When Your Friends Become Sellers: An Empirical Study of Social Commerce Site Beidian

TL;DR

This paper provides the first comprehensive measurement study of Beidian, a rapidly growing social commerce platform in China, analyzing its network structure, growth mechanisms, and user purchasing behavior to understand its unique properties.

Contribution

It offers the first quantitative analysis of the network characteristics, growth dynamics, and user behavior in a large-scale social commerce platform, highlighting its decentralized structure and strong-tie influence.

Findings

Beidian has a decentralized network structure.

Growth driven by invitation cascades.

High user loyalty correlates with purchase behavior.

Abstract

Past few years have witnessed the emergence and phenomenal success of strong-tie based social commerce. Embedded in social networking sites, these E-Commerce platforms transform ordinary people into sellers, where they advertise and sell products to their friends and family in online social networks. These sites can acquire millions of users within a short time, and are growing fast at an accelerated rate. However, little is known about how these social commerce develop as a blend of social relationship and economic transactions. In this paper we present the first measurement study on the full-scale data of Beidian, one of the fastest growing social commerce sites in China, which involves 11.8 million users. We first analyzed the topological structure of the Beidian platform and highlighted its decentralized nature. We then studied the site's rapid growth and its growth mechanism via invitation cascade. Finally, we investigated purchasing behavior on Beidian, where we focused on user proximity and loyalty, which contributes to the site's high conversion rate. As the consequences of interactions between strong ties and economic logics, emerging social commerce demonstrates significant property deviations from all known social networks and E-Commerce in terms of network structure, dynamics and user behavior. To the best of our knowledge, this work is the first quantitative study on the network characteristics and dynamics of emerging social commerce platforms.