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.
Keywords
- Classification model
- extended Bayes model
- customer classification prediction
- weighted Bayes algorithm
- lifetime value
- customer loyalty degree
- client capital credit
- fuzzy neural network
- Markov chain
Cite this article
@article{cai-11043,
author = {Qiaohong Zu and Ting Wu and Hui Wang},
title = {A Multi-factor Customer Classification Evaluation Model},
journal = {Computing and Informatics},
volume = {29},
number = {4},
pages = {509--520},
year = {2010},
issn = {1335-9150},
url = {https://cai.type.sk/content/2010/4/a-multi-factor-customer-classification-evaluation-model/}
}
TY - JOUR AU - Qiaohong Zu AU - Ting Wu AU - Hui Wang TI - A Multi-factor Customer Classification Evaluation Model JO - Computing and Informatics VL - 29 IS - 4 SP - 509 EP - 520 PY - 2010 SN - 1335-9150 UR - https://cai.type.sk/content/2010/4/a-multi-factor-customer-classification-evaluation-model/ KW - Classification model KW - extended Bayes model KW - customer classification prediction KW - weighted Bayes algorithm KW - lifetime value KW - customer loyalty degree KW - client capital credit KW - fuzzy neural network KW - Markov chain ER -
Zu, Q., Wu, T., & Wang, H. (2010). A Multi-factor Customer Classification Evaluation Model. Computing and Informatics, 29(4), 509–520. https://cai.type.sk/content/2010/4/a-multi-factor-customer-classification-evaluation-model/