东北大学学报(自然科学版) ›› 2006, Vol. 27 ›› Issue (12): 1393-1396.DOI: -

• 论著 • 上一篇    

基于数据挖掘的客户价值预测方法

赵晓煜;黄小原;   

  1. 东北大学工商管理学院;东北大学工商管理学院 辽宁沈阳110004;辽宁沈阳110004
  • 收稿日期:2013-06-23 修回日期:2013-06-23 出版日期:2006-12-15 发布日期:2013-06-23
  • 通讯作者: Zhao, X.-Y.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(70572088)

Method based on data mining to forecast customers' value

Zhao, Xiao-Yu (1); Huang, Xiao-Yuan (1)   

  1. (1) School of Business Administration, Northeastern University, Shenyang 110004, China
  • Received:2013-06-23 Revised:2013-06-23 Online:2006-12-15 Published:2013-06-23
  • Contact: Zhao, X.-Y.
  • About author:-
  • Supported by:
    -

摘要: 提出了一种利用聚类和分类等数据挖掘技术预测客户价值的新方法.通过对客户历史交易数据的分析,获得能够综合反映老客户忠诚度和价值度的指标.基于该指标对老客户进行聚类,将老客户划分为若干个不同价值的客户群,即为每个老客户赋予一个价值等级标号.利用朴素贝叶斯分类方法来预测新客户(或潜在客户)的价值,并依据预测结果来制定相应的重点客户发展战略.实例验证了该方法的有效性和可行性.

关键词: 数据挖掘, 客户价值, 聚类, 朴素贝叶斯分类, 预测

Abstract: A new method to forecast customers' value is put forward using such data mining techniques as clustering and classification. The indicators reflecting old customers' value and business integrity are gained through analyzing the historical transaction data. Then, these old customers are clustered and further classified into different groups in accordance to their value indicators, i.e., each and every old customer is assigned with a mark equivalent to its value. The naive Bayesian classification method is used to forecast new or potential customers' value, and a relevant customer development strategy is thus available. A numerical example is given to verify the effectiveness and practicability of the method proposed.

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