Customer Future Profitability Assessment: A Data-Driven Segmentation Function Approach

  • Chunhua Tian
  • Wei Ding
  • Rongzeng Cao
  • Michelle Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4055)


One of the important tasks in customer relationship management is to find out the future profitability of individual and/or groups of customers. Data mining-based approaches only provide coarse-grained customer segmentation. It is also hard to obtain a high-precision structure model purely by using regression methods. This paper proposes a data-driven segmentation function that provides a precise regression model on top of the segmentation from a data mining approach. For a new customer, a structure model constructed from profit contribution data of current customers is adopted to assess the profitability. For an existing customer, external information such as stock value performance is taken into the regression model as well as historical trend prediction on the profit contribution. In addition, this paper shows how the proposed approach works and how it improves the customer profitability analysis through experiments on the sample data.


Customer Relationship Management Future Profitability Customer Lifetime Current Customer Customer Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chunhua Tian
    • 1
  • Wei Ding
    • 1
  • Rongzeng Cao
    • 1
  • Michelle Wang
    • 2
  1. 1.IBM China Research LabBeijingChina
  2. 2.IBM Business Consulting ServicesBeijingChina

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