基于RFM的电商数据客户价值细分实例研究  

Case Study on Customer Value Segmentation of E-commerce Data Based on RFM

作　　者：许雪晶 林辰玮 XU Xue-jing;LIN Chen-wei(School of Information Engineering,Putian University,Putian 351100,China;Meizhouwan Vocational Technology College,Putian 351119,China)

机构地区：[1]莆田学院信息工程学院,福建莆田351100 [2]湄洲湾职业技术学院,福建莆田351119

出　　处：《长春师范大学学报》2021年第4期60-69,共10页Journal of Changchun Normal University

基　　金：莆田学院科研项目“电商网站客户分类信息系统研究”(2018023);莆田市科技局基金项目“基于关联规则的莆田国美电器的客户关系挖掘系统研究与实现”(2018GP2006)。

摘　　要：为了分析某遥控模型电商公司的客户给企业带来的收益,对现有的已注册客户进行客户价值细分,利用RFM模型结合K-means聚类算法对该公司2018年期间的28162条订单交易数据进行聚类,并对其评价、分析和研究。实验表明,基于RFM模型并结合K-means聚类算法能对客户进行有效的细分,因此可以通过适当的营销手段刺激消费,为企业带来更多的收益。In order to analyze the revenue brought by the customers of a remote control model E-commerce company,the customer value of the existing registered customers is subdivided.The RFM model combined with K-means clustering algorithm is used to cluster the 28162 order transaction data of the company in 2018,and its evaluation,analysis and research are carried out.Experiments show that RFM model combined with K-means can effectively segment customers,so it can stimulate consumption through appropriate marketing means,and then bring more profits to company.

关 键 词：RFM模型 K-MEANS聚类 客户价值分析 客户细分 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]