Digitizing local search: An empirical analysis of mobile search behavior in offline shopping

Mobile devices have become increasingly prevalent in the context of consumers' offline search and shopping behavior by acting as personal decision support tools. This paper investigates the relationship between consumers' real-time location and their search behavior when shopping offline. We develop two location-specific measures based on mobile device usage to analyze the association between a consumer's real-time location and their search behavior: Present store distance and present store density. We apply these measures to a unique dataset from a leading mobile product information app that includes >13 million search sessions from 2.5 million consumers searching for 1.8 million different products. Our findings show that store distance and store density significantly influence consumers' mobile search behavior: detailed searches for product-specific attributes (search depth) increase as store distance decreases and store density increases, while the number of jointly searched products within the same category (search breadth) increases as store distance and density increase. We also find that durable products weaken the main effects of store distance and density on search depth but strengthen it for search breadth. These results provide insights for offline retailers to better understand locationspecific consumer demands and improve their mobile in-app targeting and product assortment decisions.