the researchers’ own interests and profiles than other types of research.

The internet, in turn, constitutes a new means of social exchange among consumers that allows an unprecedented level of access to consumers’ interactive behavior.

The procedures for carrying out netnography begin with defining the research question, followed by identifying appropriate online consumers for the type of question of interest, and the researchers’ study of the main characteristics of these communities and their participants.

The main characteristics of the communities to be selected are: 1. Greater alignment with the research question; 2. Higher volume of posts; 3. Greater number of active participants; 4. Higher volume of detailed data; 5. Greater number of interactions among members of the type required by the research questions.

The messages to be analyzed will be classified according to two main categories: social or informational, and aligned or not aligned to the research question. The researcher’s analytical efforts are concentrated on the social messages and are aligned with the research question.

The data collection period will be extended based on the recommendations of grounded theory, until there is no more generation of new insights. One important difference between the ethnographic and netnographic methods lies in the observation subject: while the first has the goal of observing the person, the second concentrates on conversations. This distinction is necessary because the characteristics of conversation in netnography are very different from those in ethnography: they are mediated by the computer, are publically available, are generated in text form, and the identities of the participants are much more difficult to discern (Kozinets, 2002).

3.2 Brand community data collection and analysis

Based on the netnographic approach, data collection is characterized by participatory observation, which include familiarity with the brand and its products, joining the community, observing its dynamic and occasionally participating in discussion threads. The netnographic study of both communities in the study encompassed a 12-month period from June 2013 to June 2014.

Reading and categorization of the posts was directed toward identifying the characteristics of the brand community as proposed by Muniz & O'Guinn (2001): consciousness of kind, rituals and traditions, and a sense of moral responsibility.

The indicators used to verify the existence of these characteristics in the community under study were:

    1. Consciousness of kind: the use of the pronoun “us”, demonstrations of emotional connection and pride in belonging to the community;

    2. Rituals and traditions: celebration of the history of the brand or company, exchange of stories by participants involving the brand or company, and the use of jargon;

    3. Sense of moral responsibility: support for use of products and assistance overall.

Posts and comments associated with one or more of these characteristics were identified and their content was copied to document observations. Using the social networks’ own tools some characteristics of the community members involved in the chain of posts, especially those belonging to the list of employees of the company in question.

3.3 Researching the eWOM phenomenon

The metric used to assess the intensity of eWOM generated on a fan page is calculated by the relationship between the indicator “People Talking About This” published by Facebook on the fan page, the number of page fans also available on the fan page.

This relationship is known as the engagement rate. The indicator “People Talking About This” consolidates all the actions a person makes when interacting with a page, for example: liking the page, liking the content, shares, comments, event attendance confirmation, looking at pictures, etc.

Authors such as Kaushik (2011) suggest the alternative use of three metrics to assess the intensity of eWOM generated by a fan page: the rate of applause, the number of likes per post, conversation rates, of the number of comments per post, the rate of amplification or number of shares per post. However, these indicators to not take into account the number of fans, which makes them absolute rather than relative indicators and prejudices a comparison of the engagement rates among fan pages, especially companies from different sectors. For that reason the approach will not be used in this study.

3.4 eWOM data collection and analysis

The BirdSong Analytics tool was used to extract the engagement rates from fan pages during the period page studied. The tool also has a benchmarking database which allows comparisons of the engagement rates for the fan page studied to an average engagement rates for companies in the same sector.

4 Results

4.1 Assessment of the existence of brand communities

Using the three basic characteristics of brand communities as reference points, we found that the pharmaceutical company’s fan page fulfilled the criterion. Indicators are much more superficial for the fashion company, and lead to the conclusion that there is no brand community in this case.

Beginning with consciousness of kind, in examining the pharmaceutical company’s fan page we find many demonstrations of pride and emotional connections with the company and the brand. For example, a member reacted to a post announcing a company award from an important business magazine is “Proud to my <company name>”, In the same discussion thread we find comments such as “very proud” and “I am prouod to be an <associate of the company>”. One post that reported on charitable activity by the company has comments such as “So proud to be a <company name> colleague” and “It is so wonderful to work for a company that shows it cares about others every day”. The author profiles of these comments were analyzed and found that in about 40% of the cases they were employees from different countries of the company under study.

