• DocumentCode
    3251782
  • Title

    Mining optimal actions for profitable CRM

  • Author

    Ling, Charles X. ; Chen, Tielin ; Yang, Qiang ; Cheng, Jie

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Western Ontario, London, Ont., Canada
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    767
  • Lastpage
    770
  • Abstract
    Data mining has been applied to CRM (Customer Relationship Management) in many industries with a limited success. Most data mining tools can only discover customer models or profiles (such as customers who are likely attritors and customers who are loyal), but not actions that would improve customer relationship (such as changing attritors to loyal customers). We describe a novel algorithm that suggests actions to change customers from an undesired status (such as attritors) to a desired one (such as loyal). Our algorithm takes into account the cost of actions, and further it attempts to maximize the expected net profit. To our best knowledge, no data mining algorithms or tools today can accomplish this important task in CRM. The algorithm is implemented, with many advanced features, in a specialized and highly effective data mining software called Proactive Solution.
  • Keywords
    customer relationship management; data mining; Proactive Solution; customer relationship management; data mining tools; optimal actions mining; Business; Computer science; Cost function; Customer relationship management; Data mining; Electronic mail; Intelligent structures; Marine vehicles; Software algorithms; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, 2002. ICDM 2003. Proceedings. 2002 IEEE International Conference on
  • Print_ISBN
    0-7695-1754-4
  • Type

    conf

  • DOI
    10.1109/ICDM.2002.1184049
  • Filename
    1184049