An Assessment of Customer Churn Prediction Models in Nigerian Telecommunications: A Study of Mobile Service Providers in Kaduna State
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Background of the Study
Customer churn, the loss of customers to competitors, is a significant challenge in the telecommunications industry, particularly in Nigeria, where there is intense competition among mobile service providers. Churn prediction models use statistical methods and machine learning techniques to analyze customer data and predict which customers are likely to leave (Olaniyan & Abdullahi, 2024). These models allow companies to implement retention strategies, such as personalized offers or enhanced customer service, to reduce churn and increase profitability.
In Kaduna State, mobile service providers are under increasing pressure to retain customers as the market becomes saturated with competing telecom brands. This study aims to assess the effectiveness of churn prediction models used by mobile service providers in Kaduna State, examining how these models help companies anticipate customer churn and develop strategies to prevent it.
Statement of the Problem
Despite the widespread use of churn prediction models, many telecom companies in Kaduna State struggle to accurately identify at-risk customers due to issues such as incomplete customer data, poorly designed prediction algorithms, and a lack of integration between different data sources (Sani & Nuhu, 2025). As a result, retention strategies may not be as effective as they could be, leading to higher churn rates and decreased revenue. This study seeks to evaluate the challenges and effectiveness of churn prediction models in the context of Nigerian telecommunications.
Objectives of the Study
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To evaluate the effectiveness of customer churn prediction models used by mobile service providers in Kaduna State.
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To assess the factors that affect the accuracy and reliability of churn prediction models in the telecommunications industry.
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To propose strategies for improving churn prediction models and retention strategies in mobile telecom companies in Kaduna State.
Research Questions
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How effective are the customer churn prediction models used by mobile service providers in Kaduna State?
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What factors affect the accuracy and reliability of churn prediction models in the telecommunications sector?
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What strategies can be implemented to improve churn prediction models and reduce customer churn?
Research Hypotheses
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The churn prediction models used by mobile service providers in Kaduna State have no significant effect on reducing customer churn.
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Factors such as incomplete data and inadequate algorithms do not significantly affect the accuracy of churn prediction models.
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Strategies for improving churn prediction models have no significant impact on customer retention.
Scope and Limitations of the Study
This study focuses on mobile service providers in Kaduna State that use churn prediction models. Limitations include the availability of accurate data, possible biases in data collection, and varying levels of technological adoption among providers.
Definitions of Terms
Churn Prediction Models: Models that use customer data to predict the likelihood of customer attrition or discontinuation of service.
Customer Churn: The loss of customers or subscribers to competitors or due to disinterest.
Telecommunications Industry: The sector that provides telephone, internet, and data services through various communication technologies.
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