Практические методы прогнозирования сохранения клиентской базы (перевод на русский язык)

Cherkashin, Aleksandr and Sakhadzhi, Vladislav and Guliev, Ruslan and Bolshunova, Elena (2024): Практические методы прогнозирования сохранения клиентской базы (перевод на русский язык).

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. This is a Russian translation of «Practical Methods for Predicting Customer Retention» paper published on MPRA (https://mpra.ub.uni-muenchen.de/id/eprint/122400) 15.10.2024.

• Item Type: MPRA Paper
• Commentary on: Cherkashin, Alexander and Sakhadzhi, Vladislav and Guliev, Ruslan and Bolshunova, Elena (2024): Practical Methods for Predicting Customer Retention.
• English Title: Practical Methods for Predicting Customer Retention
• Language: Russian
• Keywords: абонентская база; удержание абонентов; отток абонентов; степенная функция; телекоммуникации; LTV
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; D - Microeconomics > D1 - Household Behavior and Family Economics > D12 - Consumer Economics: Empirical Analysis; L - Industrial Organization > L9 - Industry Studies: Transportation and Utilities > L96 - Telecommunications; M - Business Administration and Business Economics ; Marketing ; Accounting ; Personnel Economics > M3 - Marketing and Advertising > M31 - Marketing

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