An Exploration of Customer Segmentation Methods Based on Clustering Algorithm in the Context of Big Data

Abstract

Accompanied by the continuous development of big data technology, various industries are well aware of the advantages of big data, which are widely used in customer service work, especially in the support of customer segmentation work, and have achieved good results. In this paper, for the problems of large fluctuation of clustering results and low clustering purity in the traditional data mining process, the big data precision mining technology with improved clustering algorithm is proposed. And it is applied in the field of customer segmentation, and the experimental results show that the improved clustering algorithm is applied in customer segmentation, the result curve fluctuation amplitude is small, and the clustering purity is significantly higher than the traditional algorithm.