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机构地区:[1]南京理工大学经济管理学院,南京210094 [2]华中科技大学管理学院
出 处:《价值工程》2007年第6期6-10,共5页Value Engineering
基 金:教育部社科基金资助项目(KU07006);项目名称:高频金融时间序列预测数据挖掘方法研究;江苏省教育厅社科基金资助项目(05SJD630040);南京理工大学青年预研基金项目。
摘 要:现代商业银行已经认识到客户是企业的重要资源,成功地获得有价值的新客户和维系高价值客户是至关重要的。但目前,空前巨大的客户数据量使得准确识别有价值的个体客户变得复杂和难以有效实施。文中利用数据挖掘技术,抽取建立商业银行基于客户价值的客户识别模型所需要的知识,建立了一个考察客户目前价值、潜在价值和忠诚度的客户价值模型;并以此模型为基础进行客户识别与分割。此外,根据某商业银行的客户样本进行实例研究,划分出8个客户细分市场,根据每一细分市场的特点设计了简单的营销策略。Commercial banks have long recognized that customers are the important resource of the corporation, while acquiring the profit new customers and retaining the high value customers is the key. However, access to unprecedented amounts of individuallevel customer data may make such targeted promotional efforts increasingly difficult to effectively implement. To address this challenge, we build a customer identifying models based on customer value from individual-level. By using three dimensions, current value, potential value, and customer loyalty, a customer lifetime value model of individual customer was established. The methods by which profitable customers could be identified and segmented were explored through numerical example and corresponding marketing strategies were established by using the customer identifying result.
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