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数据仓库和数据挖掘技术的快速发展,促进着企业决策支持系统的不断更新,也促使企业与客户之间的经济关系发生着重大变革。客户关系管理(CRM)作为近年来数据挖掘技术在企业决策支持系统中又一新的应用,使企业在经营模式、销售战略以及市场服务等多元领域都突破了传统框架。传统的以产品为核心的生产经营战略也变革成“以客户为中心”的新型商业模式。客户关系管理中需要理解客户特性和客户行为,由于在与客户的经济交往的过程中存在一定的风险,利用基于数据挖掘的客户分类器,实现对客户群的认识、分类和评估,对客户风险进行管理,然后通过优化产品组合来实现客户获取、客户保留、客户忠诚和客户盈利的目的以及客户风险最小化。针对客户关系管理中数据挖掘处理工具这一重要环节,笔者试分析了数据挖掘技术让企业有能力最终认识数据的真正价值,即蕴藏在数据中的信息和知识。对于电子商务企业,丰富的数据源,自动收集的可靠数据使它很容易满足数据挖掘所必需要因素。论文从数据挖掘模式类型等内容出发,研究了电子商务企业如何利用数据挖掘技术,分析销售数据库中的数据,为个性化网络营销的实现服务。
The rapid development of data warehousing and data mining technology has promoted the continuous updating of enterprise decision support systems, and has also led to major changes in the economic relations between companies and customers. As a new application of data mining technology in enterprise decision support systems in recent years, customer relationship management (CRM) has enabled enterprises to break through the traditional framework in various fields such as business model, sales strategy and market services. The traditional product-centric production and management strategy has also changed into a new customer-centric business model. Customer relationship management needs to understand customer characteristics and customer behavior. Because there are certain risks in the process of economic interaction with customers, customer classification based on data mining is used to realize the understanding, classification and evaluation of customer groups, and to customer risk. Manage and then optimize the product mix to achieve customer acquisition, customer retention, customer loyalty and customer profitability as well as minimize customer risk. For the important part of data mining processing tools in customer relationship management, the author tried to analyze the data mining technology to enable enterprises to finally understand the real value of the data, namely the information and knowledge contained in the data. For e-commerce companies, rich data sources, and automated data collection make it easy to meet the data mining needs. Starting from the content of data mining patterns and other types, this paper studies how e-commerce companies use data mining technology to analyze data in sales databases to serve personalized online marketing.