1Introduction

Word-of-mouth (WOM) is “an interpersonal communication in which a sender spreads a message to receivers” (Bao, Chang 2014, p. 21). The same idea when applied to the Internet becomes electronic word of mouth (eWOM), a 21st century phenomenon.

The power of WOM is so well known that in 2004 the Word of Mouth Marketing Association (WOMMA) was founded in order to lead the WOM industry through advocacy, education, and ethics. According to WOMMA (2014),WOM is the driving force behind 13% of sales, while paid marketing in total accounts for 20-30% of sales.

Online consumers have more power than do other consumers and this difference may even be increasing. In fact, thanks to the Internet, the relation between firms and consumers has changed dramatically and now this relation is more favourable to consumers (Kucuk, Krishnamurthy 2007). Everyone, anywhere, at any time is able to express their opinion.

Above all, WOM has a huge impact on the service industry, where the potential customer needs information in order to choose which service to purchase. The tourist industry is one of the main sectors where WOM has proved its potential, as a service, people need opinions so that they can choose a hotel, a restaurant or cruise.

Electronic WOM (eWOM) plays an important role in electronic marketing (e-marketing) nowadays because comments can evoke emotion and affect behaviour. The real motivation to generate information on the Internet (Ho, Dempsey 2010) is the need: to be part of a group, to be individualistic, to be altruistic and for personal growth. Being part of a group and being altruistic are more relevant to the benefit of the group, and being individual and personal growth are more related to personal values. Consumers generate and distribute information and disinformation, which can lead to a response from other consumers or enterprises.

In this scenario, the purpose of this chapter is to clarify the main points for both parties (companies and consumers) and to provide a holistic perspective on the eWOM world that affects marketing strategies. Firstly, by means of a comparison between WOM and eWOM so as to comprehend the differences and relationships between offline and online channels and how information is conveyed. Secondly, the role of influencers through online comments is shown, as well as the value of positive and negative comments. Thirdly, the three key variables (trust, credibility and persuasiveness) are examined together with their interconnection in eWOM. Fourthly, the impact of eWOM in brand reputation is outlined, where disinformation is highlighted as well as the use of social networks. Finally, an insight is provided into how information is presented in eWOM and the benefits derived.

2Comparison between WOM and eWOM

User-generated content is an ensemble of positive or negative comments (Cheong, Morrison 2008; Gretzel, Yoo 2008). Overall, WOM is the provider of this content.

It can be argued that there are two different ways of spreading information and we can classify them into two distinct groups: WOM in-group (close friends or family) and WOM out-of-group (actors near a person’s social, familial, work and collegial circles) (Brown, Reingen 1987). Moving one-step forward, eWOM could affect the WOM out-of-group in a more extensive way, because it has evolved in reaction to technology, and an individual has access to any information written by any other individual in the world. Actually, eWOM out-of-group also makes reference to contact with people whom the individual does not know (Abrantes et al. 2013).

The number of internet users is sharply increasing as well as the number of connections between them. The possibilities of augmenting eWOM out-of-group is more relevant because of its much larger audience. The mathematical relation is that of one individual to the population at large.

The media used to spread information is different between WOM and eWOM. The main channel involved in eWOM is social media. In contrast, WOM favours face-to-face connection as direct interaction rather than more distanced means of spreading information.

In the study “Global Trust in Advertising” by Nielsen (2015), consumers respond more to “recommendations from people I know” as a first choice. In second place comes “the branded websites” and in third “consumer opinions posted online”. As table 1 shows, among the top six trusted ways of advertising, only the fifth affects WOM directly, while eWOM solely applies to the second, third and sixth positions.

Table 1: Top Six Positions in Trust Advertising

Keller and Fay (2012) reinforced Nielsen’s results regarding “recommendations from people I know”. As human beings, interpersonal relationship is the key to WOM. However, 90% of conversations are offline (WOM through face-to-face conversations) and only 8% online (eWOM). Is it possible to confirm that eWOM has a deeper impact than WOM?

