Helping Small Businesses Become More Data-Driven: A Field Experiment on eBay

Abstract

As digitization sweeps across industries and markets, analytics and data-driven decision making (DDD) are becoming increasingly important. The adoption of analytics and DDD has been slower in small-to-medium enterprises (SMEs) compared with large firms, and reliable causal estimates of the impacts of analytics tools for small businesses have been lacking. We derive experiment-based estimates of the impact of an analytics tool on SME outcomes, analyzing the randomized introduction of eBay’s Seller Hub (SH), a data-rich seller dashboard. We find that SH adoption is associated with increased DDD and that access to SH increases e-retailers’ revenues by 3.6% on average, as more items are transacted and service quality increases, without increases in average prices. Our results suggest that analytics and DDD help SMEs establish a competitive advantage. Managerial practices play an important role in reaping the benefits from the analytics dashboard, as more than a third of the SH impact is driven by active performance monitoring. Digital platforms should therefore embed analytics tools to support SMEs to increase entry and revenues. Furthermore, policies to support small businesses’ transition to the data era should address analytics and DDD gaps by ensuring access to both tools like SH and to appropriate managerial training. This paper was accepted by Anindya Ghose, information systems. Funding: This work was supported by the United States-Israel Binational Science Foundation [Grant 2018263]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2021.02026 .