• DocumentCode
    3167209
  • Title

    Customer segmentation for B2C e-commerce websites based on the Generalized association rules and decision tree

  • Author

    Ma, Haiying ; Gang, Dong

  • Author_Institution
    Dept. of Manage. Sci. & Eng., East China Univ. of Sci. & Technol., Shanghai, China
  • fYear
    2011
  • fDate
    8-10 Aug. 2011
  • Firstpage
    4600
  • Lastpage
    4603
  • Abstract
    Today, as the rapid popularization of Internet applications, many Chinese businesses are attracted by huge profits and market space of e-commerce, beginning to join the area of e-commerce. How to keep effective customer, attract more members of the e-commerce website and expand the market effectively, is the problem that all the managers most concerned about. Through studying and comparing common customer segmentation models, this article is proposing a integrated model that combines the techniques of generalized association rules and decision tree. This model is used for customer segmentation for e-commerce websites. It can help managers understand customers, develop markets, and support decision-making.
  • Keywords
    Internet; Web sites; customer profiles; data mining; decision trees; electronic commerce; profitability; B2C e-commerce Web sites; Chinese businesses; Internet application; customer relationship management; customer segmentation model; decision making support; decision tree; e-commerce market space; generalized association rules; profitability; Association rules; Banking; Business; Credit cards; Decision trees; Internet; Association Rules; Customer Segmentation; Decision Tree; E-commerce Introduction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
  • Conference_Location
    Deng Leng
  • Print_ISBN
    978-1-4577-0535-9
  • Type

    conf

  • DOI
    10.1109/AIMSEC.2011.6010255
  • Filename
    6010255