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Customer Segmentation Using Machine Learning: A Credit Card Usage Clustering Approach

  • Unique Paper ID: 177017
  • Volume: 11
  • Issue: 12
  • PageNo: 6-8
  • Abstract:
  • This study applies unsupervised machine learning techniques to segment credit card users based on 18 behavioral variables. Using clustering algorithms like K-Means, Agglomerative Clustering, and Gaussian Mixture Models, we identify distinct customer groups. Principal Component Analysis (PCA) enhances clustering performance and visualization. The resulting segments—such as Big Spenders, Average Users, and High Riskers—offer actionable insights for marketing and risk management. Our approach demonstrates the potential of data-driven segmentation in financial analytics.
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  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 12
  • PageNo: 6-8

Customer Segmentation Using Machine Learning: A Credit Card Usage Clustering Approach

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