This study explores whether NielsenIQ scanner data from U.S. retailers contain incremental information about the GAAP revenue of corresponding manufacturers. Using retail product/store/week data from 2006 to 2018, we construct a measure of aggregated consumer purchases at the manufacturer/quarter level, and find that it strongly predicts GAAP revenues. In addition, analyst forecasts of revenues have predictable errors, which implies that analysts do not fully incorporate the information in consumer purchases. Exploring investment implications, we find that hedge portfolios that buy (sell) stocks of firms with high (low) abnormal consumer purchases generate annualized returns on the magnitude of 14%–19%, depending on specification. Overall, these findings suggest that scanner data on consumer purchases provide an information edge over GAAP revenue, shedding light on the benefits of using transactional data.

本研究探讨来自美国零售商的 NielsenIQ 扫描仪数据是否包含有关相应制造商的 GAAP 收入的增量信息。使用 2006 年至 2018 年的零售产品/商店/周数据，我们构建了制造商/季度级别的总体消费者购买量度，并发现它强烈预测 GAAP 收入。此外，分析师对收入的预测存在可预测的错误，这意味着分析师没有将信息完全纳入消费者购买中。在探索投资影响时，我们发现购买（出售）具有高（低）异常消费者购买的公司股票的对冲投资组合产生了 14%–19% 的年化回报，具体取决于规格。总体而言，这些调查结果表明，消费者购买的扫描仪数据提供了优于 GAAP 收入的信息优势，