摘要
Many digital platforms have employed free-content promotion strategies to deal with the high uncertainty levels regarding digital content products.However,the diversity of digital content products and user heterogeneity in content preference may blur the impact of platform promotions across users and products.Therefore,free-content promotion strategies should be adapted to allocate marketing resources optimally and increase revenue.This study develops personal-ized free-content promotion strategies based on individual-level heterogeneous treatment effects and explores the causes of their heterogeneity,focusing on the moderating effect of user engagement-related variables.To this end,we utilize ran-dom field experimental data provided by a top Chinese e-book platform.We employ a framework that combines machine learning with econometric causal inference methods to estimate individual treatment effects and analyze their potential mechanisms.The analysis shows that,on average,free-content promotions lead to a significant increase in consumer pay-ments.However,the higher the level of user engagement,the lower the payment lift caused by promotions,as more-engaged users are more strongly affected by the cannibalization effect of free-content promotion.This study introduces a novel causal research design to help platforms improve their marketing strategies.
数字内容产品存在高度的不确定性,因此许多数字内容平台采取面向所有用户的免费促销策略来应对这一问题。然而,数字内容产品的多样性和用户行为偏好的异质性可能会混淆免费促销对用户的影响。因此,为了优化营销资源的分配,平台亟须调整先前的免费内容促销策略。本文基于个体级别的异质处理效应,发展了个性化的免费内容促销策略,并进一步探究了促销效果异质性的来源,尤其是用户参与水平相关变量的调节作用。为此,我们利用国内一家大型电子书平台提供的随机田野实验数据,采用机器学习与计量因果推断相结合的框架,估计出个体级别的处理效应并分析免费内容促销的潜在机制。分析结果显示,平均而言,免费内容促销将导致用户的付费金额显著增加。然而,用户参与水平越高,促销带来的付费增长就越低,因为参与水平更高的用户更容易受到免费内容促销的蚕食效应的影响。本研究引入了一种新颖的因果研究方法,能帮助电子书平台改善其营销策略。
基金
supported by the Anhui Postdoctoral Scientific Research Program Foundation(2022B579).
