💜 ChurnCure – Customer Churn Prediction Web App

Predict whether a customer will churn and get actionable retention insights with ChurnCure!

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🚀 Features

• Predict Churn: Instantly see if a customer is likely to leave.

• Churn Probability: Know the risk as a percentage.

• Suggested Discount: Retain high-risk customers with recommended discounts.

• Color-coded Results:

  • 🔴 Churn → Red
  • 🟢 No Churn → Green

• Interactive Frontend: Easy-to-use web interface.

• Supports Multiple Services: Phone, Internet, Streaming TV/Movies, and more.

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🎨 Demo

Form Image:

Result Image:

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🛠 Built With

• Backend: Python, Flask
• Machine Learning: Scikit-learn, Pandas, NumPy, Joblib
• Frontend: HTML, CSS, JavaScript
• Deployment Ready: Compatible with platforms like Render

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⚡ How to Run Locally

1. Clone the repo:

git clone https://github.com/JaweriaAsif745/churn-prediction-web.git

2. Navigate to backend and install dependencies:

cd churn-prediction-web/backend
pip install -r requirements.txt

3. Run the Flask app:

python app.py

4. Open in browser:

http://127.0.0.1:5000

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📝 Notes

• Project not yet deployed online.
• Ensure churn_model.pkl exists in the models folder.
• Currently uses local Flask server; environment variables can be added for API keys or secret configs.

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📂 Project Structure

backend/  ─ Flask app 
frontend/ ─ HTML, CSS, JS
models/   ─ Trained ML model
reports/  ─ Model evaluation & charts
requirements.txt

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🌟 Future Features

• Online deployment with cloud service (Render/Heroku).
• User authentication to manage multiple predictions.
• Export prediction results to CSV or PDF.
• Integrate email notifications for high-risk churn customers.

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📞 Contact

• Developer: Jaweria Asif
• GitHub: JaweriaAsif745

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