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从怀疑到笃信: 试用与基于学习的定价

From Doubt to Devotion: Trials and Learning-Based Pricing
Journal of Political Economy · 2026 · Tan Gan、Nicholas Wu

中文摘要

一个掌握信息的卖方设计了一种动态机制来销售体验品。卖方掌握关于产品匹配度的部分信息,而产品匹配度会影响买方的私人消费体验。我们刻画了这一动态知情委托人问题的均衡机制。掌握信息的卖方与不知情的买方之间的信念差距,加之买方的学习过程,催生了这样一类机制:向持怀疑态度的买方提供有限的产品使用权限,并在买方被良好体验打动时提供升级选项。视卖方的筛选技术而定,这表现为免费/折扣试用或分层定价,二者在数字市场中十分普遍。与静态环境相反,在均衡中拥有消费者数据反而可能降低卖方收入,因为卖方会利用数据预测买方的学习过程,并据此微调动态设计。

Abstract

An informed seller designs a dynamic mechanism to sell an experience good. The seller has partial information about the product match, which affects the buyer's private consumption experience. We characterize equilibrium mechanisms of this dynamic informed principal problem. The belief gap between the informed seller and the uninformed buyer, coupled with the buyer's learning, gives rise to mechanisms that provide the skeptical buyer with limited access to the product and an option to upgrade if the buyer is swayed by a good experience. Depending on the seller's screening technology, this takes the form of free/discounted trials or tiered pricing, which are prevalent in digital markets. In contrast to static environments, having consumer data can reduce sellers' revenue in equilibrium, as they fine-tune the dynamic design with their data forecasting the buyer's learning process.
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