Competitive targeted online advertising

Sanxi Li, Hailin Sun and Jun Yu

International Journal of Industrial Organization, 2023, vol. 87, issue C

Abstract: This paper examines how an online publisher utilizes its information about consumer preference to target advertising. In our model, two firms first bid for a prominent ad position in a publisher-organized position auction, and then compete on price in the subsequent product marketplace. We consider two dimensions of consumer heterogeneity. First, consumers are heterogeneous in product preference. Based on their tastes, some consumers prefer one product over the other, whereas other consumers may rank the products in an opposite order. Second, consumers differ in search preference, i.e., “nonshoppers” only consider the advertised product, while “shoppers” always search both firms’ products before buying. We show that targeted advertising based on product preference will mitigate price competition in product markets as well as competition in position auctions, the latter to the detriment of the publisher. In contrast, targeted advertising based on search preference always benefits the publisher, as the winning firm can charge monopoly prices to nonshoppers. We show that the publisher’s optimal choice is to utilize only the information about consumer search preference. We also explore the welfare implications of targeted advertising based on different types of consumer preference.

Keywords: Online shopping platforms; Targeted advertising; Position auction; Price discrimination (search for similar items in EconPapers)
JEL-codes: D2 D4 L1 L2 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:indorg:v:87:y:2023:i:c:s0167718723000061

DOI: 10.1016/j.ijindorg.2023.102924

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