A Two-Layer Clustering Model for Mobile Customer Analysis

Chiung-I Chang · Jui-Chih Ho

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Customer churn and segmentation Advanced Clustering Algorithms Research Data Mining and Machine Learning Applications

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.

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2005Customer segmentation and strategy development based on customer lifetime value: A case study 2012A Customer Churn Prediction Model in Telecom Industry Using Boosting 2005Research on customer segmentation model by clustering 2011Segmentation of telecom customers based on customer value by decision tree model 2008Improving Personalization Solutions through Optimal Segmentation of Customer Bases 1992Marketing to Maximize Profitability 2012Telecom customer segmentation based on cluster analysis 2013Customer segmentation and analysis of a mobile telecommunication company of Pakistan using two phase clustering algorithm

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