Rituals and traditions are also found in the form of pharmaceutical company posts of old photographs of ancient facilities around the world. Generally, posts are followed by comments of praise by current or former employees (“I work here. So proud of this company”, “I work here, too! Thanks for the picture, it is amazing…” or “not much has changed since then…

The third characteristic of brand communities cannot be found in the fan pages of pharmaceutical companies fan pages due to the nature of the product itself. In this respect it is worth noting that the company removes many comments. The company publishes a notice on its fan page reserving the right to remove comments that reference products, side effects, contain vulgar expressions, constitute medical advice or are totally off the main themes on the page.

The main objective of the fashion company’s site fan page in to direct its members to the company’s electronic site. Company posts are invariably fashion photos with items found in the brand’s virtual store. With a predominantly feminine audience, the comments that follow the post usually praise the photos or express the intent to acquire the items. Note that the company follows a policy of frequently responding to comments, motivating their authors to acquire the company’s products.

In a few situations, customer complaints about difficulties exchanging merchandise, not receiving orders on time, inaccurate charges and the like. In these situations the company does not eliminate comments from the page and responds with a request for more details on the complaint so that it can investigate, at the same time inviting the complainer to continue the conversation in private. In this way, and in a low intensity way only the third indicator for brand communities, the sense of moral responsibility, with their support for community members generally is found by analyzing the company page.

Chart 1 below summarizes the results of the study of existing brand communities on both pages.

Chart 1 Indicators of brand communities at the companies studied. 

Company
Brand community indicators (Muniz & O'Guinn, 2001) Manifestations
(Zaglia, 2013)
Fashion Pharmaceutical
Consciouness of kinf Sense of belonging”; use of pronoun “we”; pride and emotional connection No Yes
Rituals and traditions Celebration of history; exchange of stories; use of jargon No Yes
Sense of moral responsibility Integration and retention of members; support for product use; assistance generally Little No

4.2 Evaluation of eWOM intensity

The determinants of engagement rates can be found in Table 2 below.

Table 2 Engagement rates at the companies studied. 

Company Engagement rate % Average engagement rate of sector % Diference between company and sector Number of companies by sector evaluated
Fashion 3.53 2.48 1.05pp 35,060
Pharmaceutical 0.92 6.44 -5.52pp 115,157

Comparing the two companies, the fashion firm has an engagement rate nearly 4 times higher than the pharmaceutical company. The fashion company’s good performance in the comparison of engagement rates on its fan page also can be seen in the comparison with the average of the sector, having a rate higher than a percentage point, or 42% above this reference.

4.3 Summary of results

The Figure 5 below summarizes the results of the research on brand communities and eWOM for the two companies in the study.

Figure 5 Summary of the results of the companies studied. 

5 Discussion

The popularization of social media made companies include this new set of marketing tools. In opening a channel for dialogue between company and customer and allowing customers to interact among themselves, social media presented new challenges and opportunities for companies. With more information on products, clients witnessed an increase in their power vis-à-vis their relationship with companies (Bughin et al., 2010). Among the diverse opportunities for companies to use social media, and especially social networks, are the construction of brand communities and the generation of electronic word-of-mouth (eWOM).

The formation of brand communities is associated to the strength of ties to customers and a consequent increase in trust and loyalty to the company. The importance of encouraging eWOM lies in its influence on consumer buying decisions. In the context of the social networks, both phenomena are strengthened: companies can create brand communities quickly and at low cost, as well as exploiting the broader reach of word-of-mouth in this medium.

This work examines the Facebook fan pages of two companies from different sectors with very distinct presence on social networks, with a focus on identifying the formation of brand communities and in the generation of eWOM. The first company is an important multinational in the pharmaceutical sector, while the second company is a well-known feminine fashion retailer.

Research on the creation of brand communities used the netnography approach while evaluating the intensity of eWOM generation based on their fan pages using metrics calculated using public information from Facebook itself.

An analysis of the pharmaceutical company’s fan page revealed demonstrations of consciousness of kind among its member (sense of belonging to a groups of peers with a similar mentality) and the practice of rituals and observance of traditions (celebrations of history and exchange of stories involving the brand). These are two of the three characteristics that allow us to identify a group as a brand community (Zaglia, 2013). The third characteristic, support for product use and general assistance to members, does not apply to the case in question since the community rules imposed by the company itself restrict the circulation of information related to medication and illness among its members.

Analysis of the pharmaceutical company’s fan page further reveals that, among the many possible relationships to be exploited in a brand community – customer/product, customer/brand, customer/company and customer/customer (McAlexander et al, 2002) – it only developed two relationships -- customer/brand and customer/company. This despite the fact that relationships among customers have the greatest effect on developing trust and loyalty (Laroche et al., 2013) The company’s reason for not exploring the customer/product and customer/customer relations lies in the policy of restricting, due to regulatory requirements, the circulation of information about prescription drugs, or discussions involving giving medical advice or side effects.

