全生命周期客户价值数据分析挖掘方法  

Customer value data mining based on the full life cycle

作　　者：徐晓敏[1] 谷晓燕[1] XU Xiaomin;GU Xiaoyan(School of Information Management,Beijing Information Science&Technology University,Beijing 100192,China)

机构地区：[1]北京信息科技大学信息管理学院,北京100192

出　　处：《北京信息科技大学学报（自然科学版）》2020年第2期6-9,20,共5页Journal of Beijing Information Science and Technology University

基　　金：国家自然科学基金资助项目(71701020)。

摘　　要：从客户全生命周期的角度构建客户价值分析模型,综合应用RFM分析法和K-means聚类算法对客户交易数据进行挖掘,结合客户全生命周期各阶段特点,给出不同客户在不同阶段价值提升的相应策略。最后以一个C2C网店的实际交易数据为例验证方法应用的有效性。The customer value analysis model is established based on the full life cycle.Customer transaction data is excavated by the integrated application of RFM analysis and K-Means clustering algorithm.Corresponding strategies of promotion value for customers in different stages are given in accordance with the characteristics of each phase of the customer life cycle.Taking the actual transaction data of a C2C shop as an example,the effectiveness of method application is verified in the end.

关 键 词：客户价值分析 RFM分析法 K-MEANS聚类算法 数据挖掘 

分 类 号：F274[经济管理—企业管理]