Engagement maximization

Benjamin Hébert () and Weijie Zhong ()
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Benjamin Hébert: Graduate School of Business, Stanford University
Weijie Zhong: Graduate School of Business, Stanford University

Theoretical Economics, Forthcoming

Abstract: We investigate the management of information provision to maximize user engagement. A principal sequentially reveals signals to an agent who has a limited amount of information processing capacity and can choose to exit at any time. We identify a "dilution" strategy---sending rare but highly informative signals---that maximizes user engagement. The platform's engagement metric shapes the direction and magnitude of biases in provided information relative to a user-optimal benchmark. Even without intertemporal commitment, the platform replicates full-commitment revenue by inducing the user's belief to remain "as uncertain as" the prior until the rare, decisive signal arrives and induces stopping. We apply our results to two contexts: an ad-supported internet media platform and a teacher attempting to engage test-motivated students.

Keywords: Information acquisition; recommendation algorithms; polarization; rational inattention (search for similar items in EconPapers)
JEL-codes: D83 D86 (search for similar items in EconPapers)
Date: 2026-03-26
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