Development of a Customer Churn Prediction System for Telecommunication Services
Computer Science — 2025, Undergraduate
customer churntelecommunicationmachine learningprediction
This study developed a Customer Churn Prediction System to identify telecommunication subscribers likely to terminate their service. Retaining existing customers is far more cost-effective than acquiring new ones, yet churn is often detected too late. The system analyses usage behaviour, demographics, and service data, and flags customers at high risk of churn. Built with Python Django and SQLite, the system was evaluated using a subscriber dataset. The findings showed reliable risk ranking and clear drivers of churn. The study recommends deployment to support targeted retention campaigns and proactive customer care.
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