Title :
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.
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;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258703
