针对传统客户价值细分方法不够精细化的问题,提出一种基于变异系数的双聚类算法。该算法选用了变异系数作为相似性度量,运用启发武贪心策略,通过迭代增删行列的方式挖掘出客户消费记录中局部消费行为相似的客户群体。以某电信公司的电信客户细分为实例,将所提算法与K均值(K—means)算法进行性能比较,实验结果表明,所提算法具有更优的客户细分能力和更强的客户行为可解释能力。因此,它更有助于指导企业制定差异化营销策略。
To improve the refinement degree of traditional customer value segmentation method, we proposed the variation coefficient-based biclustering algorithm. The algorithm selects the variation coefficient as the similarity measurement, applies the heuristic greedy strategy, and by the way of iterating the rows' or columns' insertion and deletion, the algorithm mines the customer groups with similar local consuming behaviours from their consumption records. Taking the telecommunication customers segmentation in a certain Telecom as the example, we compared the performances of the proposed algorithm with k-means clustering algorithm. Experimental result indicated that the proposed algorithm has better ability of customer segmentation and stronger interpretable ability on customer behaviours. Therefore, it is more conducive to guiding the enterprises to develop differentiated marketing Strategies.