Engagement Maximization

TL;DR

This paper analyzes how platforms can optimize information disclosure to maximize user engagement, revealing that sending rare, highly informative signals can effectively keep users engaged without requiring commitment.

Contribution

It introduces a dilution strategy for information provision that maximizes engagement and demonstrates how platforms can replicate full-commitment revenue without commitment.

Findings

Rare signals increase user engagement effectively.

Platforms can mimic commitment by controlling belief uncertainty.

The strategy applies to online media and educational contexts.

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.