A comprehensive analysis of customer churn in an Iranian Telecommunication company, using data preprocessing, model construction, and analysis to mitigate churn rate.
Customer retention is a critical factor in business success, with understanding and predicting customer behavior being essential for maintaining a competitive edge.
This project focuses on developing a customer churn prediction model for an Iranian Telecommunication company to identify customers likely to discontinue services.
The model generates binary predictions indicating whether a customer will churn, enabling proactive retention strategies. Our methodology involves three key phases:
comprehensive data preprocessing to ensure data quality, construction of three predictive models for comparative analysis, and in-depth analysis of results to develop targeted churn mitigation strategies.
This systematic approach provides valuable insights for reducing customer attrition and maintaining long-term business sustainability.
