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

Cowles Foundation Discussion Paper No. 2258

129 Pages Posted: 14 Oct 2020

See all articles by Kai Hao Yang

Kai Hao Yang

Cowles Foundation for Economic Research

Date Written: October 9, 2020

Abstract

A data broker sells market segmentations created by consumer data to a producer with private production cost who sells a product to a unit mass of consumers with heterogeneous values. In this setting, I completely characterize the revenue-maximizing mechanisms for the data broker. In particular, every optimal mechanism induces quasi-perfect price discrimination. That is, the data broker sells the producer a market segmentation described by a cost-dependent cutoff, such that all the consumers with values above the cutoff end up buying and paying their values while the rest of consumers do not buy. The characterization of optimal mechanisms leads to additional economically relevant implications. I show that the induced market outcomes remain unchanged even if the data broker becomes more active in the product market by gaining the ability to contract on prices; or by becoming an exclusive retailer, who purchases both the product and the exclusive right to sell the product from the producer, and then sells to the consumers directly. Moreover, vertical integration between the data broker and the producer increases total surplus while leaving the consumer surplus unchanged, since consumer surplus is zero under any optimal mechanism for the data broker.

Keywords: Price discrimination, Market segmentation, Mechanism design, Virtual cost

JEL Classification: D42, D82, D61, D83, L12

Suggested Citation

Yang, Kai Hao, Selling Consumer Data for Profit: Optimal Market-Segmentation Design and its Consequences (October 9, 2020). Cowles Foundation Discussion Paper No. 2258, Available at SSRN: https://ssrn.com/abstract=3710726 or http://dx.doi.org/10.2139/ssrn.3710726

Kai Hao Yang (Contact Author)

Cowles Foundation for Economic Research ( email )

New Haven, CT 06520
United States

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