中文摘要：

顾客们对在强烈竞争的电子商务很重要。百分之二十个顾客生产百分之八十侧面，这被知道。因此，怎么发现这些顾客是很批评的。顾客一生价值(CLV ) 被介绍以崭新评估顾客，频率并且钱(RFM ) 变量。一个新奇模型被建议基于平均的订的 weighting (OWA ) 和 K 工具簇算法分析顾客购买数据和 RFM 变量。OWA 被采用在评估顾客一生价值或忠诚决定 RFM 变量的重量。K 工具算法被用来根据 RFM 价值聚类顾客。搅拌机顾客能被把每个簇组的 RFM 价值与平均 RFM 作比较发现。问询表被进行调查哪个原因引起顾客不满。评价这些原因帮助电子商务改进服务。试验性的结果证明了模型有效、讲理。

英文摘要：

Customers are of great importance to E-commerce in intense competition. It is known that twenty percent customers produce eighty percent profiles. Thus, how to find these customers is very critical. Customer lifetime value （CLV） is presented to evaluate customers in terms of recency, frequency and monetary （RFM） variables. A novel model is proposed to analyze customers purchase data and RFM variables based on ordered weighting averaging （OWA） and K-Means cluster algorithm. OWA is employed to determine the weights of RFM variables in evaluating customer lifetime value or loyalty. K-Means algo＇rithm is used to cluster customers according to RFM values. Churn customers could be found out by comparing RFM values of every cluster group with average RFM. Questionnaire is conducted to investigate which reasons cause customers dissatisfaction. Rank these reasons to help E-commerce improve services. The experimental results have demonstrated that the model is effective and reasonable.