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Customer Churn Prediction Embedded in an Analytical CRM Model

In: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Kotor, Montengero, 10-11 September 2015

Author

Listed:
  • Lázár, Ede

Abstract

This paper presents a practical implementation of an analytical customer relationship (CRM) model, which aims to increase the customer satisfaction, thereby reducing the rate of attrition. The analytical CRM model not only manages and synchronizes customer relationship management processes, but also creates added value regarding to customers by applying mathematical, predictive methods. This presented model was implemented at a Hungarian gas service provider, and estimates the probability of churn for each customer based on the characteristics of former and present customers. The methodological approach is based on econometrical background; the analytical tool is a binomial logistic regression model. As a result this study presents that using logistic regression models as predictive analytic tool we can fulfil multiple CRM goals. Using the theoretical framework of Swift (2001) we can state that the model consists of more CRM dimensions simultaneously. These are the predicted churn probability as a customer retention dimension, and the information about the efficiency of different CRM elements, and CRM channels, as a customer attraction dimension.

Suggested Citation

  • Lázár, Ede, 2015. "Customer Churn Prediction Embedded in an Analytical CRM Model," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2015), Kotor, Montengero, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Kotor, Montengero, 10-11 September 2015, pages 258-264, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    • Handle: RePEc:zbw:entr15:183657
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    References listed on IDEAS

    as
    1. Mathematica Policy Research, "undated". "Data Management (About Us)," Mathematica Policy Research Reports 650503a74edc4a0daa08ccbd1, Mathematica Policy Research.
    2. V. L. Miguéis & D. Van Den Poel & A.S. Camanho & J. Falcao E Cunha, 2012. "Modeling Partial Customer Churn: On the Value of First Product-Category Purchase Sequences," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/790, Ghent University, Faculty of Economics and Business Administration.
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    More about this item

    Keywords

    analytical CRM; predictive analytics; churn prediction; logistic regression;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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