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Persuading Customers to Buy Early: The Value of Personalized Information Provisioning

Author

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  • Kimon Drakopoulos

    (Data Sciences and Operations, Marshall School of Business, University of Southern California, Los Angeles, California 90089)

  • Shobhit Jain

    (Data Sciences and Operations, Marshall School of Business, University of Southern California, Los Angeles, California 90089)

  • Ramandeep Randhawa

    (Data Sciences and Operations, Marshall School of Business, University of Southern California, Los Angeles, California 90089)

Abstract

We study a pricing and information provisioning game between a better-informed seller (such as a retailer) and its customers. The seller is (ex post) better informed about product availability and can choose how to communicate this information to the customers. The customers are heterogeneous in their valuation for the product. The firm optimizes on publicly posted prices (which are the same for all customers) and its information provisioning (which can be personalized). Using a Bayesian persuasion framework, we find that public information provisioning, in which the firm sends the same information to all customers, has limited value. However, personalized information provisioning, in which the firm can share different information with different customers, has significant value and has attributes very similar to personalized pricing. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.

Suggested Citation

  • Kimon Drakopoulos & Shobhit Jain & Ramandeep Randhawa, 2021. "Persuading Customers to Buy Early: The Value of Personalized Information Provisioning," Management Science, INFORMS, vol. 67(2), pages 828-853, February.
    • Handle: RePEc:inm:ormnsc:v:67:y:2021:i:2:p:828-853
    DOI: 10.1287/mnsc.2020.3580
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    References listed on IDEAS

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    1. Kostas Bimpikis & Yiangos Papanastasiou & Wenchang Zhang, 2024. "Information Provision in Two-Sided Platforms: Optimizing for Supply," Management Science, INFORMS, vol. 70(7), pages 4533-4547, July.
    2. Saeed Alaei & Ali Makhdoumi & Azarakhsh Malekian, 2025. "Revenue Maximization Under Unknown Private Values with Nonobligatory Inspection," Operations Research, INFORMS, vol. 73(3), pages 1307-1319, May.
    3. Arian Aflaki & Qian (Ken) Zhang, 2026. "Is Your Price Personalized? Alleviating Customer Concerns with Inventory Availability Information," Operations Research, INFORMS, vol. 74(1), pages 181-198, January.
    4. Zheng, Shiyuan & Jiang, Changmin, 2025. "Government persuasion strategies for transport infrastructure adaptation: Spillover effects and social welfare impacts," Transportation Research Part B: Methodological, Elsevier, vol. 196(C).
    5. Thomas Mariotti & Nikolaus Schweizer & Nora Szech & Jonas von Wangenheim, 2023. "Information Nudges and Self-Control," Management Science, INFORMS, vol. 69(4), pages 2182-2197, April.
    6. Mehdi H. Farahani & Milind Dawande & Ganesh Janakiraman & Shouqiang Wang, 2025. "Avoiding Fields on Fire: Information Dissemination Policies for Environmentally Safe Crop-Residue Management," Management Science, INFORMS, vol. 71(8), pages 6683-6706, August.
    7. Ronen Gradwohl & Niklas Hahn & Martin Hoefer & Rann Smorodinsky, 2022. "Algorithms for Persuasion with Limited Communication," Mathematics of Operations Research, INFORMS, vol. 47(3), pages 2520-2545, August.
    8. Yonatan Gur & Gregory Macnamara & Ilan Morgenstern & Daniela Saban, 2023. "Information Disclosure and Promotion Policy Design for Platforms," Management Science, INFORMS, vol. 69(10), pages 5883-5903, October.
    9. Sina Khorasani & Ersin Körpeoğlu & Vish V. Krishnan, 2024. "Dynamic Development Contests," Operations Research, INFORMS, vol. 72(1), pages 43-59, January.
    10. Ricardo Alonso & Odilon Câmara, 2024. "Organizing Data Analytics," Management Science, INFORMS, vol. 70(5), pages 3123-3143, May.
    11. Biswas, Indranil & Pagare, Dewang & Tiwari, Sunil & Choi, Tsan-Ming, 2025. "Managing supply chains facing extreme weather: Supplier’s nature and investment," European Journal of Operational Research, Elsevier, vol. 325(3), pages 457-473.
    12. Jerry Anunrojwong & Krishnamurthy Iyer & David Lingenbrink, 2024. "Persuading Risk-Conscious Agents: A Geometric Approach," Operations Research, INFORMS, vol. 72(1), pages 151-166, January.
    13. Kostas Bimpikis & Giacomo Mantegazza, 2023. "Strategic Release of Information in Platforms: Entry, Competition, and Welfare," Operations Research, INFORMS, vol. 71(5), pages 1619-1635, September.
    14. Feng, Zhuo & Gao, Ying & Song, Jinbo & He, Qiaochu, 2025. "An analysis of information disclosure in build–operate–transfer road projects," European Journal of Operational Research, Elsevier, vol. 322(1), pages 292-306.
    15. Zheng, Shiyuan & Jia, Rongwen & Shang, Wen-Long & Fu, Xiaowen & Wang, Kun, 2023. "Promote transport facility Resilience: Persuasion or Subsidy?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    16. Tal Avinadav & Tatyana Chernonog & Noam Shamir, 2025. "Information Provision from a Platform to Competing Sellers: The Role of Strategic Ambiguity," Manufacturing & Service Operations Management, INFORMS, vol. 27(1), pages 269-286, January.
    17. Can Küçükgül & Özalp Özer & Shouqiang Wang, 2022. "Engineering Social Learning: Information Design of Time-Locked Sales Campaigns for Online Platforms," Management Science, INFORMS, vol. 68(7), pages 4899-4918, July.
    18. Ozan Candogan & Huseyin Gurkan, 2025. "The Value of Information Design in Supply Chain Management," Management Science, INFORMS, vol. 71(8), pages 6545-6558, August.
    19. Ozan Candogan, 2022. "Persuasion in Networks: Public Signals and Cores," Operations Research, INFORMS, vol. 70(4), pages 2264-2298, July.

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