클러스터링 기법을 활용한 이커머스 사용자 리뷰에 따른 시장세분화 연구
Published in 한국전자거래학회지, 2022
Recently, as COVID-19 has made the e-commerce market expand widely, customers who have different consumption patterns appear in the market. Because companies can obtain opinions and information of customers from reviews, they increasingly face the requirements of managing customer reviews on online platform. In this study, we analyze customers and carry out market segmentation for classifying and defining type of customers in e-commerce. Specifically, K-means clustering was conducted on customer review data collected from Wemakeprice online shopping platform, which leads to the result that six clusters were derived. Finally, we define the characteristics of each cluster and propose a customer management plan. This paper is possible to be used as materials which identify types of customers and it can reduce the cost of customer management and make a profit for online platforms.
Recommended citation: 김민경, 허재석*, 사애진, 전아름, 이한별 (2022), 클러스터링 기법을 활용한 이커머스 사용자 리뷰에 따른 시장세분화 연구, 한국전자거래학회지, 27(2), 21-36. (KCI)
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