Also on the pharmaceutical company fan page we observe the strong presence of company employees among followers, suggesting that the page also functions to encourage trust and loyalty, not just from customers, but also its collaborators.

Analysis of eWOM generation on the pharmaceutical company page shows low intensity of this kind of communication, even when compared to other companies in the health sector. This is also compatible with company restrictions on its product information, and shows that company strategy for social networks is devoted to creating brand communities. In this case, word-of-mouth that resulted in increased sales was in the realm of the relationship between the company and health professionals, which can be verified outside the context of social networks.

The feminine fashion company, in turn, clearly uses its fan pages to generate eWOM, the characteristics to allow identifying it as a brand community are not observed. There is much coherence between the company’s online marketing initiatives, the way post content on its fan page is an integral part of advertising campaigns on other online channels where the company is active (site, blog, YouTube and Instagram, among others), which permits us to classify their word-of-mouth strategy as consequential (Bughin et al., 2010). According to the same authors, marketing campaigns that generate positive eWOM (which is easy to check in this case through the netnographic study of the company) increase their range and influence.

Generally posts are composed of very attractive fashion photos; their effect is to evoke a high applause rate (DeVries et al., 2012). Moreover, they show the company focus on content as the main factor of impact in the word-of-mouth communication strategy and in the design and usability of their pieces as the most important factor for the buy. We further observe that in the effort to generate eWOM, the company encourages fan comments by responding to the great majority, including those with negative content. This is in accord with DeVries et al. (2012) who found that the both positive and negative comments generated new comments and that also the predominance of positive comments leads to an increased number of “likes”. In one way or another, comments provoke eWOM.

Finally, the issue of using disperse social network like Facebook to generate eWOM by the fashion company merits discussion. According to Bughin et al. (2010), the impact of word-of-mouth is greater when it circulates on more restricted networks where greater trust among members is found. This position, however, is refined by Chu & Kim (2011) who in a study about consumer engagement factors for eWOM on social networks found that in addition to trust the intensity of the tie and interpersonal influence are also engagement factors. The same study, further, identifies that people with little socio-demographic identity (gender, age and education, for example) also engage in eWOM on social network environments. This phenomenon originates in the concept of the importance of weak ties (Granovetter, 1973) who argues that contact with people with different profiles plays a critical role in a vast exchange of information and sharing of ideas, allowing access to information and knowledge of a different king than that circulating on networks where strong ties predominate. Thus, the fact that Facebook is a social network where members have contacts with different levels of ties explains the company’s option to use tools to generate eWOM about its products.

It is not possible to generalize the results due to the size of the sample analyzed and the restrictions intrinsic to the netnographic approach, however they do indicate that both approaches, brand community and WOM, have their applicability in the companies’ social media strategy. Even though the case study points in that direction, it is not possible to conclude that eWOM and brand communities are mutually exclusive approaches on social networks.

Complementary studies in the future would include expanding the analysis of companies present on social media through other vehicles, for example, Twitter or YouTube. They would also analyze how companies use the valuable database they have at their disposal from collecting the information shared with their customers and the data generated by interactions among them.

Financial support: None.

REFERENCES

Ba, S. (2001). Establishing online trust through a community responsibility system. Decision Support Systems, 31(3), 323-336. http://dx.doi.org/10.1016/S0167-9236(00)00144-5. [ Links ]

Bagozzi, R. P., & Dholakia, U. M. (2006). Antecedents and purchase consequences of customer participation in small group brand communities. International Journal of Research in Marketing, 23(1), 45-61. http://dx.doi.org/10.1016/j.ijresmar.2006.01.005. [ Links ]

Boyd, D. M., & Ellison, N. B. (2008). Social network sites: definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210-230. http://dx.doi.org/10.1111/j.1083-6101.2007.00393.x. [ Links ]

Bughin, J., Doogan, J., & Vetvik, O. J. (2010). A new way to measure word-of-mouth marketing. The McKinsey Quarterly, 2, 113-116. [ Links ]

Chu, S.-C., & Kim, Y. (2011). Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. International Journal of Advertising, 30(1), 47-75. http://dx.doi.org/10.2501/IJA-30-1-047-075. [ Links ]

