Is Peer Influence Essential for Success

A general conjecture is that successful products attain their popularity through influence of adopters on their peers and product information disseminating over the social network. Indeed, many studies have confirmed the existence of local peer effects and contagion. But others have shown that peer influence has a marginal, if any, effect on cascades of adoptions. In this work, we study this discrepancy by analyzing video games propagating over the social network of gamers on Steam, the world’s largest video game platform. A major identification problem – distinguishing homophily from peer influence – is a challenge in any peer influence study based on observational data. To overcome it, we introduce a novel method, Revealed Preference-based Matching Estimation, that estimates the impact of peer influence on adoption by using unsupervised machine-learning algorithm to match product adopters to users based solely on similarity of their past adoption. This procedure is applied to thousands of products and reveals how peer influence changes over their lifecycle, thus allowing us to draw general conclusions about the entire ecosystem. Results show that most products belong to one of two distinct groups, each exhibiting a characteristic temporal pattern of adoption: products that exhibit substantial peer influence; and products that do not, for which adoption is driven by preferences. Considering the reach of products in each group, surprisingly, we found that local peer effects are stronger in less popular products. Even more surprising is the fact that almost all blockbusters (products adopted by millions of users) did not exhibit substantial peer influence at any stage of their lifecycle. These results shed light on the discrepancy between observed local peer effects and the lack of peer influence in large adoption cascades that are characteristic of successful products.