Consumers’ Reliance on Product Information and Recommendations Found in UGC

Hyuk Jun Cheong, Margaret A. Morrison

The University of Tennessee


In the time since the advent of the Internet, the influence of online recommendations on consumer decision making has attracted great attention. YouTube and sites with blogging capabilities, such as MySpace and Facebook, are growing rapidly and frequently feature comments about brands and products. These comments, whether positive or negative, represent a form of user-generated content (UGC). Although recent research on peer recommendations considers electronic word of mouth, few studies focus on UGC. Using interviews with 17 participants, this study examines consumers’ opinions of online recommendations embedded in UGC compared with those of producer-generated content.


The Internet plays a significant role in the lives of millions of people in the United States (Thorson and Rodgers 2006), and many Americans consider it a necessity whose use extends to nearly every aspect of their lives. They read newspapers and magazines online, manage their bank accounts, locate information easily, monitor the lives of others, and develop social networks through online forums or sites such as MySpace and Facebook.

Another common use of the Internet is to purchase and bargain for products. Marketing communications thus have changed significantly as marketers search for ways to communicate with consumers through cyberspace and in light of their common online activities (Rogers and Allbritton 1995). These changes have induced marketers to find optimal ways to use cyberspace when promoting their products and encouraged scholars to study the Internet from the perspectives of their disciplines. Marketing and advertising scholars tend to focus on the Internet’s virtual communication roles and research various areas, including viral marketing, electronic word-of-mouth marketing (eWOM), online advergames, and interactive advertising (Fong and Burton 2006; Porter and Golan 2006; Winkler and Buckner 2006). Yet Goldsmith and Horowitz (2006) note that researchers have only recently begun to study online content created by users and its implications for marketers. study adds to this area of research by examining how consumers view user-generated content (UGC) pertaining to products found on Web sites.

In 2006, Time Magazine declared “You” the “Person of the Year,” noting how individuals express power and take influential roles in societies in which online communications are prominent (Grossman 2006). This declaration has become meaningful for both scholars and marketers. Time Magazine‘s choice of “You” instead of specific persons resulted from the vast number of ordinary people who express themselves through blogs (i.e., diary-style Web sites that generally offer observations and news, as well as commentary and recommended links; Johnson and Kaye 2004), video-sharing Web sites like YouTube, and online social communities such as MySpace and Facebook. These media have generated spheres of influence (Goldsmith and Horowitz 2006; Johnson and Kaye 2004; Steyer, Garcia-Bardidia, and Quester 2006) that encompass millions of users. According to Fulgoni (2007), 63 million people in the United States read at least one blog a month, and 24 million people visit YouTube. These huge numbers suggest not only growth in online communities but also the emergence of new types of online media that originate with consumers and that differ from more traditional Web sites in terms of who is generating the content for the sites. For example, content on YouTube and many blogs usually is generated by “ordinary” people-not trained marketers-who represent end users of products or services. For the purpose of this study, content in such Web sites is referred to as user-generated content (UGC). Conversely, content generated by producers (i.e., marketers of products) is characterized as producer-generated content (PGC).

Although UGC has been closely aligned and often confused with eWOM, the two differ depending on whether the content is generated by users or the content is conveyed by users. For example, footage on YouTube that is generated and posted by users is UGC. However, an Internet user who sends her friends a link to a YouTube site is engaging in eWOM. If the content conveyed has been generated by users, it can be both UGC and eWOM. Likewise, if the owner of a digital camera writes an opinion about his or her camera on a consumer review Web site, that opinion represents a type of UGC, because the content originates with the user. If a video including the recommendation of the camera, generated by that user, gets posted on YouTube, it again is considered UGC. However, once the video is e-mailed to other Internet users by an acquaintance, it becomes eWOM. Thus, though UGC and eWOM are distinct concepts, they are related; to be successful, eWOM depends on the dissemination of content, and UGC has less influence without eWOM.

A related issue deals with marketers’ lack of ability to “control” UGC sites, a definitive difference from PGC. Johnson and Kaye (2004, p. 624) note that “bloggers are not bound by standards of objectivity; most have strong views that they express openly.” Thus, UGC runs the spectrum from positive to negative. When UGC is negative, it can have harmful implications for building and sustaining a brand’s equity, an issue compounded by the fact that readers of UGC may consider it more credible than content that originates with the producer (e.g., brand advertising). Johnson and Kaye (2004) specifically find that readers of blogs, a form of UGC, judge them as highly credible, especially compared with traditional media. However, their study considers only generalized blog content, not product-focused UGC or online PGC. Lack of information about the credibility of these two different types of Web sites, as well as the influence of positive and negative UGC, highlights the need for marketers to study product-focused UGC to understand its influence relative to that of PGC.

The dearth of information on product-focused UGC and users of UGC, and the myriad of issues surrounding them, prompts this study to investigate consumers’ attitudes toward brands or products embedded in UGC.

Literature Review

eWOM and UGC

Before the advent of cyberspace, scholars such as Katz and Lazarsfeld (1955), Brooks (1957), Bearden and Etzel (1982), and Rogers (1983) researched face-to-face word-of-mouth (WOM) communication (Fong and Burton 2006; Lam and Mizerski 2005). In a seminal study, Katz and Lazarsfeld (1955) examine the relationships between opinion leaders and their followers and find that interpersonal relationships are much more influential than mass media when people evaluate political candidates. Furthermore, this influence extends beyond politics and to purchases of household goods and food.

