This project is an AI-powered customer churn prediction system that predicts whether a customer is likely to leave a company or continue using its services. The system uses machine learning algorithms and customer behavior analysis to improve customer retention strategies.
- Customer churn prediction
- Data preprocessing and cleaning
- Machine learning model training
- Accuracy and performance evaluation
- Interactive web interface
- Real-time prediction system
- Data visualization and analytics
- Python
- Pandas
- NumPy
- Scikit-learn
- Matplotlib
- Flask / Gradio
- Logistic Regression
- Random Forest
- Decision Tree
- XGBoost
Customer churn dataset containing:
- Customer demographics
- Subscription details
- Usage behavior
- Service history
- Payment information
- Telecom industry
- Banking systems
- E-commerce platforms
- Subscription-based services
- Customer retention analysis
- Deep learning integration
- Cloud deployment
- Real-time analytics dashboard
- Explainable AI predictions
- Mobile application support
pip install -r requirements.txt
Run the Project
python app.py
Output
The system predicts:
Churn Customer
Non-Churn Customer
Prediction Confidence Score
Folder Structure
customer-churn-prediction/
│
├── app.py
├── model.py
├── train.py
├── requirements.txt
├── README.md
├── dataset.csv
├── models/
├── static/
├── templates/
└── screenshots/