Seeding Viral Content The Role of Message and Network Factors YUPING LIU-THOMPKINS Online viral campaigns require a seeding strategy that involves choosing the first- Old Dominion University generation consumers to spread a viral message to. Building on social-capital theory and [email protected] social-network analysis, this research examine key aspects of the seeding strategy by tracking the diffusion of 101 new videos published on YouTube. The results show that the need for a “big-seed” strategy (i.e., using many seed consumers) depends on message quality. Furthermore, one should choose consumers who have strong ties with the advertiser and who also have strong influence on others, rather than simply wider reach. Among seed consumers, they should share a moderate amount of interest overlap instead of being too homogeneous or heterogeneous as a group. INTRODUCTION and Lilien, 2008). This view comes from the reali- “Viral marketing” refers to the act of propagating zation that viral marketing outcomes are affected marketing messages through the help and cooper- by many factors that firms have limited control ation from individual consumers. It departs from over. Although these factors introduce a great deal traditional advertising in its reliance on consumer of uncertainty into the viral-marketing process, it word of mouth (WOM) instead of mass media as does not mean that firms cannot make informed the message conveyance vehicle. decisions to maximize the possibility of success Compared with traditional advertising, viral (Kalyanam et al., 2007). marketing enjoys the benefits of lower cost, higher One such area that marketers may control is how credibility, faster diffusion, and better targeting of to start the viral diffusion process—what usually consumers (Bampo et al., 2008; Dobele, Toleman, is referred to as the “seeding strategy.” A seeding and Beverland, 2005). Furthermore, the emergence strategy involves determining how many initial of online communities and social media in recent consumers (“seeds”) are needed to disseminate years have vastly extended individual consumers’ a viral message to and what types of consumers influence beyond their immediate circle of close to choose as seeds. As these seed consumers are friends to more casual acquaintances and some- responsible for the initial dissemination of the viral times even strangers (Duan, Gu, and Whinston, message to other fellow consumers, selecting the 2008). This significantly increased the scale of viral right targets as seeds can have a significant impact marketing, putting it into a more central position on later rounds of the viral diffusion process in company strategy (Ferguson, 2008). (Bampo et al., 2008; Watts and Peretti, 2007). Despite its increasing use, both marketing prac- Academic research on online viral market- titioners and researchers have pointed out the elu- ing offers limited guidance on choosing a proper siveness of viral marketing success and a general seeding strategy. Although existing studies have lack of understanding of what drives the success of examined the impact of individual and content viral marketing efforts (Ferguson, 2008; Kalyanam, characteristics that affect the pass-along of viral McIntyre, and Masonis, 2007). Some see viral mar- information, few have explicitly addressed the keting as more of an art than a science (De Bruyn proper choice of seed consumers. DOI: 10.2501/JAR-52-4-000-000 December 2012 JOURNAL OF ADVERTISING RESEARCH 59 SEEDING VIRAL CONTENT Addressing this gap in the literature, Message characteristics relate to the consumers. The central thesis from this the current research draws from the social- content and creative design of a viral stream of research is that the structure of capital theory and social-network analysis message, which are under the control of the social network through which a viral to identify four key elements of the seed- the advertiser (Ho and Dempsey, 2010; message spreads can affect the even- ing strategy: Kalyanam et al., 2007). An effective viral tual reach and influence of the message message should break through clutter and (Bampo et al., 2008; De Bruyn and Lilien, • the number of seeds to use, consumer indifference to encourage fur- 2008). Furthermore, a consumer’s role in • the strength of tie between seed individ- ther pass-along of the message. Research- diffusion depends on his or her position uals and the message originator, ers have found, for instance, that humor in the social network as defined by the • the level of influence of individual and sex appeal are popular tactics used in consumer’s relationship with others in the seeds, and viral messages (Golan and Zaidner, 2008) network, such as network centrality and • the interest homogeneity among seed and that