When consumers pass along product-focused information to others, WOM (and its online equivalent, eWOM) becomes a key factor for marketers. Over a typical week, as Keller (2007) notes, an average American consumer participates in 121 WOM conversations, during which specific brand names get mentioned 92 times. Arndt (1967, p. 3) defines WOM as the “oral, person to person communication between a receiver and a communicator whom the receiver perceives as non-commercial, concerning a brand, a product or a service.” Conclusions from early studies of WOM suggest that it has a significant influence on consumers’ decision-making processes, especially when they look for information about products, brands, or services (Fong and Burton 2006). According to Brooks (1957), friends and acquaintances-those people to whom consumers talk every day-are the most influential sources in terms of opinions and subsequent behaviors, and personal contacts provide the most effective form of WOM. The influence of WOM is particularly strong when consumers consider purchases of new types of products or services with which they have no prior personal experience (Engel, Blackwell, and Kegerreis 1969).

Reingen and colleagues (1984) find that proximity also plays a role in WOM; if a group of people live together, their chance of exposure to WOM increases, and thus, their brand preferences are more similar than those of people who do not live together. Support and justification for decisions, social status, social power, and need for information all have been identified as major factors that motivate WOM communications (Gatignon and Robertson 1986; Lam and Mizerski 2005). Moreover, WOM emerges as more persuasive than advertising (Goldsmith and Horowitz 2006), especially print advertising (Herr, Kardes, and Kim 1991). However, existing literature lacks studies that specifically compare online UGC and PGC about products.

Another stream of research examines positive and negative WOM communications and identifies the people most likely to engage in product-related WOM (Anderson 1998; Blodgett, Granbois, and Walters 1993; Mahajan, Muller, and Kerin 1984; Marsha 1984; Weinberger, Allen, and Dillon 1981a; Weinberger, Allen, and Dillon 1981b). For example, Anderson (1998) proposes a utility-based model with a U-shaped function that captures the tendency for very dissatisfied and very satisfied customers to engage in WOM communications. Bowman and Narayandas (2001), examining negative WOM and customer loyalty, find that customers who describe themselves as loyal are more likely than less loyal customers to engage in positive WOM. However, these authors also find that loyal customers tend to engage in WOM when they are dissatisfied (Bowman and Narayandas 2001). This aspect of WOM extends to eWOM as well; in a study of those consumers who post on product review Web sites, users report that extreme dissatisfaction or extreme satisfaction with a product purchase experience provide the main factors leading them to post (Bailey 2005). These findings obviously have implications for the current study, because negative WOM logically conflicts with attempts to manage brand communications.

Aspects of the Internet also lend themselves well to eWOM communication. Through virtual communities, consumers extend their social networks to people they have never met in person, then seek out these people regularly for their opinions about products and services. This process exists both for virtual acquaintances with whom consumers have established relationships and for more public forums, in which users might not “know” one another but are connected through some common interest (Fong and Burton 2006). Dellarocas (2003) calls this phenomenon a “WOM revolution.”

In addition, where consumers encounter eWOM provides an important concern for marketers. Sussan, Gould, and Weisfeld-Spolter (2006) reveal that if the information relates to specific products, eWOM is more effective when consumers find the information on a third-party Web site, independent of the company to which the content relates. This finding suggests that the context in which eWOM appears influences perceived effectiveness.

Because many brands and products appear in the footage of sites such as YouTube, MySpace, and Facebook or get discussed on blogs or in discussion forums, marketers’ interest in UGC has been growing. Despite this growing attention, little research investigates the influence of UGC. Furthermore, the research that does exist tends to focus exclusively on aspects of UGC on discussion/forum-type Web sites or Web sites originating with product producers, offering little insight into how this material compares with PGC. The current study therefore expands on previous research by examining the credibility of UGC relative to PGC.

Theoretical Perspective

Since the 1940s, researchers have studied the influence of source credibility on interpersonal influence. In a study investigating the influence of media on voting habits, Lazarsfeld, Berelson, and Gaudet (1948) indicate that very few voting choices change as a result of the mass media. Instead, people tend to be influenced more by face-to-face contacts with other people (Lazarsfeld and Menzel 1963). The two-step flow model of communication stems from this idea; that is, a transfer of information occurs from the mass media to opinion leaders, and influence then spreads from opinion leaders to their followers (Rogers 1983). Lazarsfeld, Berelson, and Gaudet (1948) define opinion leaders as those people who are interested in new issues and tend to diffuse their opinions about them. Opinion leaders also can be divided into two groups: those who influence others in limited spheres and those who influence others in ways that are broader in nature (Merton 1968). The concept of opinion leaders matters greatly for marketers seeking to harness the power of UGC, because “consumer opinions, once expressed online, can be long-lasting and far-reaching, and these opinions have been shown to have an effect on purchase choice” (Graham and Havlena 2007, p. 428).

