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Churn Analysis in a Romanian Telecommunications Company

Author

Listed:
  • Andreea Dumitrache

    (PhD Student, Academy of Economic Studies, Bucharest, Romania)

  • Monica Mihaela Maer Matei

    (Conf. Univ. Dr., Academy of Economic Studies, Bucharest, Romania)

Abstract

Telecommunications is one of the sectors where the customer base plays a significant role in maintaining stable revenues, so special attention is paid to prevent their migration to other providers. Over time, businesses in the telecommunications industry have faced multiple threats of financial loss from migrating customers who want to leave their telecom service provider in exchange for other offers from competing companies. An effective prediction model of this action can not only be viewed as an insurance policy, supporting stable revenue, but also provides suggestions for database management so that potential migrant customers can benefit from personalized offers and services, depending on their profile, thus preventing their loss. The aim of this paper is to predict customers who are going to defect in a Romanian mobile telecommunications company. The churn analysis is developed for post-paid customers. We used logistic regression to predict churn and a solution based on smoothed bootstrap technique to correct for the drawbacks of imbalanced classes. In our study this procedure did not significantly improve the performance of the logistic classifier measured by AUC (Area Under the Receiver Operating Characteristic curve). So even after balancing the sample we still obtain a really reduced value of the AUC, making it difficult to correctly predict churn phenomenon on the available data set.

Suggested Citation

  • Andreea Dumitrache & Monica Mihaela Maer Matei, 2019. "Churn Analysis in a Romanian Telecommunications Company," Postmodern Openings, Editura Lumen, Department of Economics, vol. 10(4), pages 44-53, December.
    • Handle: RePEc:lum:rev3rl:v:10:y:2019:i:4:p:44-53
    DOI: https://doi.org/10.18662/po/93
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    References listed on IDEAS

    as
    1. Bing Zhu & Bart Baesens & Aimée Backiel & Seppe K. L. M. vanden Broucke, 2018. "Benchmarking sampling techniques for imbalance learning in churn prediction," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(1), pages 49-65, January.
    2. Arno de Caigny & Kristof Coussement & Koen W. de Bock, 2018. "A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees," Post-Print hal-01741661, HAL.
    3. De Caigny, Arno & Coussement, Kristof & De Bock, Koen W., 2018. "A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees," European Journal of Operational Research, Elsevier, vol. 269(2), pages 760-772.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Churn; class imbalance; customer; telecommunications;
    All these keywords.

    JEL classification:

    • A23 - General Economics and Teaching - - Economic Education and Teaching of Economics - - - Graduate

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