The authors study the effect of word-of-mouth (WOM) marketing on member growth at an Internet social networking site and compare it with traditional marketing vehicles. Because social network sites record the electronic invitations sent out by existing members, outbound WOM may be precisely tracked. WOM, along with traditional marketing, can then be linked to the number of new members subsequently joining the site (signups). Due to the endogeneity among WOM, new signups, and traditional marketing activity, the authors employ a Vector Autoregression (VAR) modeling approach. Estimates from the VAR model show that word-ofmouth referrals have substantially longer carryover effects than traditional marketing actions. The long-run elasticity of signups with respect to WOM is estimated to be 0.53 (substantially larger than the average advertising elasticities reported in the literature) and the WOM elasticity is about 20 times higher than the elasticity for marketing events, and 30 times that of media appearances. Based on revenue from advertising impressions served to a new member, the monetary value of a WOM referral can be calculated; this yields an upper bound estimate for the financial incentives the firm might offer to stimulate word-of-mouth.

The authors thank the Marketing Science Institute for the research grant provided to this project. They also thank BazaarVoice for the data analyzed in this article as well as the invaluable conversations surrounding this topic. Christophe Van den Bulte served as associate editor for this article.

No abstract

The success of Internet social networking sites depends on the number and activity levels of their user members. Although users typically have numerous connections to other site members (i.e., “friends”), only a fraction of those so-called friends may actually influence a member's site usage. Because the influence of potentially hundreds of friends needs to be evaluated for each user, inferring precisely who is influential—and, therefore, of managerial interest for advertising targeting and retention efforts—is difficult. The authors develop an approach to determine which users have significant effects on the activities of others using the longitudinal records of members' log-in activity. They propose a nonstandard form of Bayesian shrinkage implemented in a Poisson regression. Instead of shrinking across panelists, strength is pooled across variables within the model for each user. The approach identifies the specific users who most influence others' activity and does so considerably better than simpler alternatives. For the social networking site data, the authors find that, on average, approximately one-fifth of a user's friends actually influence his or her activity level on the site.

The authors study the effect of word-of-mouth (WOM) marketing on member growth at an Internet social networking site and compare it with traditional marketing vehicles. Because social network sites record the electronic invitations sent out by existing members, outbound WOM may be precisely tracked. WOM, along with traditional marketing, can then be linked to the number of new members subsequently joining the site (signups). Due to the endogeneity among WOM, new signups, and traditional marketing activity, the authors employ a Vector Autoregression (VAR) modeling approach. Estimates from the VAR model show that word-ofmouth referrals have substantially longer carryover effects than traditional marketing actions.The long-run elasticity of signups with respect to WOM is estimated to be 0.53 (substantially larger than the average advertising elasticities reported in the literature) and the WOM elasticity is about 20 times higher than the elasticity for marketing events, and 30 times that of media appearances. Based on revenue from advertising impressions served to a new member, the monetary value of a WOM referral can be calculated; this yields an upper bound estimate for the financial incentives the firm might offer to stimulate word-of-mouth.

No abstract

No abstract

As social network use continues to increase, an important question for marketers is whether consumers’ online shopping activities are related to their use of social networks and, if so, what the nature of this relationship is. On the one hand, spending time on social networks could facilitate social discovery, meaning that consumers “discover” or “stumble upon” products through their connections with others. Moreover, cumulative social network use could expose consumers to new shopping-related information, possibly with greater marginal value than the incremental time spent on a shopping website. This process may therefore be associated with increased shopping activity. On the other hand, social network use could be a substitute for other online activities, including shopping. To test the relationship between social network use and online shopping, the authors leverage a unique consumer panel data set that tracks people's browsing of shopping and social network websites and their online purchasing activities over one year. The authors find that greater cumulative usage of social networking sites is positively associated with shopping activity. However, they also find a short-term negative relationship, such that immediately after a period of increased usage of social networking sites, online shopping activity appears to be lower.