基于RFM的客户分类及价值评价模型

激烈的市场竞争使得客户资源争夺成为企业成功的关键因素.正确的客户分类能帮助企业有效分配营销资源,针对性地加强客户联系、改善客户关系、增强客户忠诚度,使得企业获得核心竞争力.基于此,本文分析了客户分类与客户关系管理的关系以及神经网络技术在客户分类中的应用情况,利用自组织神经网络研究客户分类问题,以RFM为分析变量建立客户分类模型；比较输出层构造分别为“2×2”、“3×3”和“4×4”的自组织神经网络模型分类结果,确定最佳的自组织神经网络模型；利用层级分析法对“4×4”型自组织神经网络模型划分的16类客户进行价值分析、价值排序,得到每类客户具体的相对价值大小,为企业准确认识客户价值、合理分配资源提供依据.

The Model of Customer Classification and Evaluation of Customer Value based on RFM

With competition of enterprises becoming more and more severity,the decisive factor for survival and development of an enterprise is the capability of the enterprise for contending for customers.Therefore,a reasonable customer classification is a premise condition for allocation of enterprise resource and improving the relation between the enterprise and its customers.The relation between cusomer segmention and customer relationship management is analyzed and Nerver Network is applied in customer segmention.Using RFM,the customer classification model based on Self Organization Map(SOM)is established.The optimal export frame of the SOM customer classification model is 4×4 through analyzing the SOM model with the export frame of 2×2,3×3,4×4.Each kind of customer is thought having different current value by the analysis of the 16 kinds of customer classified on RFM.Furthermore,the contributing right of the customer current value is analyzed using analytic hierarchy process(AHP).The order of the current value of every kind of customer is also acquired through arrangement.