When marketers present a new product or a newly launched brand, they consider both traditional and nontraditional media in which to place advertising. Nontraditional media, especially for younger consumers, typically include (but are not limited to) the Internet and its associated channels, such as cellular phones, PDAs, and interactive television. Not surprisingly, in response to the widespread availability and growth of computer-based and digital technologies, studies of opinion leaders have evolved to include computer-mediated communication, particularly that related to the Internet (Wellman 2001). Consumers able to access two-way communication networks, such as the Internet, potentially can influence one another more than those who have only traditional, one-way channels. In face-to-face relationships, an opinion leader typically can influence fewer than 12 people (mostly either family members or acquaintances). However, with the advent of the Internet, opinion leaders have acquired the power to influence unlimited numbers of people (Lyons and Henderson 2005). Although the Internet certainly extends the potential “stage” of an opinion leader, most studies on opinion leadership continue to focus on face-to-face relationships (Lyons and Henderson 2005). However, the concept of opinion leaders has implications for understanding UGC.

One of the first scholarly research studies to describe online interpersonal influence and eWOM, conducted by Senecal and Nantel (2001), examines how opinion leaders and followers interact in cyberspace. Smith, Menon, and Sivakumar (2003) also investigate the influence of peer-to-peer recommendations on decision making. They find that recommendations from both experts and regular people with “tie strength” have relatively the same influential power. Godes and Mayzlin (2004), in their analysis of the content of posted messages from usenet newsgroups relative to the success of new television shows, demonstrate that the amount and dispersion of communication relates to a show’s success. Senecal and Nantel (2004) also conduct an experimental study of consumers’ use of online recommendations; according to their findings, consumers who receive positive recommendations about products are twice as likely to purchase the recommended products as other people.

Consumers also seek information about new products from opinion leaders for various reasons. Goldsmith and Horowitz (2006) identify eight different motivations for online opinion seeking before purchase: (1) reduce risk; (2) because others do it; (3) to secure lower prices; (4) access easy information; (5) accidental/unplanned; (6) because it is cool; (7) stimulation by offline inputs, such as TV; and (8) to get prepurchase information. Evidence also suggests that opinion leaders are technology savvy. According to  Geissler and Edison (2005), “market mavens”-those opinion leaders who help consumers deal with numerous product choices-have an affinity for technology, suggesting that they are astute users of Internet-related communications.

Scholars also have couched studies of influence in terms of social network theory, which examines the linkages in social relationships according to actors and their ties (Monge and Contractor 2003). This perspective offers the potential of identifying informal linkages among potential target audiences. However, though identifying the motivations for online opinion seeking and the links between social relationships represent importance aspects of understanding online influence, they still give an incomplete picture of how consumers perceive different forms of information, such as UGC versus PGC.

Research Questions

Two research questions guide this study. The first is a contextual question that aims to identify the kinds of product information sites that consumers use. The second, and main, question deals with the credibility of UGC versus PGC.

The context of a message is an important consideration for marketers. Before executing a marketing campaign, marketers and advertisers must determine which media to use to accomplish the most cost-effective campaign. However, allocating a campaign to the right media is getting more difficult, because consumers’ media selections have become more complex (Soberman 2005). Media planning provides one of the most important factors affecting the success of campaigns. If consumers embrace product information that other online users have posted and rely on it more than they do on PGC, then UGC potentially could provide an attractive context for marketers and advertisers. To exploit UGC more efficiently, marketers and advertisers must identify the type of Web sites on which consumers encounter UGC about their products.

RQ1: What kinds of Web sites do consumers rely on when they try to get information about a product?

Online opinion leadership and UGC have significant import to marketers and advertisers, because opinion seeking may signal purchase intentions (Bellman, Lohse, and Johnson 1999; Fong and Burton 2006). If opinion seeking signals an intention to purchase products, and UGC functions as a new dimension of media through which opinion leaders publicly voice their opinions, it is worth examining how consumers perceive product information and product recommendations they find in UGC relative to PGC. With that in mind, the second research question is:

RQ2: Do consumers deem the product or brand information they find in UGC more trustworthy than information they find in PGC (e.g., online advertisements, product information on manufacturer’s Web sites)?


Qualitative in-depth interviews serve to investigate the research questions. As the main focus of the study, UGC remains a relatively new concept, and research regarding it is limited in nature. Because the goal of this research is to understand participants’ point of view and attitudes toward UCG, in-depth interviews provide a ready way to tap into appropriate information. A purposive sampling method gathers  nine university undergraduate and eight graduate students from a large public university located in the southeast United States, whom the researchers interviewed. According to Gallagher, Parsons, and Foster (2001), using student samples is more effective than random samples when scholars study online consumer behavior, because students are among the heaviest of Internet users. Furthermore, college students are attractive to marketers, because their brand loyalties have not solidified. Logically, because they are heavy Internet users with low brand loyalty, they should research products in cyberspace and seek UGC about products. This combination of traits makes college students ideal participants for the study. Table 1 details the main characteristics of the participants.

The developed interview guide is based on a review of the literature and includes five main questions with associated probes (Appendix A). The questions initially explore each respondent’s tendencies to use the Internet; thoughts about UGC Web sites, such as blogs, YouTube, and discussion boards; and online opinion-seeking habits. Even though the interview guide includes associated probes, the questions depend on  information provided by the participants; that is, a participant’s response to the main questions determines which probes follow. The interviews took place in comfortable surroundings in which participants would not be distracted. Interviews ranged from 15 to 45 minutes, and 15 interviews lasted at least 35 minutes.

