摘要
证券公司对于客户的挖掘和分类有利于挖掘潜在客户和做出适当的营销决策。本文将决策树、逻辑斯蒂回归和贝氏机率分类算法用于判断被访者是否购买股票,以此挖掘潜在客户,用K-means聚类法将股票购买者划分不同的类型,并建议采取不同的服务和营销方式,提高客户的忠诚度。
It＇s benifit to securities companies by making appropriate marketing decisions and mining the potential customers through mining and classification of their customers. Decision Tree, logistic regression, Bayesian probability classification algorithm are used to judge whether the customers will buy some stocks or not to potential customers. Different categories of customers can be got by K-means cluster through analyzing the existing customers of securities companies. Thereby different services will be adopted to satisfy the different demands from different customers and to enhance the customer loyalty.
出处
《统计研究》
CSSCI
北大核心
2008年第9期49-53,共5页
Statistical Research
基金
国家教育部社科研究规划项目(06JA910003)资助
关键词
数据挖掘
决策树
聚类分析
Data mining
Decision Tree
Cluster analysis
