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Measuring Churner Influence on Pre-paid Subscribers Using Fuzzy Logic

Author

Listed:
  • Louise Columelli

    (EURECOM)

  • Miguel Núñez del Prado

    (Universidad del Pacífico)

  • Leoncio Zarate-Gamarra

    (Peru IDI)

Abstract

In the last decades, mobile phones have become the major medium for communication between humans. The site effect is the loss of subscribers. Consequently, Telecoms operators invest in developing algorithms for quantifying the risk to churn and to influence other subscribers to churn. The objective is to prioritize the retention of subscribers in their network due to the cost of obtaining a new subscriber is four times more expensive than retaining subscribers. Hence, we use Extremely Random Forest to classify churners and non-churners obtaining a Lift value at 10% of 5.5. Then, we rely on graph-based measures such as Degree of Centrality and Page rank to measure emitted and received influence in the social network of the carrier. Our methodology allows summarising churn risk score, relying on a Fuzzy Logic system, combining the churn probability and the risk of the churner to leave the network with other subscribers.

Suggested Citation

  • Louise Columelli & Miguel Núñez del Prado & Leoncio Zarate-Gamarra, 2016. "Measuring Churner Influence on Pre-paid Subscribers Using Fuzzy Logic," Working Papers 16-22, Centro de Investigación, Universidad del Pacífico.
    • Handle: RePEc:pai:wpaper:16-22
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    References listed on IDEAS

    as
    1. Michela Bia & Alessandra Mattei, 2008. "A Stata package for the estimation of the dose–response function through adjustment for the generalized propensity score," Stata Journal, StataCorp LP, vol. 8(3), pages 354-373, September.
    2. Friedman, Jerome H., 2002. "Stochastic gradient boosting," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 367-378, February.
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    Keywords

    Churn; Data mining; Classification and Fuzzy logic;
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