De Vries, L., Gensler, S., & Leeflang, P. S. H. (2012). Popularity of brand posts on brand fan pages: an investigation of the effects of social media marketing. Journal of Interactive Marketing, 26(2), 83-91. http://dx.doi.org/10.1016/j.intmar.2012.01.003. [ Links ]

Feick, L. F., & Price, L. L. (1987). The market maven: a diffuser of marketplace information. Journal of Marketing, 51(1), 83-97. http://dx.doi.org/10.2307/1251146. [ Links ]

Fournier, S., & Avery, J. (2011). The uninvited brand. Business Horizons, 54(3), 193-207. http://dx.doi.org/10.1016/j.bushor.2011.01.001. [ Links ]

Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360-1380. http://dx.doi.org/10.1086/225469. [ Links ]

Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word‐of‐mouth via consumer‐opinion platforms: what motivates consumers to articulate themselves on the Internet? Journal of Interactive Marketing, 18(1), 38-52. http://dx.doi.org/10.1002/dir.10073. [ Links ]

Hill, R. A., & Dunbar, R. I. M. (2003). Social network size in humans. Human Nature, 14(1), 53-72. PMid:26189988. http://dx.doi.org/10.1007/s12110-003-1016-y. [ Links ]

Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53(1), 59-68. http://dx.doi.org/10.1016/j.bushor.2009.09.003. [ Links ]

Kaplan, A. M., & Haenlein, M. (2011). Two hearts in three-quarter time: how to waltz the social media/viral marketing dance. Business Horizons, 54(3), 253-263. http://dx.doi.org/10.1016/j.bushor.2011.01.006. [ Links ]

Kaushik, A. (2011). Best social media metrics: conversation, amplification, applause, economic value. Recuperado em 7 Fevereiro 2011, de https://www.kaushik.net/avinash/best-social-media-metrics-conversation-amplification-applause-economic-value/Links ]

Kozinets, (2002). Robert V. The field behind the screen: using netnography for marketing research in online communities. Journal of Marketing Research, 39(1), 61-72. http://dx.doi.org/10.1509/jmkr.39.1.61.18935. [ Links ]

Laroche, M., Habibi, M. R., & Richard, M.-O. (2013). To be or not to be in social media: How brand loyalty is affected by social media? International Journal of Information Management, 33(1), 76-82. http://dx.doi.org/10.1016/j.ijinfomgt.2012.07.003. [ Links ]

Larson, K., & Watson, R. (2011). The value of social media: toward measuring social media strategies. In Proceedings of the ICIS 2011 (pp. 1-18). Shanghai, China. Paper 10. [ Links ]

McAlexander, J., Schouten, J. W., & Koenig, H. F. (2002). Building brand community. Journal of Marketing, 66(1), 38-54. http://dx.doi.org/10.1509/jmkg.66.1.38.18451. [ Links ]

Messinger, P. R., Stroulia, E., Lyons, K., Bone, M., Niu, R. H., Smirnov, K., & Perelgut, S. (2009). Virtual worlds—past, present, and future: New directions in social computing. Decision Support Systems, 47(3), 204-228. http://dx.doi.org/10.1016/j.dss.2009.02.014. [ Links ]

Miller, R., & Lammas, N. (2010). Social media and its implications for viral marketing. Asia Pacific Public Relations Journal, 11(1), 1-9. [ Links ]

Muniz, A. M., Jr., & O'Guinn, T. C. (2001). Brand community. The Journal of Consumer Research, 27(4), 412-432. http://dx.doi.org/10.1086/319618. [ Links ]

Tapscott, D. (2008). Grown up digital: how the net generation is changing your world HC. New York: McGraw-Hill. [ Links ]

Zaglia, M. E. (2013). Brand communities embedded in social networks. Journal of Business Research, 66(2-2), 216-223. PMid:23564989. http://dx.doi.org/10.1016/j.jbusres.2012.07.015. [ Links ]

Zhou, Z., Zhang, Q., Su, C., & Zhou, N. (2012). How do brand communities generate brand relationships? Intermediate mechanisms. Journal of Business Research, 65(7), 890-895. http://dx.doi.org/10.1016/j.jbusres.2011.06.034. [ Links ]

Received: April 30, 2015; Accepted: March 10, 2016

Creative Commons License Este é um artigo publicado em acesso aberto (Open Access) sob a licença Creative Commons Attribution, que permite uso, distribuição e reprodução em qualquer meio, sem restrições desde que o trabalho original seja corretamente citado.