文献类型：期刊文献

中文题名：基于客户价值的期货业客户聚类细分方法

英文题名：Customer clustering segmentation method for futures industry based on customer value

作者：陈智高[1];陈月英[1];常香云[1]

机构：[1]华东理工大学商学院,上海200237

年份：2006

卷号：46

期号：Z1

起止页码：1046

中文期刊名：清华大学学报（自然科学版）

外文期刊名：Journal of Tsinghua University(Science and Technology)

收录：CSTPCD;;EI(收录号：20070110348815);Scopus;北大核心:【北大核心2004】；CSCD:【CSCD2011_2012】；

基金：上海市科技发展基金软科学研究基金项目(056921047)

语种：中文

中文关键词：客户关系管理;期货业;客户价值;聚类分析;客户细分

外文关键词：customer relationship management;futures industry;customer value; clustering analyses;customer segmentation

摘要：针对目前国内外学者较少重视的期货业客户细分问题,提出了可操作的期货业客户细分方法。通过对中国期货业面临的市场服务问题和客户特点的分析,认为解决问题的关键是对期货客户进行有效细分,支持期货企业差异化服务的实现。依据期货业客户管理特点构建了期货业客户价值预测模型,提出基于客户当前价值和增值价值的两维聚类细分方法。以某期货公司为案例描述了方法的实际应用,证明了所提方法可行性。
This paper studies customer segmentation issues and proposes feasible method in futures industry,on which scholars paid limited attention.With the analysis of the market service problem that futures industry confronts with and its customer characteristics,this paper suggests that the key to the solution is to provide customers with individualized service by making effective segmentation of futures customers.According to the characteristics of customer management in futures industry,it proposes a customer value predicting model and a set of algorithms for futures industry,and a two-dimension clustering segmentation method of current and expected value is presented.Finally,the paper takes one futures company as an example to illustrate the application of the method,and verify its feasibility.