DocumentCode
3251782
Title
Mining optimal actions for profitable CRM
Author
Ling, Charles X. ; Chen, Tielin ; Yang, Qiang ; Cheng, Jie
Author_Institution
Dept. of Comput. Sci., Univ. of Western Ontario, London, Ont., Canada
fYear
2002
fDate
2002
Firstpage
767
Lastpage
770
Abstract
Data mining has been applied to CRM (Customer Relationship Management) in many industries with a limited success. Most data mining tools can only discover customer models or profiles (such as customers who are likely attritors and customers who are loyal), but not actions that would improve customer relationship (such as changing attritors to loyal customers). We describe a novel algorithm that suggests actions to change customers from an undesired status (such as attritors) to a desired one (such as loyal). Our algorithm takes into account the cost of actions, and further it attempts to maximize the expected net profit. To our best knowledge, no data mining algorithms or tools today can accomplish this important task in CRM. The algorithm is implemented, with many advanced features, in a specialized and highly effective data mining software called Proactive Solution.
Keywords
customer relationship management; data mining; Proactive Solution; customer relationship management; data mining tools; optimal actions mining; Business; Computer science; Cost function; Customer relationship management; Data mining; Electronic mail; Intelligent structures; Marine vehicles; Software algorithms; Technology management;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, 2002. ICDM 2003. Proceedings. 2002 IEEE International Conference on
Print_ISBN
0-7695-1754-4
Type
conf
DOI
10.1109/ICDM.2002.1184049
Filename
1184049
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