Abstract: A novel customer segmentation method based on integration of customer’s static and dynamic attributes is developed.A weighted method of customer’s time series is proposed and statistical features of time series are adopted for customer clustering,which make each group of customers have similar sequence feature.A genetic algorithm approach is adopted to improve the clustering quality.Clustering result is combined with the static attributes of customer for further segmentation.Experimental result indicates that compared with traditional segmentation methods,the proposed method improves the accuracy of segmentation.

Key words: customer segmentation, time series, clustering, genetic algorithm