Real-Time Sales Data, Streamer Improvisation, and Sales Performance: Evidence From Live Stream Selling
Yumei He et al.
Abstract
Live stream selling has surged as an innovative form of e-commerce, supporting high social interactivity and fast-paced sales for large-scale audiences. However, live streamers must manage complex, concurrent tasks— such as presenting products, engaging with viewers, and employing various sales tactics to facilitate consumer purchases, while dealing with uncertainty in foreseeing viewers’ reactions and time pressure for selling products. This study examines the role of real-time sales data in influencing streamers’ impromptu decision-making and sales outcomes in live stream selling. On the one hand, real-time sales data might exacerbate the already complex decision-making, overwhelming and distracting streamers. On the other hand, it may help streamers improvise their tactics and utilize time more efficiently and effectively to improve sales performance. In partnership with a leading global live stream selling platform, we analyzed data from a randomized field experiment to unravel whether, how, and under which conditions the provision of real-time sales data affects live stream sales performance. The streamers in the experiment were randomly assigned to either the treatment group, which had access to real-time sales data for presale products, or the control group, which had no such access. Our results reveal that product sales of presale products in the treatment group increased by approximately 40.21% compared to those in the control group. Further, the observed main effect can be explained by streamers’ data-driven improvisation in promotional, linguistic, and presentational pace tactics. Moreover, heterogeneity analyses reveal that the positive effect of real-time data on sales performance is more salient for streamers with likely better improvisational skills and for products with higher uncertainty, thereby providing suggestive evidence of streamer improvisation as the underlying mechanism. This study contributes to the literature on data-driven decision-making, evidencing the importance of real-time data for enhancing decision-making processes and outcomes. Our findings also offer guidance for implementing real-time data infrastructure in live stream selling platforms.
2 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.25 × 0.4 = 0.10 |
| M · momentum | 0.55 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.