Churn Prediction in Telecommunications Using Geospatial and Machine Learning Techniques

Authors: Kirti Vasdev

DOI: https://doi.org/10.5281/zenodo.14607920

Short DOI: https://doi.org/g8xxst

Country: USA

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Abstract: Churn prediction is a critical focus area in the telecommunications industry due to its direct impact on customer retention and revenue. Leveraging geospatial and machine learning (ML) techniques, businesses can better understand customer behavior, identify at-risk customers, and implement targeted retention strategies. This paper explores theoretical underpinnings, case studies, and practical applications, emphasizing the integration of geospatial data with advanced ML models. The research also discusses challenges, datasets, and potential future developments in this domain

Keywords: Churn prediction, Telecommunications, Customer retention, Revenue impact, Geospatial data, Machine learning, Customer behavior, At-risk customers, Retention strategies, Theoretical underpinnings, Case studies, Practical applications, Advanced ML models, Challenges, Datasets, Future developments

Paper Id: 231985

Published On: 2025-01-06

Published In: Volume 13, Issue 1, January-February 2025

Cite This: Churn Prediction in Telecommunications Using Geospatial and Machine Learning Techniques - Kirti Vasdev - IJIRMPS Volume 13, Issue 1, January-February 2025. DOI 10.5281/zenodo.14607920

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