Title:Enhancing Effectiveness of Referral Programs by Promoting Active Matching: Evidence from Field Experiments
Speaker:Yupeng Chen, Wharton School of the University of Pennsylvania
Time:Wednesday, 27 December, 13:30-15:00
Location:Room K01, Guanghua Building 2
Referral programs have been widely used by firms for new customer acquistion. In this paper, we propose that a firm can enhance the effectiveness of its referral program by promoting active matching (i.e., referring customers' deliberate screening of their friends and diligent matching of those who they think may be a good fit to the firm). We propose three treatments aimed at promoting active matching, including (1) offering current customers a gift before inviting them to refer friends, (2) notifying current customers about the value that they have received from the firm before inviting them to refer friends, and (3) rewarding referring customers based on the value of their referred customers. We empirically test these three treatments by conducting two field experiments in collaboration with a leading Chinese online financial services firm. We find that all three treatments substantially enhanced the effectiveness of the focal referral program, which is measured for each current customer as the total value of his or her referred customers. We also find that the enhancement was primarily driven by the acquisition of higher-value new customers rather than the acquisition of more new customers. Moreover, we explore the machanisms underlying these treatments, and find evidence suggesting that the gift and notification treatments induced reciprocity from current customers toward the firm, and that all three treatments promoted active matching.
Yupeng Chen is a doctoral candidate in Marketing at the Wharton School of the University of Pennsylvania. His research interests lie in two areas: referral programs and preference estimation. He is particularly interested in conducting field experiments to identify treatments that can enhance the effectiveness of referral programs and understand the underlying mechanisms. He is also interested in developing machine learning methodologies for accurate estimation of consumers’ heterogeneous preferences. His research has been published inMarketing Science.
Prior to Wharton, Yupeng obtained his Ph.D. in Operations Research from Columbia University in 2015 and his B.S. in Mathematics from Peking University in 2009.
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