Table 1
Study Participant Characteristics

Study Participant Characteristics

Participants viewed three different materials during the course of the interview, all of which pertain to the Toyota Prius, an entry-level automobile. The use of an automobile in this study is appropriate, given the relevance of this product category to students. According to Harris Interactive, three of every fourcollege students own or have access to a car for personal use. During 2002-2003, students spent $31 billion on automobiles, and one in every eight students is expected to buy a car in the next year (“College Students”). The Alpha material contains an advertisement for the Toyota Prius (PGC), whereas the Beta and Gamma materials feature questions and opinions about the Prius generated by consumers (UGC). To examine how consumers respond to both positive and negative UGC, the study offers two kinds of UGC materials; Beta material provides negative opinions about the car, whereas Gamma material includes positive opinions about it (the Findings section describes these materials more fully). During the interviews, all participants saw PGC. In addition, participants A-G, P, and Q saw the Beta material, while participants H-N and O reviewed only the Gamma material (Table 1).

All interviews were audio taped. After the completion of each interview, the tapes were reviewed several times to identify emerging themes. The notes taken regarding these relevant themes provide the basis of the findings.


Before attempting to answer the two research questions, the study process identifies the online habits of the participants. Most participants describe themselves as medium or heavy users of the Internet; 12 participants indicate that they spend a large amount of their free time surfing the Internet. The major online activities of the participants are diverse; however, all participants search for their interests on Google and use at least one e-mail site. Of particular importance for the current study, 8 participants report engaging in online shopping, 12 are YouTube users, and 11 visit blogs on a regular basis (Table 2).

Table 2
Major Online Activities

Major Online Activities

In light of their comments about their online activities, and to answer RQ1, the interview questions specifically ask the respondents about blogs, YouTube, and discussion boards.

Blogging. Eleven participants reveal that they personally have at least one blog, and 1 (participant Q) indicates that she previously blogged but no longer does. The most popular blogs are those developed on social network sites such as MySpace and Facebook. Three participants (A, B, and M) indicate they have blogs on both these Web sites. The reasons they list for why they maintain blogs include to keep friends updated, to develop new friendships, to see pictures/video or hear songs, and to relax. As one participant notes, “I do blog to keep my friends updated,” and “I think a blog is a good way for people to express themselves.” Six participants do not have blogs, largely because they “do not want others to invade their privacy” and think “blogging is time-consuming.” Some participants who blog also note concerns about privacy, though their concerns did not dissuade them from blogging.

Nine participants (A, B, D, F, H, L, M, O, and Q) acknowledge having seen product images or product information on others’ blogs; the rest have not or do not remember having seen them. The products or services that participants remember vary: restaurants, MP3 players, tennis shoes, cars, liquor, food, and clothes. Participant F, who has a part-time job at a cosmetics shop in a mall, notes: “My friends often ask me about cosmetics and skin care, and I send recommendations to them via my blog.” She also adds, “Some of my friends actually bought the cosmetics I recommended.” Another, whose friend puts pictures of food on her blog, indicates that she would try the food because she had seen it on the blog or because of her friend’s recommendation. In general though, even participants who recall seeing product information on blogs do not indicate that they actually seek out this information or are influenced by it. Rather, it was as if the product information was an artifact of the blog, not its focus or a reason for seeking out the blog.

YouTube. Twelve participants use YouTube, and several comment that they search footage on YouTube more than three times per week. The main reason they visit to YouTube is for fun; some mention that they go to the site because their friends send them hyperlinks to funny videos. However, despite its widespread use, YouTube does not seem to be effective for either product advertisements or product placements in videos. Thirteen participants either had not seen any product information or recommendations on YouTube or could not recall seeing them. Only one participant remembers a recommendation with a beer in its video but does not remember the brand of the beer. Another participant comments that she had viewed promotional information, often commercials, on YouTube but purely for entertainment purposes:

YouTube is more an entertainment thing…. I’m going to look up Bud Light on YouTube because I know they’re going to have a lot of funny videos. But I’m not going to go to YouTube and say, “Please educate me about this product”…. Heinz had a contest to have people make commercials for Heinz products and there’s this guy brushing his teeth with ketchup. That’s funny, I’ll look up Heinz. Because I know that it’s going to be funny videos, not because they’re going to say “OK Heinz 57. This is the process how it’s made. This is how healthy it is for you.” That’s not what I’m looking for on YouTube.

Apparently, YouTube is not perceived as a vehicle that conveys online recommendations, but it has a viral power, especially when the footage is funny or provocative (Porter and Golan 2006).

Discussion Boards. All participants know about discussion boards, but they do not seem to be active users in terms of generating content. Most have not posted any questions or comments; one participant posted a review on an apartment-rating discussion board-a negative evaluation because she was disappointed with her new apartment. However, they do read discussion boards. Eleven participants have seen a discussion board while searching for their interests on Google and had read UGC on discussion boards. They also consult discussion boards for product information, even after they have purchased. For example, when asked if she read UGC about products in which she was interested, one participant comments:

Sometimes not until it’s too late. Like I’ll buy something and realize that it doesn’t really work that well and then I’ll think to look it up after the fact. And there will be all these really bad reviews and I’ll think “Oh crap! Why did I buy it when I was there? Why didn’t I come home and check the Internet first?”

