Telecom-Customer-Churn-Analysis-Prediction and Telecom-Churn-Analysis

About Telecom-Customer-Churn-Analysis-Prediction

VibolvatanakPOCH/Telecom-Customer-Churn-Analysis-Prediction

Telecom Customer Churn Analysis & Prediction project uses Gradient Boosting for precise predictions, Power BI for churn pattern visualizations, and Streamlit for interactive insights. With robust code and meticulous data preprocessing, stakeholders access accurate predictions to optimize retention and drive profitability.

About Telecom-Churn-Analysis

AliAmini93/Telecom-Churn-Analysis

Developed a churn prediction model using XGBoost, with comprehensive data preprocessing and hyperparameter tuning. Applied SHAP for feature importance analysis, leading to actionable business insights for targeted customer retention.

This project helps telecom companies understand why customers leave by analyzing their usage patterns and demographics. It takes customer data like age, contract type, and service usage, and predicts which customers are likely to churn. This allows customer retention specialists or marketing managers to proactively target at-risk customers with specific offers to keep them.