DocumentCode
2321236
Title
Application of clustering on credit card customer segmentation based on AHP
Author
Ying, Li ; Yuanyuan, Wu
Author_Institution
Bus. Sch., East China Univ. of Sci. & Technol., Shanghai, China
Volume
3
fYear
2010
fDate
9-10 Jan. 2010
Firstpage
1869
Lastpage
1873
Abstract
It has been crucial for credit card operators to conduct targeted marketing with effective customer segmentation recently years. The clustering analysis of data mining technology is the most effective tool for this, and the selection of indicators means a lot on the results of segmentation in the meanwhile. In this paper, we select two algorithms, AHP (Analytical Hierarchy Process) for indicator optimization, and K-means for clustering. Based on briefly theoretical analysis of the algorithms, we carry out a case study using the data of credit card customers from a commercial bank of Shanghai, and develop the corresponding marketing strategies, possessing certain theoretical value and practical significance.
Keywords
banking; credit transactions; customer relationship management; data mining; decision making; marketing data processing; optimisation; pattern clustering; AHP; Shanghai commercial bank; analytical hierarchy process; clustering analysis; credit card customer segmentation; credit card operators; data mining technology; indicator optimization; k-means; marketing strategy; targeted marketing; theoretical analysis; Algorithm design and analysis; Business; Clustering algorithms; Credit cards; Data analysis; Data mining; Eigenvalues and eigenfunctions; Electronic mail; Resource management; Testing; AHP; Credit Card; Index System; K-means; Segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Logistics Systems and Intelligent Management, 2010 International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4244-7331-1
Type
conf
DOI
10.1109/ICLSIM.2010.5461312
Filename
5461312
Link To Document