基于RFM模型的物流客户价值研究  

Research on Logistics Customer Value Based on RFM Model

作　　者：陈倩舒 方晓平[1] CHEN Qianshu;FANG Xiaoping(Central South University,Changsha 410075,China)

机构地区：[1]中南大学

出　　处：《物流科技》2019年第7期19-22,共4页Logistics Sci-Tech

摘　　要：客户关系管理已成为企业管理战略转变的关键部分。客户关系管理的核心问题是对不同类型的客户进行价值分类,采用不同的定制化营销策略,更好地服务顾客,以最大限度地实现企业的效益。文章利用物流企业的客户历史消费数据,在RFM模型基础上,利用层次分析法确定指标权重,K-Means聚类算法进行客户细分对物流客户进行价值研究,并将物流客户细分为:一般价值客户、一般发展客户与重要保持客户。Customer relationship management has become a key part of the transformation of corporate management strate-gy. The core problem of customer relationship management is to classify different types of customers and adopt different customized marketing strategies to better serve customers to maximize the benefits of the company. In this paper, based on the historical consumption data of logistics enterprises, based on the RFM model, the analytic hierarchy process is used to determine the index weights. The K-Means clustering algorithm is used to conduct customer value research on logistics customers, and the logistics customers are subdivided into: Value customers, general development customers and important customers.

关 键 词：客户管理 RFM模型 数据挖掘 K-MEANS聚类算法 客户细分 

分 类 号：F274[经济管理—企业管理]