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基于RFM分析模式的零售业客户分群实现过程 被引量:3

The Process of Cluster Customers Based on the RFM Model
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摘要 CRM系统近年来得到人们的广泛研究。客户分群作为CRM系统中的一个分支,是进行其他决策工作的基础之一。简单有效的客户分群方法利用了RFM分析模式,从数据库中提取出这3个影响因子的值,作为分析的依据,接着采用K-平均值算法,实现了对数据分群的操作,具有一定的实用价值。 Nowadays, the CRM system is studied by people popularly. The core of the CRM is how to cluster our customers. An efficient method is using the RFM model. It extractives the RFM, and then uses the K-mean algorithm to cluster the customers.
作者 周欢
出处 《金陵科技学院学报》 2008年第1期33-36,共4页 Journal of Jinling Institute of Technology
作者简介 周欢(1981-),女,江苏扬州人,硕士研究生.助教,研究方向:计算机数据库技术,商业智能。
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  • 1[美]KotlerP ArmstrongG著 俞利军译.营销学导论[M].北京:华夏出版社,1997.624-633.
  • 2Berger P D, Bechwati N N. The allocation of promotion budget to maximize customer equity [ J ]. Omega, 2001,29:49 - 61.
  • 3Dwyer F R. Customer lifetime valuation to support marketing decision making[J ]. Journal of Direct Marketing, 1989,8(2) :73 - 81.
  • 4Tao Y H, Rosa Yeh C C. Simple database marketing tools in customer analysis and retention[J]. International Journal of Information Management,2003,23:291 - 301.
  • 5Cohen M D. Exploiting response models:optimizing crosssell and up- sell opportunities in banking[J ]. Information Systems,2004,29(4) :327 - 341.
  • 6Miglautsch J. Thoughts on RFM scoring[J]. The Journal of Database Marketing, 2000,8 (1): 35 - 43.
  • 7Schell E. The case for database marketing[J]. Catalog Age,2003,20(2) :50.
  • 8Hughes M A. Boosting response with RFM[J]. American Demographics, 1996, (5) :4 - 9.
  • 9Hughes M A. Making your database pay off using recency frequency and monetary analysis[ Z]. Http://www. dbmarketing, com/articles/art104a, htm.
  • 10Novo J. Drilling down:turning customer data into profits with a spreadsheet[ M ]. Bangor: booklocker, com,2001.

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