直播流媒体
产品(数学)
计算机科学
影响力营销
长尾
价值(数学)
业务
营销
广告
多媒体
数学
统计
机器学习
几何学
关系营销
市场营销管理
作者
Hailiang Chen,Yifan Dou,Yongbo Xiao
标识
DOI:10.1016/j.elerap.2023.101266
摘要
The rise of live-streaming e-commerce has attracted the wide participation of online influencers, brands, and retailers. Live streamers offer a fresh shopping experience to consumers through broadcasting product demonstrations and communicating with them. This study characterizes the streamers' behavior and explores the key drivers of live-streaming e-commerce success as measured by gross merchandise value (GMV) and fan growth. We employ both machine learning and econometric methods to analyze a unique dataset of 55,096 shows by the top 1,000 live streamers on Alibaba's live streaming platform. We identify three distinct clusters. The most important differentiating features include a live streamer's platform affiliation and product category. Selling more products and spending more time on each product in a live-streaming show are two factors driving both GMV and fan growth. We also discover that a large fan base does not always help, as the positive effect of fan base only exists conditionally.
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