WOMMA (2014) asserted that offline WOM is responsible for 2/3 of the impact, while online only accounts for 1/3. However, they both amplify the effect of paid media by 15%. Compared to traditional advertising, WOM has an immediate impact, especially in the first two weeks. In the movie industry, eWOM particularly affects the first week’s box-office revenues and after the second week both WOM and eWOM have a direct influence on revenues (Bae, Kim 2013).

The “go viral” effect is higher in eWOM than WOM. As mentioned before, the huge number of users on the Internet is a useful means of spreading information and thus the “go viral” has a higher potential in eWOM than WOM. However, it is worth noticing the close interconnection between WOM and eWOM, where the omnichannel is latent, because a face-to-face comment can be included on a website and online information can be broadcast in a TV programme. The same information and disinformation may be spread through diverse channels.

If there is a trend to use omnichannels, how can enterprises keep track of where information concerning them is located? Unfortunately, there is no direct tool for marketers to control both online and offline channels (Allsop et al. 2007). In the case of eWOM, there are several social media monitoring bodies such as e.g. Netvibes, Datashif, UberVU. Unfortunately there is no consensus on which is the most appropriate tool to receive feedback and various companies, marketers and researchers have tackled the problem without any relevant success.

Both WOM and eWOM studies on communication agree that a favourable comment increases the probability of purchase and unfavourable word of mouth has the opposite effect (Arndt 1967; Ho, Dempsey 2010). Reading comments is a mean to reducing uncertainty. As a general rule, in the off and online world, the principle of saving time is of paramount importance, consumers try to cut down on the time spent on searches by using the comments of other like-minded users or by asking for information.

Communication through both channels has the same direction: one-to-one, one-to-many and many-to-many. While in face-to-face communication, information assumes an oral format, in electronic communication information is written and endurable (Barreto 2014). However, written communication is more effective because it leads senders to describe products and brands more accurately through a self-enhancement effect (Berger, Iyengar 2013).

Several researchers agreed that anonymity is a unique characteristic in eWOM (Breitsohl et al. 2010; Cheung et al. 2008). However, in WOM the sentence “someone told me”, also implies anonymity, and this feature is made even clearer on the Internet. It is also worth noticing that anonymity provides a greater opportunity to formulate misleading information, because the source is anonymous and so cannot be verified.

Besides, people often make their decisions after consulting online information (Lee 2009). Therefore, eWOM affects not only online purchases, but also those in the real world (figure 1). The opposite effect is also well known by companies and mostly affects local commerce, being detrimental to their sales. It is common practice for consumers to visit a small retailer only for the purpose of seeing a product recommended online or offline physically and then to purchase it online.

Although eWOM is gaining in popularity, marketers should not believe that eWOM has replaced WOM (Fulgoni, Lipsman 2015). Offline and online communications are complementary and marketers need to see both channels in a holistic way. Enterprises are adapting themselves to the present situation because consumers use cross-channel information. Years ago, business focused on developing multi-channel selling approaches and now they are turning into omnichannel strategies, where consumers check information on offline and online channels and then they decide where to buy. The IBM Omnichannel Capability Index (2015) pointed out the need of providing a shopping experience independent of the chosen channel. In that case, the interconnection of eWOM and WOM is crucial to consumers due to their omnichannel behaviour.

3eWOM: Negative vs Positive Comments

Negative comments are more persuasive than positive reviews, particularly, among females (Bae, Lee 2011a; Jeong, Jang 2011). Negative reviews have a great impact on consumer-based brand equity. Contrary to popular belief, a bad comment not only deeply affects a small company’s equity, but also that of renowned enterprises (Bambauer-Sachse, Mangold 2011). Thus the size of a company does not render it immune to this effect.

Negative eWOM (eNWOM) postings have a greater linguistic impact on users. This language normally expresses anger on the part of the poster and connects more to their frustrations (Gheorghe, Liao 2012). Negative emotional expressions tend to have less of an impact than might be expected because consumers believe that those expressions are based on an irrational disposition (Kim, Gupta 2012). eNWOM is sometimes perceived as disinformation, especially when it is placed among numerous positive eWOM (ePWOM).

Negative eWOM has a more significant effect on experience goods than on search goods and even more so if the website’s reputation is taken into account. These negative comments are more reliable on established websites (Park, Gretzel 2007; Park, Lee 2009).

