¹Laboratory of Quantum Engineering and Quantum Materials, School of Physics and Tele-communication Engineering, South China Normal University, Guangzhou 510006, China
²NIT, ZheJiang University, Hanzhou, P.R.China
³Industrial Center, Shenzhen Polytechnic, Shenzhen , Guangdong, China

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Abstract—The paper presents a novel approach for customer segmentation which is the basic issue for an effective CRM ( Customer Relationship Management ). Firstly, the chi-square statistical analysis is applied to choose set of attributes and K-means algorithm is employed to quantize the value of each attribute. Then DBSCAN algorithm based on density is introduced to classify the customers into three groups (the first, the second and the third class). Finally biclustering based on improved Apriori algorithm is used in the three groups to obtain more detailed information. Experimental results on the dataset of an airline company show that the biclustering could segment the customers more accurately and meticulously. Compared with the traditional customer segmentation method, the framework described is more efficient on the dataset.

Index Terms—Customer segmentation, biclustering, Kmeans, Chi-square statistics, DBSCAN, Apriori

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Cite: Xiaohui Hu, Haolan Zhang , Xiaosheng Wu, Jianlin Chen, Yu Xiao, Yun Xue , Tiechen Li, Hongya Zhao, "A New Customer Segmentation Framework Based on Biclustering Analysis," Journal of Software vol. 9, no. 6, pp. 1359-1366, 2014.