A Multi-factor Customer Classification Evaluation Model

Authors

  • Qiaohong Zu
  • Ting Wu
  • Hui Wang

Keywords:

Classification model, extened Bayes model, customer classification prediction, weighted Bayes algorithm, lifetime value, customer loyalty degree, client capital credit, fuzzy neural network, Markov chain

Abstract

Pervasive application of data mining technology is very important in analytical CRM software development when the distributed data warehouse is constructed. We propose a multi-factor customer classification evaluation model CLV/CL/CC which comprehensively considers customer lifetime value, customer loyalty and customer credit. It classifies clients with synthetic data mining algorithms. In this paper, we present an extended Bayes model which substitutes the primary attribute group with a new attribute group to improve the classification quality of naive Bayes.

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Author Biographies

Qiaohong Zu

School of Logistics Engineering
Wuhan University of Technology
430 063 Wuhan, China

Ting Wu

School of Logistics Engineering
Wuhan University of Technology
430 063 Wuhan, China

Hui Wang

School of Logistics Engineering
Wuhan University of Technology
430 063 Wuhan, China

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Published

2012-01-26

How to Cite

Zu, Q., Wu, T., & Wang, H. (2012). A Multi-factor Customer Classification Evaluation Model. Computing and Informatics, 29(4), 509–520. Retrieved from http://147.213.75.17/ojs/index.php/cai/article/view/96