The real problem with eNWOM is the fact that enterprises do not perceive a negative comment as a chance to improve. The geniality will transform an eNWOM into an ePWOM and create a real asset for the company. Kikumori and Ono (2013) identified that an eNWOM may have a positive impact.

However, if ePWOM appears together with information connected to a promotion, it is more persuasive than negative eWOM (Zhang et al. 2010). Positive expression in a single positive comment does not lead to positive impact (Kim, Gupta 2012).

A basic human motive (self-enhancement) guides consumers to create ePWOM, while NWOM is merely transmitted (De Angelis et al. 2012). Statistically speaking an ePWOM occurs three times more often (3 to 1) than an eNWOM (East et al. 2007). Customers spread eNWOM when there is a serious failure (Wang et al. 2014). A satisfied consumer is more prone to writing a positive comment than an unsatisfied customer is prone to writing a negative comment. However, in the study by Cheung et al. (2007) cultural differences were found: Chinese eNWOM is based on venting anger and punishing the business organization, while US eNWOM will seek compensation and the correction of a bad situation.

Through positive comment, the sender has a deep influence on the receiver. The two-step flow communication (Katz 1957) also applies to eWOM. In this case, there is a push communication relation (figure 2), where the aim is to spread information through intermediaries and to push consumers to buy or even to get them to advise other consumers to do so. Both manufacturers and producers need to find the best influencer with the best impact on potential customers (Arenas-Gaitan et al. 2013). When influencers really believe that a service or product could benefit consumers, their comments improve the credibility of the brand and increase purchase intention. Fashion bloggers are well known as a best influencer. A good example is Chiara Ferragni with more than three million followers on Instagram and 500,000 unique visitors of her renowned blog “the blonde salad” every month. Each time she recommends a certain product it sells out in a very short space of time. Harvard Business School wrote a business case based on Chiara Ferragni’s success.

Such influencers are on the whole considered as leaders. When their messages are accurate and comprehensive, followers react more strongly to this information (Bao, Chang 2014; Godes, Mayzlin 2009). Influencers have the role of leadership and that is why manufacturers and producers should find a leader to spread their information so as to profit from it (return on investment in emarketing) or generate a multiplier or ripple effect. Overall, an authoritative opinion maker entices future customers or fosters a behavioural outcome. However, it remains unclear whether influencers have been paid by the enterprise to write positive comments. The market rate for influencers is around €6,000 to promote a product or a brand.1

A problem with the influence of eWOM arose when it was discovered that some hotels created fake comments, which is an illegal practice and forbidden in Britain, Ireland, France, Italy and Germany. This malpractice continues because the average payment for hiring somebody willing to make such comments is around €8 per comment. Li et al. (2014) demonstrated some patterns that reveal the authenticity of a message. A fake comment may include excessive use of superlatives and a lack of detail and description.

To sum up, eWOM is created through comments, where the information can constitute eNWOM or ePWOM. Both can affect purchases, eNWOM reduces the percentage of sales, whereas ePWOM has the opposite effect.

4eWOM and Variables

The key elements to effective persuasion on the Internet are credibility and trust (Teng et al. 2014). Credibility, trust and persuasiveness are variables that are closely interconnected (figure 3). Although some researchers have tried to focus their studies on one variable (Cheung et al. 2009; Pan, Chiou 2011), their findings proved that one variable cannot survive without the other. If a comment is credible, readers rely on it and the message can persuade them to react by following its recommendation, as for example, encouraging the buying of a product or just improving the brand’s reputation. That way, the overlap of the three variables is shown and they act as a chain of events.

4.1eWOM and Credibility

As a rule, there is a push relation between positive comments, credibility and purchase intentions. A positive comment has a positive impact on credibility and influences purchase intention (see figure 4, Chih et al. 2013). However, this simple model has some moderators that enhance or temper credibility.

On the Internet, the credibility of the creator of any information might suffer due to lack of face-to-face contact. The more positive comments are presented on a website, the higher its potential to undermine the credibility of the site, although it may result in higher scores (Doh, Hwang 2009; Reichelt et al. 2013). Not only negative, but also positive comments could be detrimental to the credibility of the source.

