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Engagement maximization

Author

Listed:
  • Hébert, Benjamin

    (Graduate School of Business, Stanford University)

  • Zhong, Weijie

    (Graduate School of Business, Stanford University)

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.

Suggested Citation

  • Hébert, Benjamin & Zhong, Weijie, 0. "Engagement maximization," Theoretical Economics, Econometric Society.
    • Handle: RePEc:the:publsh:6567
    as

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    References listed on IDEAS

    as
    1. Filip Matêjka & Alisdair McKay, 2015. "Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model," American Economic Review, American Economic Association, vol. 105(1), pages 272-298, January.
    2. Dmitry Orlov & Andrzej Skrzypacz & Pavel Zryumov, 2020. "Persuading the Principal to Wait," Journal of Political Economy, University of Chicago Press, vol. 128(7), pages 2542-2578.
    3. Jeffrey Ely & Alexander Frankel & Emir Kamenica, 2015. "Suspense and Surprise," Journal of Political Economy, University of Chicago Press, vol. 123(1), pages 215-260.
    4. Andrew Caplin & Mark Dean & John Leahy, 2022. "Rationally Inattentive Behavior: Characterizing and Generalizing Shannon Entropy," Journal of Political Economy, University of Chicago Press, vol. 130(6), pages 1676-1715.
    5. Maryam Saeedi & Yikang Shen & Ali Shourideh, 2024. "Getting the Agent to Wait," Papers 2407.19127, arXiv.org.
    6. Alexander Frankel & Emir Kamenica, 2019. "Quantifying Information and Uncertainty," American Economic Review, American Economic Association, vol. 109(10), pages 3650-3680, October.
    7. Hébert, Benjamin & Woodford, Michael, 2023. "Rational inattention when decisions take time," Journal of Economic Theory, Elsevier, vol. 208(C).
    8. Benjamin Hébert & Jennifer La’O, 2023. "Information Acquisition, Efficiency, and Nonfundamental Volatility," Journal of Political Economy, University of Chicago Press, vol. 131(10), pages 2666-2723.
    9. Jeffrey C. Ely & Martin Szydlowski, 2020. "Moving the Goalposts," Journal of Political Economy, University of Chicago Press, vol. 128(2), pages 468-506.
    10. Sims, Christopher A., 2010. "Rational Inattention and Monetary Economics," Handbook of Monetary Economics, in: Benjamin M. Friedman & Michael Woodford (ed.), Handbook of Monetary Economics, edition 1, volume 3, chapter 4, pages 155-181, Elsevier.
    11. Hebert, Benjamin & Zhong, Weijie, 2022. "Engagement Maximization," Research Papers 4035, Stanford University, Graduate School of Business.
    12. Benjamin Hébert & Michael Woodford, 2021. "Neighborhood-Based Information Costs," American Economic Review, American Economic Association, vol. 111(10), pages 3225-3255, October.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

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    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law

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