An Economic Framework for Generative Engines: Advertising or Subscription?

TL;DR

This paper develops a dynamic economic model to analyze how generative engines like ChatGPT decide between showing ads or offering ad-free subscriptions, balancing immediate revenue and long-term user engagement.

Contribution

It introduces a novel framework capturing query-level decisions and derives optimal policies for monetization strategies considering competition and user sensitivity.

Findings

Optimal ad policy follows a cutoff rule based on immediate payoff versus long-term value.

High ad revenue or low user sensitivity shifts policy toward more ads.

Presence of rivals encourages more ad-free responses to sustain user retention.

Abstract

Generative Engines (GEs) such as ChatGPT and Google's AI Overviews are rapidly reshaping search economics by delivering synthesized responses that allow users to bypass third-party websites, cutting those sites' advertising revenue. Yet this shift also leaves GEs facing their own monetization problem: whether to insert ads into synthesized responses or keep them ad-free to drive subscription conversions. In this paper, we introduce a dynamic framework to study this problem, which captures how query-level design choices shape user engagement, retention, and subscription conversion over time. Using this framework, we show that the optimal policy follows a cutoff rule: ads should only be shown to users only when the immediate ad payoff exceeds the long-term value of providing ad-free responses. This cutoff shifts toward with-ad responses when i) ad revenue is high or ii) users are less sensitive to ads, and toward ad-free responses when iii) subscription conversion becomes relatively more valuable. In addition, the presence of rival GEs shifts the optimal policy further toward ad-free responses, as ad-heavy monetization becomes less sustainable when users can freely switch to alternatives. Our findings reveal incentives for real-life generative engine providers to adopt designs that enhance user experience and long-term sustainability.