However, if eWOM is customized (visual cues, numbers), it becomes more trustworthy, due to the fact that consumer experiences are relevant (Ha 2002; Teng et al. 2014). Users’ acceptance of online reviews as reliable increases for comments if the user perceives the post as useful or recognises social ties with the poster (Teng et al. 2014).

Another variable affecting credibility is product type. A review of an experience product is most credible when it appears in an online community and is given more credit than a search product comment when it appears in a consumer-developed review site (Bae, Lee 2011b).

The previous experiences of participants as well as the quantity and articulation of posts are major factors. Readers of information may give it more credit when they are able to compare different opinions, as in that way they have the opportunity of choosing which is more convincing (O’Reilly, Marx 2011).

The initial model in figure 4 has moderators that affect credibility and the final decision (figure 5).

5eWOM and Brand Reputation

In social discussion eWOM is an indicator of the reputation of a brand, be it a company or the author of a book, and it even affects complementary goods (Amblee, Bui 2011).

In the banking sector, loyalty and ePWOM derive from user-friendly web development and satisfaction on the part of the customer (Casaló et al. 2008). However, several researchers have drawn similar conclusions regarding the relationship between technology readiness and eWOM (Chen 2011).

Gender is a variable that directly affects brand reputation, because women are more willing to post brand-related content on Facebook than men (Choi, Kim 2014).

In an eWOM group, if there is a strong connection between the stakeholders, they react less aggressively when their brand receives eNWOM and tend to downplay criticism, because they regard the brand as if it were an integral part of the group (Chang et al. 2013).

Dissatisfying product or service experiences produce eNWOM, which is strongly detrimental to the company’s reputation and sales when the company does not take immediate action to solve the problem of unsatisfactory product or service experiences (Nyer, Gopinath 2005; Burton, Khammash 2010). However, if the company treats the complaint adequately, this rapid reaction increases consumer loyalty and satisfaction level (Hong, Lee 2005). After eNWOM, prompt feedback reduces the overall impact on the brand (Shimabukuro Sandes, Torres Urdan 2013).

The better known and bigger a company is, the higher the number of antibrand sites that appear, which are deleterious to the brand image (Krishnamurthy, Kucuk 2009). In those anti-brand sites, the language used has a marked ideological and transactional component.

Post-purchase reviews written by e-communities can create harmful rumours. Thus, companies have to pay particular attention to negative feedback and eNWOM in order to safeguard both their brand and their online reputation.

Brands really need to promote e-interactivity with their potential consumers or potential eWOM senders to protect their image. Harmful rumours might be prevented if the brand automatically reacts reasonably. Otherwise, the snowball effect (Brooks 1957) may impact them and disinformation can increase in a way that the brand cannot control.

6eWOM and Social Networks

Social networks can be considered as a broadcast medium and, of course, they play a main role in eWOM and create consumer-to-consumer communication (C2C). However, there is a difference in the way information is presented: in the typical way as on Facebook or Twitter, and discussion communities such as e.g. TripAdvisor. Researchers consider the first group as a provider of information in a social context while the second is considered a source of information (Arenas-Gaitan et al. 2013). The main difference is the interconnection among readers on Facebook (replies are possible) and this is not the case on TripAdvisor.

There has been much debate (de Cristofaro et al. 2014) regarding recent practices where a company is able to buy e.g. 10,000 likes for around €36, which is why even the comments a potential customer may find within a social network make them wonder whether they have been bought.

Individuals are primary actors in social networks (SNs) and, they construct online communities around their opinions and contributions where they can identify themselves as part of a group (Brown et al. 2007).

Social networks provide the likelihood of expanding social circles, but when community members use the fan page its main purpose is to collect information to be used by enterprises. Facebook collects personal data from users which they then sell to attract advertisers. However, users tend to express their preferences by clicking on “Like” rather than sharing the information within their social circle (Chen 2011).

What happens with those social networks such as Facebook where the user can only “Like” or do nothing? Facebook users tend to be more positive than negative (Chen et al. 2013), because they do not have the possibility to express a simple “Not Like” when they do not agree. They only have the chance to express “Like” to a negative comment.