Participants generally assume that information posted on discussion boards comes from other users and do not often question the source of comments. When asked the question “Have you wondered if the content in the discussion board was posted by marketers?” all but one participant answer they had not thought about who posted questions and answers on discussion boards but simply assumed it was other individuals-even if they did not know the people posting the comments. For example, when asked how he was sure that it was customers who posted comments, participant P notes:

I guess you’re not. I mean I guess they could lie and say they are a customer when they could be somebody from the company that’s just randomly posting that up there to make you believe it’s a consumer. But, I just tend to believe it, though.

It is also worth noting that participants tend to research and seek out UGC only for more involving products. This focus makes sense, because it is impractical to research all product purchases; some products are repeat purchases and thus no research is needed, and for others, the amount of potential risk is very low and not worth the effort:

Yeah. I’m trying to remember a specific incident of something I’ve looked up. I mean, not everything I buy I’m going to look up on the Internet, obviously that would take too much time. But, uhm, I guess big purchases.

In terms of RQ1, though blogs and vehicles such as YouTube do not provide memorable vehicles for delivering product messages, the same cannot be said of discussion boards, Participants actively seek information on discussion boards, though they seldom post themselves. Furthermore, though they read discussion boards, they seldom evaluate the source of the material and tend to assume that the content is user generated. To offset any sense that marketers are trying to deceive them, this finding suggests that PGC must be clearly marked as such. Kaikati and Kaikati (2004) note that the misuse of stealth marketing in nontraditional vehicles may actually cause negative impacts on the product or brand. In some cases, stealth marketing even may be perceived as underhanded, in which case consumers wind up feeling as if the company has tried to trick them by catching them off guard.

Determining the answer to RQ2, which wonders whether consumers deem product or brand information in UGC more trustworthy than information found in PGC, requires providing participants with two forms of material during the interview sessions (e.g., Alpha and Beta or Alpha and Gamma). The Alpha material (PGC) features an article about the Toyota Prius, generated by product producers (e.g., marketers, ad practitioners, professional writers hired by the company, journalists), that provides positive information about hybrid technology, environmental news, and the eye-catching, highly technological features of the car. The UGC materials consist of a summary of questions and answers about the Toyota Prius; the Beta UGC is mainly negative, whereas the Gamma UGC includes mainly positive answers. The question and answers come from Yahoo! Answers, a discussion board on which Internet users can freely post questions and answers. Nine participants saw the Alpha and Beta materials, and eight saw the Alpha and Gamma materials.

Participants indicate their thoughts about both materials. Among those seeing the Alpha/Beta combination, only two participants (C and E) find the Alpha material (PGC) was more trustworthy. Specifically, participant C comments: “I trust both materials, but I like the first one [Alpha material] better.” He rationalizes his thought by saying that “the second one [Beta material] might be written by kids who don’t know about cars.” Conversely, seven participants trust the Beta material (UGC) more, noting that a consumer’s opinion is more credible than an advertiser’s positive words, because the consumer has nothing to gain by posting the comments:

Well, the ones [making comments] who own the car seem more credible than the other ones. But I would still tend to go on their advice rather than on the dealer’s advice because the dealer is trying to sell you the car, so they don’t want to say anything bad about it.

Furthermore, the fact that a poster owns and has direct experience with a product seems to sway several participants, who view these comments as more credible than PGC. Noted two participants:.

I always look at review sites before I buy something substantial. I mean, there’s a risk involved and I want to make sure I’m not wasting money. I’d much rather read comments from someone who owns the product I’m interested in. They’re on the front line and I tend to feel that they’re giving me a fuller picture than if I go to the manufacturer’s site. I mean, why would they lie? They’re not going to make money off of it.

Well, I would say the car company is important, but I think maybe the people, the audience, their views are important because they have experience. And the car company, they just try to make it appealing so that they can sell it.

Participants who saw the Alpha (PGC) and Gamma (positive UGC) materials respond to similar questions about the credibility of the material. Three participants (I, J, and M) comment that they trust the PGC more than the UGC, because they think the information generated by manufacturers is regulated by commercial law and therefore must be truthful. As  one comments, “They can’t lie about stuff like that. Wouldn’t they get sued? Why risk it?” However, they also posit that because the intent of producers is to sell products, PGC only tells a positive story about the product, which suggests that they perceive PGC does not give them “the whole story.”

The other five participants (H, K, L, N, and O) who saw the Alpha/Gamma combination indicate the Gamma UGC is more credible and persuasive. These participants view consumers who post UGC as credible because they “had nothing at stake” and therefore were not likely to post untruthful comments. To these participants, PGC, though not necessarily untruthful, presents only part of the product’s “story”.

