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Machine learning based classification and segmentation techniques for CRM: a customer analytics

Author

Listed:
  • Narendra Singh
  • Pushpa Singh
  • Krishna Kant Singh
  • Akansha Singh

Abstract

Machine learning and data mining help companies to build a tool that can make and take actions based on customer knowledge and information. Customer information is the base of maintaining long term relationship with customers and also known as customer relationship and management (CRM). Classification and segmentation of customer data set is utilised to maintain efficient relation with customers and subsequently increase the profitability and productivity. In this paper, author proposed customer segmentation based on demographic properties like gender, age and spending score and analysed the data set for interesting fact. The derived attribute data set is investigated for classification. Classification is used to categorise each customer into a number of classes, i.e., 'gold', 'silver', 'elite' and 'occasional'. Comparison of different classification algorithm is simulated by WEKA tool. Multi-layer perceptron (MLP) is found as the best classification algorithm with an accuracy of 98.33% compared to Naïve Bayes, regression and J48.

Suggested Citation

  • Narendra Singh & Pushpa Singh & Krishna Kant Singh & Akansha Singh, 2020. "Machine learning based classification and segmentation techniques for CRM: a customer analytics," International Journal of Business Forecasting and Marketing Intelligence, Inderscience Enterprises Ltd, vol. 6(2), pages 99-117.
    • Handle: RePEc:ids:ijbfmi:v:6:y:2020:i:2:p:99-117
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    Cited by:

    1. Minnu F. Pynadath & T. M. Rofin & Sam Thomas, 2023. "Evolution of customer relationship management to data mining-based customer relationship management: a scientometric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3241-3272, August.

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