the social visibility of a viral mes- tie strength (Goldenberg, Han Lehmann, individuals. sage encourages its diffusion (Susarla and Hong, 2009; Kiss and Bichler, 2008; et al., 2012; Salganik, Dodds, and Watts, Susarla et al., 2012). Using viral videos from YouTube as the 2006). Research in this area has often produced backdrop, it empirically tests the relation- Besides message characteristics, indi- conflicting results. For instance, on the ship between these seeding decisions and vidual consumers also play a critical role effect of network structure, some research- viral-diffusion outcome. Because informa- in the viral marketing process. This cat- ers have shown that a scale-free network, tion for making these decisions easily can egory of influence has received the most where only a few members have many be obtained from observable online social- extensive examination in the literature. connections, facilitates social contagion network activities and internal customer Findings in this area show that consum- (Barabási, 2002; Smith, Coyle,, Lightfoot, data, the findings from this research can ers’ personality traits (e.g., Chiu, Hsieh, and Scott, 2007). Others have found no offer very practical guidance to optimally Kao, and Lee, 2007; Sun, Youn, Wu, and difference, however, between a scale-free seeding a viral-marketing campaign. Kuntaraporn, 2006); demographics (e.g., network and a random network, where Trusov, Bodapati and Bucklin, 2010); usage most network members have a similar WHAT AFFEcts ONLINE VIRAL characteristics (e.g., Niederhoffer, Mooth, number of network connections (Kiss and MARKETING SUCCESS? Wiesenfeld, and Gordon, 2007; Sun et al., Bichler, 2008). Yet, a third study concluded In the last 5 to 10 years, interest in online 2006); and motivation for sharing content that cascades were less likely to happen in viral marketing has increased among mar- (e.g., Eccleston and Griseri, 2008; Phelps a network where individual influence is keting and advertising scholars. Studies in et al., 2004) all can affect the success of highly unbalanced than in a random net- this area typically have focused on either viral messages. work (Watts and Dodds, 2007). intermediate actions/processes such as For example, researchers have found probability of opening and passing along female and younger consumers tend to Gaps in the Literature viral information (e.g., Ho and Dempsey, exert more influence on their targets and Although academic researchers have 2010; Phelps et al., 2004), or end outcomes to be more susceptible to viral influences started to construct a roadmap of fac- such as the eventual reach of a viral cam- than male and older consumers (Katona tors contributing to the success of online paign and the adoption of the promoted et al., 2011; Trusov et al., 2010). Studies viral marketing, research in this area still product (e.g., Bampo et al., 2008; Katona, also have associated both extroversion and has been very limited (Chiu et al., 2007; Zubcsek, and Sarvary, 2011). innovativeness with a higher tendency to De Bruyn and Lilien, 2008) and has pro- In answering the question of what pass along content (Chiu et al., 2007; Sun duced fragmented and sometimes con- affects viral marketing success, three types et al., 2006). From a motivational stand- flicting results. of factors have been suggested: point, research has consistently found More specifically, there are two import- altruism to drive message sharing (e.g., ant gaps in the literature that need to be • message characteristics, Ho and Dempsey, 2010; Phelps et al., 2004). addressed: • individual sender or receiver character- Though individual characteristics focus istics, and on a single consumer, network charac- • Most existing studies have relied on • social network characteristics. teristics describe the connection between computer simulations or consumer 60 JOURNAL OF ADVERTISING RESEARCH December 2012 SEEDING VIRAL CONTENT surveys. Although simulation allows Specifically, researchers have called then comprise the social capital that it can controlled experimentation with net- for more analysis of a viral campaign’s draw upon for fulfilling its goals such as work properties that are difficult to seeding strategy (Bampo et al., 2008; spreading a viral message or increasing implement in a field setting, results Yang, Yao, Ma, and Chen, 2010), which brand awareness. from such studies are constrained by defines the choice of consumers that An important benefit of social capital is parameter and model assumptions that companies should initially spread the the facilitation of information flow (Lin, often prove unrealistic in the real-world viral message to. 2001; Van den Bulte and Wuyts, 2007), (Bampo et al., 2008). As a result, the As these seeds will initiate