In: Computing and Informatics, vol. 29, no. 4
Q. Zu - T. Wu - H. Wang
A Multi-factor Customer Classification Evaluation Model
Year, pages: 2010, 509 - 520
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
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.
How to cite:
Zu, Q., Wu, T., Wang, H. 2010. A Multi-factor Customer Classification Evaluation Model. In Computing and Informatics, vol. 29, no.4, pp. 509-520. 1335-9150.
Zu, Q., Wu, T., Wang, H. (2010). A Multi-factor Customer Classification Evaluation Model. Computing and Informatics, 29(4), 509-520. 1335-9150.