Approaches to Clustering in Customer Segmentation

  • Authors

    • Shreya Tripathi
    • Aditya Bhardwaj
    • Poovammal E
    2018-07-20
    https://doi.org/10.14419/ijet.v7i3.12.16505
  • Customer Relationship Management, Customer Segmentation, Clustering, K-Means Clustering, Hierarchical Clustering

  • Abstract

    Customer Relationship Management(CRM) has always played a crucial role as a market strategy for providing organizations with the quintessential business intelligence for building, managing and developing valuable long-term customer relationships. A number of business enterprises have come to realize the significance of CRM and the application of technical expertise to achieve competitive advantage. This study explores the importance of Customer Segmentation as a core function of CRM as well as the various models for segmenting customers using clustering techniques. The available clustering models for customer segmentation, in general, and the major models of K-Means and Hierarchical Clustering, in particular, are studied and the virtues and vices of the techniques are pointed out. Finally, the possibility of developing a hybrid solution by the combination of the above two techniques, having the ability to outperform the individual models, is discussed.

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  • How to Cite

    Tripathi, S., Bhardwaj, A., & E, P. (2018). Approaches to Clustering in Customer Segmentation. International Journal of Engineering & Technology, 7(3.12), 802-807. https://doi.org/10.14419/ijet.v7i3.12.16505

    Received date: 2018-07-29

    Accepted date: 2018-07-29

    Published date: 2018-07-20