---
title: "SegmentX: Behavioral Intelligence"
emoji: 🛍️
colorFrom: blue
colorTo: indigo
sdk: docker
pinned: false
license: mit
---

# 🛍️ SegmentX: E-Commerce Behavioral Intelligence Portal

SegmentX is a professional behavioral intelligence platform. It transforms e-commerce transactions into actionable segments using RFM and K-Means++. Features include revenue forecasting, Pareto analysis, churn probability, and product affinity mapping to maximize customer retention and mission-critical marketing ROI.

---

## 🚀 Key Features

- **Behavioral Segmentation**: Automated RFM analysis and K-Means++ clustering for precision customer categorization.
- **Advanced Forecasting**: Monthly revenue trend analysis to identify seasonality and long-term growth patterns.
- **Predictive Analytics**: Individual-level Churn Probability (%) and Customer Lifetime Value (CLV) projections.
- **Market Basket Insights**: Segment-specific product affinity analysis highlighting top-selling items per cluster.
- **Strategic Visualization**: Heatmaps, 2D PCA projections, and Pareto-based revenue contribution charts.
- **Campaign Ready**: Interactive direct-to-CSV segment export for immediate use in email marketing tools.

---

## 📁 Project Structure

```
customer_segmentation/
├── data/
│   ├── raw/                # Cleaned transactions (UK-only)
│   └── processed/          # Aggregated RFM features and scaled data
├── docs/                   # Project documentation and instructions
├── models/                 # Saved K-Means cluster model
├── outputs/                # Visualization plots, segment mapping, and product affinity
├── pipeline/               # Modular Python scripts (Cleaning, RFM, Training)
├── app.py                  # Streamlit dashboard
├── README.md               # User guide and setup instructions
├── Procfile                # Deployment configuration
└── requirements.txt        # Required Python libraries
```

---

## 🛠️ Installation & Usage

1. **Install Dependencies**:
   ```bash
   pip install -r requirements.txt
   ```
2. **Launch the Dashboard**:
   ```bash
   streamlit run app.py
   ```

---

## 🚀 Deployment

This project is configured for one-click deployment to **Heroku**, **Streamlit Cloud**, or **Docker**.
- **Procfile**: Pre-configured for web dyno execution.
- **runtime.txt**: Specifies Python 3.10 usage.
- **.gitignore**: Optimized to handle large dataset storage.

---

## 📄 License

This project is licensed under the **MIT License** - see the [LICENSE](LICENSE) file for details.