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September 5, 2025Frontiers in Artificial IntelligenceOpen Access

A predictive analytics approach to improve telecom's customer retention

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Authors

AOAsem OmariOAOmaia Al-OmariTATariq Al-Omari

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Overview

Predictive model reduces customer churn in telecom companies, suggesting effective data strategies.

Key Points

  • Developing a predictive model significantly enhances customer retention strategies for telecom companies.
  • Our analysis indicates that the Support Vector Machine yielded the best performance among several predictive models.
  • The study employs various advanced data analysis techniques, including machine learning algorithms for churn prediction.
  • Integrating effective data pre-processing and feature selection improves the interpretability of the models.

Cite This Study

Omari et al. (2025) studied this question.

synapsesocial.com/papers/68c23922b210217d6477ac5chttps://doi.org/10.3389/frai.2025.1600357
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Machine Learning for Telecom Customer Retention and Growth2025
  2. 2Identifying customer churn in Telecom sector: A Machine Learning Approach2024 · 1 citations
  3. 3Enhanced Customer Retention: Deep Learning- Based Churn Prediction for Telecom Industry2025
  4. 4Comparative Analysis of Machine Learning Models for Telecom Customer Churn Prediction2025 · 1 citations
  5. 5Literature Review on Customer Churn Prediction in Telecom Industry2025