I guess there’s a give and take on each of them. I mean, I guess I would say that the user comments are more trustworthy because they’re not going to profit from me buying a Prius. So they don’t care one way or another except that they’re so excited about their Prius that they want more people to have them. It’s like a club thing. But, yeah. Yeah, I would definitely say that because, this website, the Toyota website, is just going to tell me all the good things about it. And it’s going to tell me that it’s perfect for everyone, you know, the football player fits in it. And the kids love it ‘cuz they’re funky. And the mom loves it because of gas mileage. So, you know, they’re going to tell me all these things. But they’re not going to tell me to rent it for a week, the way those other people did, because if I take 10-minute trips I’m not going to like it.

Across all 17 participants, 12 find UGC material more credible and trustworthy than PGC. This finding does not differ much regardless of whether participants view positive or negative UGC.


This study employs a framework based on personal influence to shed light on how consumers use the Internet for product purchases or information, as well as how they view the UGC they encounter as they search. Thus, this research attempts to clarify the differences between UGC and PGC in terms of consumers’ perceptions of their believability.

Do ideas about social influence and related theories, such as the two-step flow model, offer much insight into the role of UGC and its influence?  Does this perspective offer advertisers and marketers an effective way to conceptualize the online audience? This research suggests as much. Consumers are likely to look for product information or recommendations before purchase, especially for highly involving products. Among the information they consider is that generated by other consumers. Participants in this study indicate that they mainly obtain user generated information and recommendations from discussion boards, in support of Fong and Burton’s (2006) finding that discussion boards are useful for consumers who want the opinions of others and may influence potential purchases. Discussion boards content is generated by consumers, usually those in the prepurchase stage or those who have already purchased and wish to share their product experiences. However, blogs, particularly those found on social networking sites, are not memorable to consumers in terms of the product information they might convey.

A major finding of this study is that participants voice more trust in product information created by other consumers than in information generated by manufacturers. The trustworthiness attributed to UGC remains similar, regardless of whether participants view positive or negative information. Most participants trust other end-users’ opinions, because they think other consumers convey more than just positive information about products. In addition, another consumer’s personal experience with a product seems important to several participants who view such UGC as more credible than PGC. This finding supports the work of Goldsmith and Horowitz (2006), who find that consumers search other consumers’ opinions to reduce their risks and obtain prepurchase information; therefore, other consumers’ information emerges as more important than advertising. The current study suggests that this comparison also holds in an online environment.

Comments from participants also indicate that they view people posting UGC on discussion boards or reviewer sites as opinion leaders, even if they did not know the people who generate the UGC. When participants do not agree with the opinions stated in UGC, they still seem to consider them. Furthermore, opinion leaders have an affinity for media and  are themselves are influenced by media (Graham and Havlena, 2007), though they also have an effect on those in their spheres of influence (Vernette, 2004). A logical conclusion thus suggests that marketers can use the media to influence opinion leaders and thereby indirectly sway consumers who look to opinion leaders for details like product recommendations and information.

Several studies show that targeting opinion leaders can be an effective way to capitalize on the insights generated by social influence perspectives. For example, Vernette (2004) reveals that identifying opinion leaders and targeting them through media is realistic, providing that marketers accurately identify the target and can describe it in terms that planners can implement. Graham and Havlena (2007) also find that advertising can stimulate consumers to advocate for products, and online advertising has the greatest influence in this area. Although at first glance, opinion leader populations might seem small, in reality, a little more than 10% of a given population potentially represents opinion leaders for a product category, which implies their numbers actually are sizable (Vernette 2004). Opinion leaders also respond to and like advertising (Vernette 2004). Our participants view UGC as credible and believable, which suggests they view people who post such comments as opinion leaders; opinion leaders have an affinity for media and are sizable in numbers. In combination, these findings suggest that opinion leaders can be reached using traditional media planning techniques and provide a good investment for marketers.

Knowledge about opinion leaders even can be used to offset negative UGC. Participants do not differentiate much between positive and negative UGC, viewing each type as credible and, in particular, more credible than PGC. However, negative UGC can have a harmful impact on a brand, which leads to a crucial question” What can a marketer do to offset negative UGC? Previous research suggests that marketers might harness the power of WOM to create brand advocacy, including positive associations about a brand (Keller 2007). Opinion leaders are central to this concept. On the basis of a study of the relationship between WOM about brands and brand advertising, Graham and Havlena (2007, p. 433) indicate a “‘two-step’ flow of communication in brand advertising…. [B]y disseminating brand messages in media, advertisers can stimulate consumers to talk about, and say good things about, their products.” This dual-flow perspective suggests that marketers might overcome negative UGC with positive advertising about a brand aimed at opinion leaders. This strategy should be particularly effective with online advertising, because it stimulates brand searches, Web site visits and on- and offline brand advocacy.

Only five participants indicate greater trust in product information generated by product producers, largely because they believe such information is regulated by commercial law. However, they also acknowledge the goal of such communication is to sell products. Although the participants are correct in noting that deceptive and untruthful advertising is illegal, their understanding of the legal aspects of advertising does not appear to go much beyond this superficial level. Similarly, participants indicate that they “just assume” that comments on discussion boards emanate from consumers; they rarely consider the source of the information carefully. In combination, these findings indicate that, regardless of how tempting the opportunity a producer has to “plant” comments in discussion boards, it should avoid this tactic unless it clearly marks those comments as originating with the marketer. The failure to do so likely will have a negative impact on the product or brand (Kaikati and Kaikati 2004).

