Customer Shopping Behavior and the Persistence of Revenues and Earnings

Abstract

Using GPS location data from customers’ mobile devices that encompasses nearly 2.9 billion visits to over 1 million retail locations belonging to 286 U.S. firms, we develop new measures of customer shopping behavior (CSB) and show these to be associated with revenue and earnings persistence. Specifically, revenues and earnings are more persistent when a firm’s customers (a) are repeat rather than one-time customers, (b) live closer to retail locations, (c) spend more time in retail locations, (d) have less variable shopping patterns, and (e) shop during the week rather than on weekends. After demonstrating that CSB can help to understand the implications of current revenues and earnings for the future, we examine whether investors, analysts, and managers fully incorporate CSB into their decisions. We find that investors and analysts do not fully incorporate CSB into trading decisions and revenue forecasts, which leads to predictable stock returns and forecast errors. However, investment decisions by managers align with CSB. Our results illustrate conditions under which revenues and earnings are sustainable and which stakeholder decisions are consistent with insights provided by customer data.

Keywords: customers, revenues, earnings persistence, market efficiency, big data

JEL Classification: M41, M31, G14, G31