Mobile customer clustering based on call detail records for marketing campaigns

  • Lin Q
  • Wan Y
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Abstract

Competition in the mobile telecommunications industry is becoming more and more fierce. In order to improve mobile operator’s competitiveness and customer value, several data mining technologies can be used. One of most important data mining technologies is customer clustering analysis. This targeting practice has been proven manageable and effective for mobile telecommunications industry. Most telecommunications carriers cluster their mobile customers by billing data. This paper proposes to cluster mobile customers based on their call detail records (CDR). It clusters customers based on real CDR, and analyzes their behaviors. Based on the analyzed results of the clustering model, the paper suggests practical proposals for the mobile operators’ marketing. Furthermore, it compares marketing effectiveness before and after using the clustering, and proves that new promoting strategy has visible effects.

Author-supplied keywords

  • Call detail records (CDR)
  • Clustering
  • Customer behavior
  • Mobile telecommunication operators

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Authors

  • Qining Lin

  • Yan Wan

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