Exploring business opportunities from mobile services data of customers: An inter-cluster analysis approach

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We use customer clustering to explore the behavioral patterns of customers who subscribe to mobile services. Two clustering techniques, K-means and KVQ, are used to cluster customers using knowledge about attributes that are broadly grouped under usage, revenue, services, and user categories. We used inter-cluster analysis on the clusters generated from the two techniques to compare the distribution of customers among the different categories of attributes. We observed that it was important to use multiple techniques for clustering. Our analysis discovered several interesting facts about customers, such as the imbalance between customers’ usage of mobile services, subscriptions to services, and revenue contributions. These knowledge nuggets could enable mobile service providers to better align their marketing strategies with the needs of customers.

论文关键词:Clustering,Customer profiling,Kohonen vector quantization,K-means,Mobile telecommunication

论文评审过程:Received 3 April 2009, Revised 19 May 2009, Accepted 26 July 2009, Available online 4 August 2009.

论文官网地址:https://doi.org/10.1016/j.elerap.2009.07.006