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.
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