Selling Consumer Data for Profit: Optimal Market-Segmentation Design and Its Consequences
American Economic Review
vol. 112,
no. 4, April 2022
(pp. 1364-93)
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.Citation
Yang, Kai Hao. 2022. "Selling Consumer Data for Profit: Optimal Market-Segmentation Design and Its Consequences." American Economic Review, 112 (4): 1364-93. DOI: 10.1257/aer.20210616Additional Materials
JEL Classification
- D42 Market Structure, Pricing, and Design: Monopoly
- D82 Asymmetric and Private Information; Mechanism Design
- D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- L81 Retail and Wholesale Trade; e-Commerce
- M31 Marketing