The Value of Consumer Data in Online Advertising

Marc Bourreau, Caillaud Bernard and Romain de Nijs ()
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Caillaud Bernard: Paris School of Economics – Ecole des Ponts ParisTech, Paris, France
Romain de Nijs: CREST – Ecole Polytechnique, Palaiseau, France

Review of Network Economics, 2017, vol. 16, issue 3, 269-289

Abstract: In this paper we propose a model where consumer personal data have multidimensional characteristics, and are used by platforms to offer ad slots with better targeting possibilities to a market of differentiated advertisers through real-time auctions. A platform controls the amount of information about consumers that it discloses to advertisers, thereby affecting the dispersion of advertisers’ valuations for the slot. We first show by way of simulations that the amount of consumer-specific information that is optimally revealed to advertisers increases with the degree of competition on the advertising market and decreases with the cost of information disclosure for a monopolistic platform, competing platforms or a welfare-maximizing platform, provided the advertising market is not highly concentrated. Second, we exhibit different properties between the welfare-maximizing situation and the imperfectly competitive market situations with respect to how the incremental value of information varies: there are decreasing social returns to consumers’ data, while private returns may be increasing or decreasing locally.

Keywords: auction; data; online advertising (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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Related works:
Working Paper: The Value of Consumer Data in Online Advertising (2017)
Working Paper: The Value of Consumer Data in Online Advertising (2017)
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DOI: 10.1515/rne-2017-0066

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