Viral Product Design: Testing Social Contagion and Peer Influence Effects in Networks Using Randomized Trials

 

SINAN ARAL

KAUFMAN MANAGEMENT CENTER

 

We examine how firms can create word of mouth peer influence and social contagion by incorporating viral features into the design of their products. Evaluating the effects of such product design decisions on social contagion is difficult because econometric identification of peer influence is non-trivial. Although several approaches have been proposed, it is widely believed that the most effective way to obtain unbiased estimates of peer effects is to conduct large-scale randomized trials of peer-to-peer communications intended to influence particular economic decisions, such as the decision to adopt a product. We therefore designed and conducted a randomized field experiment testing the effectiveness of passive-broadcast and active-personalized viral messaging capabilities in creating peer influence and social contagion among the 1.4 million friends of 9,687 experimental users of Facebook.com. The experiment utilizes a customized commercial Facebook application to observe user behavior, communications traffic and the peer influence effects of randomly enabled viral messaging capabilities on application diffusion in the local networks of experimental and control population users. Results show that viral product design features generate econometrically identifiable peer influence and social contagion effects. Features that require more activity on the part of the user and are more personalized to recipients create greater marginal increases in the likelihood of adoption per message, but generate fewer total messages creating countervailing effects on peer influence. On average, passive-broadcast viral messaging capabilities, which are less personalized but also require less user effort, generate a 246% increase in local peer influence and contagion effects over a baseline model in which viral messaging is disabled. Adding active-personalized viral messaging capabilities, which are more personalized but require more user effort, generates an additional 98% increase in local peer influence and contagion effects over the passive-broadcast model. Analysis shows that initial peer adoptions in users’ local networks drive a viral feedback loop that accelerates contagion. These results shed light on how viral products can be designed to generate social contagion and how randomized trials can be used to identify peer influence effects in social networks.