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Practical Methods for Predicting Customer Retention

Author

Listed:
  • Cherkashin, Alexander
  • Sakhadzhi, Vladislav
  • Guliev, Ruslan
  • Bolshunova, Elena

Abstract

This study examines methods for analyzing and forecasting the retention of active subscribers in the telecommunications industry using various criteria for subscriber activity. The results demonstrate that the retention dynamics of an active subscriber base can be effectively modeled using a decreasing power function. This allows for medium-term forecasting based on initial subscriber activity data. However, it is important to note the potential limitations in the effectiveness of the proposed approach for long-term forecasting, associated with changes in subscriber churn dynamics over time.

Suggested Citation

  • Cherkashin, Alexander & Sakhadzhi, Vladislav & Guliev, Ruslan & Bolshunova, Elena, 2024. "Practical Methods for Predicting Customer Retention," MPRA Paper 122400, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:122400
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    File URL: https://mpra.ub.uni-muenchen.de/123946/1/MPRA_paper_123946.pdf
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

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    Keywords

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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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