基于数据挖掘的促销决策支持系统

Sales promotion decision support system based on data mining

提出一种根据客户资料和购物历史数据进行数据挖掘的促销决策支持系统,该系统有机地结合RFM模型、关联规则和序列模式的数据挖掘技术,寻找企业最有价值的目标客户群,发掘目标客户群的商品购买模式,预测目标客户群的商品购买趋势,挖掘目标客户群的购买力,为企业提供动态、实时和准确的促销决策支持.使企业能对目标客户群采取有针对性的高效的促销措施,以更快的速度、更高的准确度和更出色的客户服务,满足客户个性化的需求,以提高企业的客户服务水平,建立并保持客户忠诚度,增加企业的销售额,降低企业的营销成本.实践证明,该系统高效且可广泛使用.

The sales promotion decision support system in which the customer data and legacy sales data are used for data mining is presented in this paper. The RFM model, the association rules and sequential patterns techniques are integrated in this system in order to seek the valued customer group, dig the purchased patterns, predict the purchasing trend, and inspire the purchasing power of the target customer group. It will provide dynamic, real time and exact sales promotion decision for the company. It could make the company to adopt efficient and pertinent sales promotion approaches to fit customers with faster, more exact and excellent services. It will satisfy the individuated needs, improve the quality of customer service, establish and keep customer faithfulness, increase sales, and reduce the marketing cost. This system has been proved to be efficient and could be applied widely.