This study adopts a purposive sampling method to investigate online users’ opinion-seeking behavior, which is appropriate given the research questions. However, this approach provides a relatively small sample size. Thus, though the findings shed light on attitudes and opinions about UGC, they are not generalizable to larger populations of college students or consumers. Further research might employ methods that make such generalizations possible. Similarly, the findings tend to indicate that consumers view negative UGC as more trustworthy than positive UGC, but the small sample size makes this conclusion tentative at best.

The study design asks participants to consider UGC about a car, a highly involving product. Participants also claim it is unrealistic to seek out UGC for every product purchase. Thus, what are the parameters of online influence with regard to consumer behavior? For which product categories does UGC hold the most sway? These are important questions for future research.

Even though the participants are more likely to search for product information on discussion boards than on YouTube or blogs, they remain heavy users of all these media. Therefore, the advertising potential of UGC on YouTube or blogs could be enormous, particularly given the growth of social networking sites with blogging capabilities. For example, if a consumer runs into an attractive picture of a product in a friend’s blog, he or she may develop a good impression of the product and subsequently purchase it because of that experience. An important area for further research therefore is the influence of the UGC found on YouTube or blogs on consumers’ future purchases. This study does not indicate that blogs or YouTube are effective ways for promoting a product, but this result could be an artifact of the study method. Other researchers, employing different methods, might uncover evidence to the contrary.


Anderson, E. (1998), “Customer Satisfaction and Word of Mouth,” Journal of Service Research, 1(1), 5-17.

Arndt, J. (1968), “Selective Processes in Word of Mouth,” Journal of Advertising Research, 8(3), 19-22.

Bailey, A. A. (2005), “Consumer Awareness and Use of Product Review Websites,” Journal of Interactive Advertising, 6(1), 90-108.

Bearden, W., and M. Etzel (1982), “Reference Group Influence on Product and Brand Purchase Decisions,” Journal of Consumer Research, 9(2), 183.

Bellman, S., Gerald Lohse, and E. Johnson (1999), “Predictors of Online Buying Behavior,” Communications of the ACM, 42(12), 32-38.

Blodgett, J., D. Granbois, and R. Walters (1993), “The Effects of Perceived Justice on Complainants’ Negative Word-of-Mouth Behavior and Repatronage Intentions,” Journal of Retailing, 69(4), 399.

Bowman, D. and D. Narayandas (2001), “Managing Customer-Initiated Contacts with Manufacturers: The Impact on Share of Category Requirements and Word-of-Mouth Behavior,” Journal of Marketing Research, 38(August), 281-297.

Brooks, R. (1957), “‘Word-of-Mouth’ Advertising in Selling New Products,” Journal of Marketing, 22(April), 154.

“College Students to Spend Nearly $15 Billion on Cars in 2004.” Available at (accessed November 29, 2007).

Dellarocas, C. (2003), “The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms,” Management Science, 49(10), 1407-1424.

Engel, J., R. Blackwell, and R. Kegerreis (1969), “How Information Is Used to Adopt an Innovation,” Journal of Advertising Research, 9(4), 3-8.

Fong, J. and S. Burton (2006), “Electronic Word-of-Mouth: A Comparison of Stated and Revealed Behavior on Electronic Discussion Boards,” Journal of Interactive Advertising, 6(2), 61-70.

Fulgoni, G. (2007), “Plan for Advertising on UGC,” Marketing News, 41(1), 16-18.

Gallagher, K., J. Parsons, and K.  Foster (2001), “A Tale of Two Studies: Replicating “Advertising Effectiveness and Content Evaluation in Print on the Web,” Journal of Advertising Research, 41(4), 71-81.

Gatignon, H. and T.  Robertson (1986). “Competitive Effects on Technology Diffusion,” Journal of Marketing, 50(3), 1-12.

Geissler, G. L. and S.W.  Edison (2005), “Market Mavens’ Attitudes Towards General Technology: Implications for Marketing Communications,” Journal of Marketing Communications, 11(2), 73-94.

Godes, D. and D. Mayzlin (2004), “Using Online Conversations to Study Word-of-Mouth Communications,” Marketing Science, 23(4), 545-560.

Goldsmith, R. and D. Horowitz (2006), “Measuring Motivations for Online Opinion Seeking,” Journal of Interactive Advertising, 6(2), 1-16.

Graham, J. and W. Havlena (2007), “Finding the ‘Missing Link’: Advertising’s Impact on Word of Mouth, Web Searches and Site Visits,” Journal of Advertising Research, 47(4), 427-435.

Grossman, L. (2006), “Time’s Person of the Year: You.” Available at,9171,1569514,00.html (accessed December 13, 2006).

Herr, P., Frank Kardes, and J.  Kim (1991), “Effects of Word-of-Mouth and Product-Attribute Information of Persuasion: An Accessibility-Diagnosticity Perspective,” Journal of Consumer Research, 17(4), 454-462.

Johnson, T. J. and B.K.  Kaye (2004), “Wag the Blog: How Reliance on Traditional media and the Internet Influence Credibility Perceptions of Weblogs Among Blog Users,” Journalism & Mass Communication Quarterly, 81(3), 622-642.

