中文摘要：

在分析客户行为的随机性和非确定性的基础上，指出现有的确定性客户细分方法不能很好地适应客户细分问题的这些特点．为此，提出基于云模型的动态客户细分模型，该模型将客户细分过程表示为一个C过程与一个P过程，并将描述非确定关系的云模型理论引入到客尸细分的P过程中，从而实现了客户细分的动态性，提高了模型对客户行为描述的客观性．文章采用来自UCI的合成数据及来自银行的实际客户数据进行了数据实验，实验结果表明了该方法的有效性．

英文摘要：

Customer segmentation is one of the basic functions in customer relationship management. Most of the customer segmentation methods definitely classified the customer into different classes according to their attributes. But these definite classification methods can＇t fit the customer segmentation tasks well, for the uncertain and stochastic characteristics of customer behavior. The shortcoming of current definite customer segmentation methods consisted of a C-process and a P-process according to the uncertainty and the heterogeneity in data space of customers＇ behaviors. The proposed new model could meet the requirement in presenting the uncertainty of customers＇ behaviors by introduced the cloud model theory in to the P-process. A synthetic data experiment and a real data experiment indicated the effectiveness of this method.