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 to 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 over 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.

Keywords: Data-driven decision making, analytics, productivity, information technology, small and medium enterprises, management practices