Kaikati, A. and J. Kaikati (2004), “Stealth Marketing: How to Reach Consumers Surreptitiously,” California Management Review, 46(4), 6-22.

Katz, E. and P. Lazarsfeld (1955), Personal Influence: The Part Played by People in the Flow of Mass Communication. New York: The Free Press.

Keller, E. (2007), “Unleashing the Power of Word of Mouth: Creating Brand Advocacy to Drive Growth,” Journal of Advertising Research, 47(4), 448-452.

Lazarsfeld, P., B. Berelson, and H. Gaudet (1948), “The People’s Choice,” American Sociological Review, 13(6), 792.

Lazarsfeld, P. and H.  Menzel (1963), “Mass Media and Personal Influence,” in The Science of Human Communication, Wilbur Schramm (ed.). New York City: Basic Books, 94-115.

Lam, D. and D. Mizerski (2005), “The Effects of Locus of Control on Word-of-Mouth Communication,” Journal of Marketing Communications, 11(3), 215-228.

Lyons, B. and K. Henderson (2005), “Opinion Leadership in a Computer-Mediated Environment,” Journal of Consumer Behavior, 4(5), 319-329.

Mahajan, V., E. Muller, and R. Kerin (1984), “Introduction Strategy for New Products with Positive and Negative Word-of-Mouth,” Management Science, 30(12), 1389-1401.

Marsha, R. (1984), “Word of Mouth Communication as Negative Information,” Advances in Consumer Research, 11(1), 697-702.

Merton, R. (1968), Social Theory and Social Structure. Glencoe, IL: The Free Press.

Monge, P.R. and N.S. Contractor (2003), Theories of Communication Networks. New York: Oxford University Press.

Porter, L. and G.  Golan (2006), “From Subservient Chickens to Brawny Men: A Comparison of Viral Advertising to Television Advertising,” Journal of Interactive Advertising, 6(2), 30-38.

Reingen, P., B. Foster, J. Brown, and S. Seidman (1984), “Brand Congruence in Interpersonal Relations: A Social Network Analysis,” Journal of Consumer Research, 11(3), 771-783.

Rogers, E. (1983), Diffusion of Innovations. New York: The Free Press.

Rogers, E. and M. Allbritton (1995), “Interactive Communication Technologies in Business Organizations,” The Journal of Business Communication, 32(2), 177-195.

Senecal, S. and J. Nantel (2001), Online Interpersonal Influence. Available at (accessed December 12, 2006).

Senecal, S. and J.  Nantel (2004), “The Influence of Online Product Recommendations on Consumers’ Online Choices,” Journal of Retailing, 80(1), 159-169.

Smith, D., S. Menon, and K.  Sivakumar (2003), Trust Me, Would I Steer You Wrong? The Influence of Peer Recommendations within Virtual Communities. Paper presented at Academy of Marketing Science Annual Conference, Florida.

Soberman, D. (2005), “The Complexity of Media Planning Today,” Journal of Brand Management, 12(6), 420-429.

Steyer, A., R. Garcia-Bardidia, and P. Quester (2006), “Online Discussion Groups as Social Networks: An Empirical Investigation of Word-of-Mouth on the Internet,” Journal of Interactive Advertising, 6(2), 51-59.

Sussan, F., S. Gould, and S. Weisfeld-Spolter (2006), “Location, Location, Location: The Relative Roles of Virtual Location, Online Word-of Mouth (eWOM) and Advertising in the New-Product Adoption Process,” Advances in Consumer Research, 33(1), 649-650.

Thorson, K. and S. Rodgers (2006), “Relationships between Blogs as eWOM and Interactivity, Perceived Interactivity, and Parasocial Interaction,” Journal of Interactive Advertising, 6(2), 39-50.

Vernette, E. (2004), “Targeting Women’s Clothing Fashion Opinion Leaders in Media Planning: An Application for Magazines,” Journal of Advertising Research, 44(1), 90-107.

Weinberger, M., C. Allen, and W.  Dillon (1981a), “Negative Information: Perspectives and Research Directions,” Advances in Consumer Research, 8(1), 398-404.

Weinberger, M., C. Allen, and W.  Dillon (1981b), “The Impact of Negative Marketing Communications: The Consumers Union/Chrysler Controversy,” Journal of Advertising, 10(4), 20-47.BWellman, B. (2001), “Physical Place and Cyberplace: The Rise of Personalized Networking,” International Journal of Urban and Regional Research, 25(2), 227-252.

Winkler, T. and K. Buckner (2006), “Receptiveness of Gamers Embedded Brand Messages in Advergames: Attitudes towards Product Placement,” Journal of Interactive Advertising, 7(1), 37-46.

Appendix: Interview Guide

Interview Guide Part 1

Interview Guide Part 2

About the Authors

Hyuk Jun Cheong (B.A., Law, Keimyung University, Korea) is a Master’s student in the School of Advertising and Public Relations at the University of Tennessee. His research interest focuses on user generated content in computer environments.

Margaret A. Morrison (Ph.D., The University of Georgia) is an Associate Professor in the School of Advertising and Public Relations at the University of Tennessee. Her research interests include tobacco advertising, account planning and Thai advertising.