From Social to Purchase: Customer Selection in Social Group Buying

选择(遗传算法) 业务 营销 社会商业 团购 群(周期表) 广告 计算机科学 社会化媒体 万维网 人工智能 有机化学 化学
作者
Cheng Yan,Shaochong Lin,Zuo‐Jun Max Shen
出处
期刊:Production and Operations Management [Wiley]
卷期号:34 (6): 1512-1530 被引量:3
标识
DOI:10.1177/10591478241302761
摘要

Social scope group buying has emerged as an increasingly popular promotional strategy and has served as a new customer acquisition tool. In the service industry, companies use social group buying (SGB) to recruit new customers and promote full-price products. Through SGB activities, customers can trade their social capital to form buying groups, experience SGB-offered sample products, and further alleviate uncertainty regarding expensive full-price products before making a final purchase. We investigate this novel SGB phenomenon by examining customers’ decisions throughout the “experience-conversion” process. In collaboration with a leading online educational platform, we examine customers’ grouping behavior during SGB activities and analyze their subsequent purchases. Our analysis reveals an interesting pattern in which non-grouped customers have a higher proportion of full-price product purchases than grouped customers. We postulate that, in addition to observations from operational data, unobserved social information is important for gaining a deeper understanding of the customer behaviors underlying this pattern. Employing a Bayesian learning framework, we model customers’ three-stage discrete-choice decision-making processes and quantify two influential social information factors: social cost and social learning. By incorporating social information, our Bayesian learning model demonstrates improved effectiveness in assisting companies with accurately predicting final purchases in the conversion process. We provide actionable insights into how companies can employ our model to strategically tailor SGB designs by customer segments to increase overall purchase rates. Our study sheds light on the significance of social information in enhancing customer management and refining SGB design.
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