【摘要】 针对CRM客户分类,提出模拟退火算法与K均值算法相结合的聚类算法。利用模拟退火算法全局寻优能力改变k均值算法易陷入局部极值的缺点。经标准数据集检验,证明算法有效。根据烟草商业企业业务数据和卷烟营销特点分析,设计客户分类评价指标模型。将算法应用于烟草商业企业CRM客户分类,分类结果符合卷烟营销特点,从实用角度验证算法有效。根据客户分类设计了差异化CRM营销策略。更多还原

【Abstract】 Propose a simulated annealing K-means(SAKM) algorithm for CRM customer clustering,which use the global optimize ability of SA to remedy the local extremum shortcoming of KM.The standard data computational results indicate that it is better than the K-means algorithm.A clustering attributes model had been designed which come from the analyzing of tobacco commercial enter-prise’sale data and characteristic.Testify the SAKM in tobacco commercial enterprise CRM customer clustering,the result validate SAKM is in effect,and then propose a personal CRM strategy.更多还原