• DocumentCode
    2159253
  • Title

    An Empirical Study of Customer Churn in E-Commerce Based on Data Mining

  • Author

    Wu Heng-liang ; Zhang Wei-wei ; Zhang Yuan-yuan

  • Author_Institution
    Sch. of Manage. Sci. & Eng., Shandong Inst. of Bus. & Technol., Yantai, China
  • fYear
    2010
  • fDate
    24-26 Aug. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    With the e-commerce market competition becoming more and more furious, it has become one of the focuses of companies that how to avoid customer churn and carry out customer retention. This paper applies many techniques of data mining to the research of customer churn, such as clustering analysis, decision tree, neural network, etc, establishes an e-commerce customer churn model and analyzes the factors which influence customer retention.
  • Keywords
    consumer behaviour; customer relationship management; data mining; decision trees; electronic commerce; neural nets; pattern clustering; clustering analysis; customer churn; customer retention; data mining; decision tree; e-commerce market competition; neural network; Analytical models; Artificial neural networks; Companies; Data mining; Data models; Decision trees;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management and Service Science (MASS), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5325-2
  • Electronic_ISBN
    978-1-4244-5326-9
  • Type

    conf

  • DOI
    10.1109/ICMSS.2010.5576627
  • Filename
    5576627
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2159253