Consumer Search and Purchase: An Empirical Investigation of Search-Based Retargeting

Abstract

This paper empirically investigates how marketers can retarget consumers based on their behaviors in the previous search process, a practice we call “search-based retargeting”. To infer the relationship between search activities and preferences of retargeted consumers, we develop a dynamic consumer search model that is based on Weitzman’s model (1979) but it incorporates several key modifications. Based on the model estimation results, we explore the effectiveness of retargeting by studying two types of marketing actions. We find that, when the marketing action is to recommend a seller and provide full seller information, the retargeting value is high for consumers with intensive search and for sellers with high conversion rates. When the marketing action is couponing, it is more useful for a seller to target “own” customers rather than competitors’ customers who have previously clicked into other sellers’ pages but not his. The retargeting value is high for consumers who have searched multiple sellers and have searched the seller first in the search process, and for sellers with high click rates. By charging sellers for either the seller recommendation or the coupon delivery, the online retail platform will obtain a substantial profit gain, and sellers and consumers are also benefited. However, the gains from the seller recommendation are significantly higher, suggesting that providing the seller information is more important as a retargeting strategy.