• DocumentCode
    3500785
  • Title

    Customer Retention Based on BP ANN and Survival Analysis

  • Author

    Zhang, Guozheng

  • Author_Institution
    Coll. of Bus., Houzhou Dianzi Univ., Hangzhou
  • fYear
    2007
  • fDate
    21-25 Sept. 2007
  • Firstpage
    3406
  • Lastpage
    3411
  • Abstract
    "Customer retention" is an increasingly pressing issue in today\´s ever-competitive commercial arena. This is especially relevant and important for sales and services related industries. This paper focus on constructing a new customer retention framework based on BP ANN (artificial neural network) and survival analysis. The new customer retention framework constituted of two parts, one is the BP ANN survival analysis model which integrates ANN technology and survival analysis to predict customer likelihood of defection and estimating customer value, the other is CLV (customer lifetime value) & CSP (customer survival phase) segment model which segment customer into different cluster to target high value, retainable customer. Effective actions triggered by these models could be the key to eventual customer retention. The empirical analysis is based on 23560 customers selected from the data warehouse of a large Chinese telecommunications company. This paper also suggests some propositions for further research.
  • Keywords
    backpropagation; customer relationship management; neural nets; BP artificial neural network; customer lifetime value; customer likelihood of defection; customer retention; customer survival phase; survival analysis; Artificial neural networks; Business; Educational institutions; Forward contracts; Hazards; Marketing and sales; Predictive models; Pressing; Profitability; Strategic planning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-1311-9
  • Type

    conf

  • DOI
    10.1109/WICOM.2007.843
  • Filename
    4340618