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首页> 外文会议>International Conference on Cybernetics and Information Technologies, Systems and Applications(CITSA2004) and 10th International Conference on Information Systems Analysis and Synthesis(ISAS2004) vol.1 >The Empirical Study of Applying Data Mining to Escalate Marketing Performance
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The Empirical Study of Applying Data Mining to Escalate Marketing Performance

机译：应用数据挖掘提升营销绩效的实证研究

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摘要

CRM is the process of controlling efficient, cost-effective flow knowledge to individual customers' requirements, and interaction with customers through channels for the purpose of escalating the customer's lifetime value. In other words, product is the core business process of traditional marketing, while customer is the core business process of CRM. The former concerns which product is the best sales while the latter does which customer is faithful. In order to digest the individual customer, we should set up customer's perfect database which contains date of interaction with each customer, such as primary information, transaction, service, activities and the like. To evaluate the performance, we should forecast customer's buying preference; to trace the trailing, we should use Bob Stone's (1996) R-F-M criteria (recency, frequency, monetary amount) through database. The research collects and analyzes references on promoting buying rate; moreover, it introduces R-F-M criteria, brings up the idea of identify each individual customer to promote both the marketing profit and the customer's lifetime value. The result shows that marketing performance derive from gini-weighted RFM model has the advantage over traditional RFM model by 24.80%.
机译：CRM是一种控制高效，经济高效的流程知识以适应单个客户需求的过程，并通过渠道与客户进行交互以提高客户的生命周期价值。换句话说，产品是传统营销的核心业务流程，而客户是CRM的核心业务流程。前者关注哪种产品是最好的销售，而后者则关注哪个客户是忠实的。为了消化单个客户，我们应该建立客户的理想数据库，其中包含与每个客户交互的日期，例如主要信息，交易，服务，活动等。要评估效果，我们应该预测客户的购买偏好；为了追踪尾迹，我们应该通过数据库使用Bob Stone（1996）的R-F-M标准（汇率，频率，金额）。该研究收集并分析了有关提高购买率的参考资料；此外，它引入了R-F-M标准，提出了识别每个客户的想法，以促进营销利润和客户的生命周期价值。结果表明，基尼加权RFM模型获得的营销绩效比传统RFM模型具有24.80％的优势。

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