What do measures of real-time corporate sales say about earnings surprises and post-announcement returns?

Customer Loyalty and the Persistence of Revenues and Earnings

“…Our findings complement recent research that finds big data can increase price efficiency (Froot et al 2017;Kang et al 2021;Zhu 2019) by highlighting a source of potentially relevant information for market participants. Although recent evidence suggests that analysts and investors do incorporate new data sources in their analyses and investment strategies, we find that data on customer loyalty is not fully incorporated into analysts' forecasts and not immediately impounded into stock prices by investors.…”

“…Several studies use new data sources to predict the amount of a firm's revenues. For example, Trueman et al (2001) show that traffic on a firm's website can be used to predict revenues, Froot et al (2017) show that real-time measures of web searches on mobile devices for 50 large U.S. retailers explain quarterly revenues, and Chiu et al (2020) show that Google searches of firm products can be used to predict revenue growth. Second, we use customer data not to predict revenues directly but rather to explain variation in the persistence of revenues and earnings.…”

Leveraging Big Data to Study Information Dissemination of Material Firm Events

“…Investors often get information about material firm events through the firms' own disclosures or traditional media (Bushee et al [2010], Miller and Skinner [2015]). With the emergence of new technologies in capturing data (e.g., obtained from satellite images and Web traffic), recent research (e.g., Froot et al [2017]; Zhu [2019]) documents that big data could be a timely information source for price discovery and corporate governance. Therefore, an evaluation of the value of big data relative to firms' disclosures and traditional media coverage of material firm events is a worthy research inquiry.…”

“…Third, the big data considered by most prior studies are at the quarterly frequency. Our real-time foot traffic data allow us to explore how quickly the stock market incorporates high-frequency big data (see also Froot et al [2017]). Finally, our findings contribute to the operations literature (e.g., Hendricks and Singhal [2005a, b]) that documents the adverse financial effects of operational disruptions.…”

The Firm Next Door: Using Satellite Images to Study Local Information Advantage

“…Finally, our study adds to the emerging field that uses big data to examine economic questions generally (Froot et al. [2017]), as well as research examining the impact of big data in particular (Zhu [2019]). Our study is especially timely given that investors now routinely supplement the formal financial statements with less traditional information sources like the data used in this study (Goldman Sachs [2016]).…”