基于数据挖掘技术的AFH客户分类应用研究

客户分类是客户关系管理(CRM)的重要研究内容,是企业开展一对一营销的重要基础。文章在分析传统的RFM模型和Marcus模型的基础上,提出了以客户平均购买额(Average monetary)、购买频率(Frequency)和客户保持时间(Hold time)作为客户价值细分变量的AFH客户分类模型,实例化构建了面向AFH客户分类主题的数据仓库,并从客户的贡献度(当前价值)和忠诚度(增值潜力)两个维度对客户AFH值进行Two-step和k-mease双重聚类分析,形成了基于客户生命周期利润(CLP)的客户价值矩阵,并提供了针对不同客户群的商业策略。应用结果表明,AFH客户分类模型具有很强的表征性,能充分反映客户的当前价值和增值潜力,能为企业提供有效的决策支持信息。

Applied Research on AFH Customer Classification based on Data Mining Technology

Customer classification is an important part of customer relationship management(CRM)research,it is an important basis for enterprises to develop one-to-one marketing.This paper through analysing traditional RFM model and the Marcus model,put forward the AFH customer classification model with customer value segmentation variables:customer Average Monetary(A-value),Frequency(F-value) and Hold time(H-value),and instantiated build data warehouse oriented AFH customer classification theme.Through two-step and K-mease double cluster analysis customers AFH-value from two perspectives,Contribution(current value)and loyalty(appreciation potential) of customer,form a customer value matrix based on customer life profit(CLP),and pointed out that the business strategy for different customer groups.The application results shows that the AFH customer classification model has evident characteristics,it can fully reflect the customer’s current value and appreciation potential and provide effective information for enterprises’ decision.