Digitizing Offline Search: An Empirical Analysis of Mobile Search Behavior in Offline Shopping
47 Pages Posted: 8 May 2015 Last revised: 23 Dec 2020
Date Written: December 23, 2020
Mobile devices have become increasingly important in the context of consumers’ offline search and shopping behavior. This paper theorizes and tests the impact of consumers’ real-time geographic location on their search behavior when shopping offline. More specifically, we develop two location-specific measures, (1) present store distance and (2) present store density, to investigate the effects on the depth and breadth of search. We test our hypotheses using a unique data set of a leading mobile product information app that includes 67 million unique search activities of 2.5 million consumers searching for 1.8 million different products. We find that search depth decreases with increasing present store distance and increases with increasing present store density. In addition, search breadth increases with increasing present store distance and increasing present store density. Finally, durable products mitigate the relationships of distance and density with search depth but amplify their relationships with search breadth. These results help retailers and brands to gain a better understand of consumers’ location-specific product preferences, which can be used for more precise mobile ad targeting, local product assortment and (pop-up) store location decisions.
Keywords: Consumer Search, Retailing, Location-Based Services, Big Data, Random Coefficient Model
JEL Classification: M31, D83, C23, C25, L86
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