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Selling Consumer Data for Profit: Optimal Market-Segmentation Design and Its Consequences

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  • Kai Hao Yang

Abstract

A data broker sells market segmentations to a producer with private cost who sells a product to a unit mass of consumers. This paper characterizes the revenue-maximizing mechanisms for the data broker. Every optimal mechanism induces quasi-perfect price discrimination. All the consumers with values above a cost-dependent cutoff buy by paying their values while the rest of consumers do not buy. The characterization implies that market outcomes remain unchanged even if the data broker becomes more powerful—either by gaining the ability to sell access to consumers or by becoming a retailer who purchases the product and sells to the consumers exclusively.

Suggested Citation

  • Kai Hao Yang, 2022. "Selling Consumer Data for Profit: Optimal Market-Segmentation Design and Its Consequences," American Economic Review, American Economic Association, vol. 112(4), pages 1364-1393, April.
    • Handle: RePEc:aea:aecrev:v:112:y:2022:i:4:p:1364-93
    DOI: 10.1257/aer.20210616
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    Citations

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    Cited by:

    1. Alessandro Bonatti, 2023. "The Platform Dimension of Digital Privacy," NBER Chapters, in: The Economics of Privacy, National Bureau of Economic Research, Inc.
    2. Smolin, Alex & Ichihashi, Shota, 2022. "Data Collection by an Informed Seller," TSE Working Papers 22-1330, Toulouse School of Economics (TSE).
    3. Shota Ichihashi & Alex Smolin, 2023. "Buyer-Optimal Algorithmic Consumption," Papers 2309.12122, arXiv.org, revised Oct 2023.
    4. Ronen Gradwohl & Moshe Tennenholtz, 2023. "Selling Data to a Competitor (Extended Abstract)," Papers 2307.05078, arXiv.org.
    5. Tommaso Bondi & Omid Rafieian, 2023. "Privacy and Polarization: An Inference-Based Approach," Working Papers 23-09, NET Institute.
    6. Han Wang, 2023. "Contracting with Heterogeneous Researchers," Papers 2307.07629, arXiv.org.
    7. Jacopo Bizzotto & Adrien Vigier, 2022. "A Case for Tiered School Systems," Working Papers 202205, Oslo Metropolitan University, Oslo Business School.
    8. Ronen Gradwohl & Moshe Tennenholtz, 2023. "Selling Data to a Competitor," Papers 2302.00285, arXiv.org.
    9. Bonatti, Alessandro & Bergemann, Dirk, 2022. "Data, Competition, and Digital Platforms," CEPR Discussion Papers 17544, C.E.P.R. Discussion Papers.
    10. Shota Ichihashi & Alex Smolin, 2022. "Data Provision to an Informed Seller," Papers 2204.08723, arXiv.org, revised Mar 2023.
    11. Rong, Jianxin & Wang, Dazhong, 2023. "Contracting in hierarchical platforms," Economics Letters, Elsevier, vol. 226(C).
    12. Maslov, Alexander & Noiset, Luc & Schwartz, Jesse A., 2022. "A closer look at two conjectures about irregular marginal revenue," Economics Letters, Elsevier, vol. 218(C).
    13. Liang, Annie & Madsen, Erik, 2024. "Data and incentives," Theoretical Economics, Econometric Society, vol. 19(1), January.
    14. Tal Alon & Paul Dutting & Yingkai Li & Inbal Talgam-Cohen, 2022. "Bayesian Analysis of Linear Contracts," Papers 2211.06850, arXiv.org, revised Jul 2023.
    15. Jacopo Bizzotto & Adrien Vigier, 2022. "Sorting and Grading," Papers 2208.10894, arXiv.org, revised Feb 2024.
    16. Yang, Kai Hao, 2023. "On the continuity of outcomes in a monopoly market," Journal of Mathematical Economics, Elsevier, vol. 108(C).

    More about this item

    JEL classification:

    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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