Creating Social Contagion Through Firm-Mediated Message Design: Evidence from a Randomized Field Experiment

Abstract

We study whether and how a firm can enhance social contagion simply by varying the message shared by customers with their friends. We focus on two key components of information contained in the message—information about the sender’s purchase status prior to referral and information about the existence of referral rewards—and their impacts on the recipient’s purchase decision and further referral behavior. In collaboration with an online daily-deal platform, we design and conduct a large-scale randomized field experiment involving more than 75,000 customers to identify the causal effect of different message designs on creating social contagion. We find that small variations in message content can have a significant impact on both recipients’ purchase and referral behaviors. Specifically, we find that (1) adding only information about the sender’s purchase status increases the likelihood of the recipient’s purchase but has no impact on follow-up referrals, (2) adding only information about referral reward increases the recipient’s follow-up referrals but has no impact on purchase likelihood, and (3) adding information about both the sender’s purchase and the referral rewards increases neither the likelihood of purchase nor follow-up referrals. We build a model to analyze the tradeoff between more adoption and more diffusion and implement the best-performing message design in a production system with millions of shared messages per year (with a projected increase in net profits of more than US$1 million per year). We further exploit the rich heterogeneity in deal, recipient, sender, and social-tie characteristics and examine the mechanisms underlying the effect of message design. The results suggest that both social learning and social utility are at work, and the attenuation in the recipient’s purchase is mainly driven by a decrease in social learning resulting from credibility concerns. The findings of the study provide actionable guidelines to firms for optimal design of messages at the aggregate and more granular levels. This paper was accepted by Anandhi Bharadwaj, information systems.