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
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;
Conference_Titel :
Logistics Systems and Intelligent Management, 2010 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-7331-1
DOI :
10.1109/ICLSIM.2010.5461312
