Time: 10:00, 11 June 2025
Speaker: Pu Zhao is an Assistant Professor in the Department of Marketing at Peking University Guanghua School of Management. He received bachelor's degrees in mathematics, economics, and political science from the University of California, Los Angeles, and received his PhD in Business Administration with a concentration in marketing from Boston University in 2024. His research focuses on quantitative marketing strategy design and optimization, digital platform design and regulation, and especially the decision trade-offs among creators, consumers, and platforms in digital platform settings.
Abstract:
Referral marketing is increasingly adopted by creators to incentivize existing subscribers through referral rewards for customer acquisition. In this study, we focus on a referral program design where creators have discretion over pricing and referral decisions. We quantify the financial consequences of referral marketing by investigating these decisions with a structural model. Using a unique panel dataset of 1,755 creators over 39 months from a Chinese creator platform, we find that (1) a 1% increase in referral rewards leads to an average 0.78% increase in new subscribers; (2) when creators produce highly exclusive content, simply increasing referral rewards does not significantly boost referred subscribers; (3) for every 1% increase in creator profits, the relative probability of choosing a higher referral percentage decreases by 0.96%. Our structural model is generalizable enough to accommodate creators' pricing and referral decisions under different popular referral program designs in the market. In counterfactual analyses, we compare the current decentralized referral program design with two prevalent platform-driven designs: a fixed referral percentage or a fixed reward amount. We find that under the platform-driven designs, creators are less likely to adopt referral programs and lower subscription prices to attract subscribers, but platform revenue increases significantly, highlighting a misalignment between the profit-maximizing goal of creators and the revenue-maximizing objective of the platform.
