English

Engagement Maximization

Theoretical Economics 2025-12-12 v6

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

Cite

@article{arxiv.2207.00685,
  title  = {Engagement Maximization},
  author = {Benjamin Hébert and Weijie Zhong},
  journal= {arXiv preprint arXiv:2207.00685},
  year   = {2025}
}
R2 v1 2026-06-24T12:11:42.853Z