In SNs like Twitter, those users who are motivated by the brand, the so called “brand followers”, serve as role models and tweet or retweet brands’ links (Chu, Sung 2015). In fact, the information on a SN has higher impact on intention and trust than the information included on a firms’ website (Meuter et al. 2013).

However, up to now there are a number of questions left unanswered which presents challenges for new research: how can a company monitor each fan in terms of revenue? What is the best way of measuring social networks? How can thousands of fans be converted into profit?

7eWOM and Information

As a rule, eWOM is based on recommends, shares, likes and comments. However, comments can be classified not only according to positive or negative information, but also according to their content. After analysing information on numerous conversations in discussion forums, Andreassen and Streukens (2009) considers that, they can be divided into four main categories:

As can be seen, these four main categories relate to a final business purpose. Information request aims at a prospective purchase, usage experiences and comments relating to new products are a response from buyers and can encourage potential consumers. Finally, business practice issues are closely related to the image of the enterprise and can boost sales.

Other researchers such as Hung and Li (2007) have highlighted four categories for the responses found in virtual communities:

There is not much consensus about how to generalize information in eWOM. It seems apparent that a comment can facilitate the choice of brand and product and is the driving force behind consumer persuasion. In this process, experience is used as a mediator as well as business practice.

eWOM has changed the buying environment. The amount of information that a consumer can access has developed new ways of organizing information and specialized sites such as e.g. TripAdvisor, where the buyer can compare prices, evaluate other visitors’ opinions and classify a service not only according to the price variable. e-marketing strategists see the need to identify more variables in order to be able to apply the best strategy. An example might be the motivation behind the creation of fake comments that create disinformation (Levine et al. 2010).

8eWOM and Benefits

Who really benefits from the information on the Internet?

On the one hand, individuals transmitting information satisfy self-needs such as being part of something noticeable. They also increase their social needs and intentions, such as helping the community and bonding socially (Alexandrov et al. 2013). By helping out another member of a virtual community the communicator enhances their self-worth (O’Reilly, Marx 2011).

Consumers use eWOM because they need to avoid uncertainty and risk in their purchases (Chan, Ngai 2011; Goldsmith, Horowitz 2006; O’Reilly, Marx 2011).

In contrast, customer participation through eWOM influences behavioural outcomes, which also affects firms’ outcomes by increasing efficiency and generating higher revenues (Bolton, Saxena-Iyer 2009). When a product receives a positive evaluation from consumers, as for example on Amazon, it is more likely to be purchased (Leskovec et al. 2007).

eWOM has been recognized as a powerful driver of purchaser intention that really benefits enterprises. In fact, virtual communities foster attitudes and purchase intentions (Huang et al. 2012). As various researchers have confirmed purchases, as well as brand image and reputation, are much influenced and enriched by eWOM (Jalilvand, Samiei 2012).

Regarding the relation between consumers and firms, eWOM helps to enhance conative and action loyalty levels (Roy et al. 2014). The largest benefit of loyalty is an increase in long-term sales as well as the fostering of repurchases.

9Conclusion

Although there are several factors that influence eWOM, this chapter tries to take a holistic approach, because ultimately the various effects are interconnected and it is very difficult to assert that any single factor is the trigger in eWOM. EWOM creates both information and disinformation, because as consumers we cannot clearly identify valid information, and firms cannot reliably identify whether a comment is genuine or a fake.

In eWOM, influencers have a leading role and are a mediator between enterprises and potential customers, but they can also create disinformation because some may be paid to assert something positive even when they themselves are not convinced of it.

ENWOM needs to be followed and attended to, because it directly affects e-reputation. A prompt response may prevent a potentially undesirable snowball effect. However, too much ePWOM is also suspicious and can project a distorted image of a company.

Virtual communities are very relevant to companies and they can be a crucial asset for them in critical situations. Social networks can be a tool to promote such virtual communities.

The information within individual comments is difficult to classify, because the amount of information on the Internet is so huge and there are few studies in this area.

There are many unknown factors in this field which need to be examined and clarified that are fundamental for companies in order for them to convert the information into a source of revenue. Although there are several studies of eWOM, there remain gaps that require further research.

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