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.
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 ...
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2006年第12期1393-1396,共4页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(70572088)
关键词
数据挖掘
客户价值
聚类
朴素贝叶斯分类
预测
data mining
customer value
clustering
naive Bayesian classification
forecast
