A Customer Intelligence System Based on Improving LTV Model and Data Mining

Author

Chen, Yu-zhe ; Zhao, Ming-hua ; Zhao, Shu-liang ; Wang, Yan-jun

Author_Institution

Coll. of Math. & Inf. Sci., Hebei Normal Univ.

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

1352

Lastpage

1357

Abstract

Customer relationship management is one of the leading business strategies for today´s companies, the key to successful implementation of CRM is customer intelligence. This paper designs and implements a customer intelligence system based on improving LTV model and data mining. Two data mining techniques are used including self-organizing map and fuzzy decision tree. The proposed system provides such functions as customer identification, customer loyalty analysis, customer satisfaction analysis, profitable customer segmentation, and customer differentiation. It can be used to make customer strategies

Keywords

competitive intelligence; customer relationship management; data mining; decision trees; fuzzy set theory; self-organising feature maps; CRM; LTV model; customer differentiation; customer identification; customer intelligence system; customer loyalty analysis; customer relationship management; customer satisfaction analysis; data mining techniques; fuzzy decision tree; profitable customer segmentation; self-organizing map; Companies; Customer relationship management; Customer satisfaction; Cybernetics; Data mining; Decision trees; Educational institutions; Electronic mail; Intelligent systems; Learning systems; Machine learning; Mathematical model; Customer Intelligence; Customer Relationship Management; Fuzzy Decision Tree; Self-Organizing Map;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.258703

Filename

4028274