Two-layer Clustering Model for Mobile Customer Analysis

Abstract

Customer segmentation provides an effective and efficient way to obtain insights into customer characteristics and behavioral preferences. To enhance customer relationship management and focus on a dynamically changing marketplace, the authors built a two-layer clustering model for mobile telecom customer analysis. The first layer identifies the cluster by domain in accordance with the contribution of the basic degree of customer segmentation. The second layer uses clustering algorithms to group together highly homogeneous groups and identify representative groups to explain the group's characteristics. It then builds a mobile-user clustering model based on customer attributes to help enterprises view changes in customer value and behavior. The clustering results of this study are readable, have marketing implications, and are intuitive. They can be combined with products to assist marketing staff with effective marketing. After verification, this method achieves the desired results.