| --- |
| title: "SegmentX: Behavioral Intelligence" |
| emoji: 🛍️ |
| colorFrom: blue |
| colorTo: indigo |
| sdk: docker |
| pinned: false |
| license: mit |
| --- |
| |
| # 🛍️ SegmentX: E-Commerce Behavioral Intelligence Portal |
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| 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. |
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| ## 🚀 Key Features |
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| - **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. |
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| --- |
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| ## 📁 Project Structure |
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|
| ``` |
| 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 |
| ``` |
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| --- |
|
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| ## 🛠️ Installation & Usage |
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| 1. **Install Dependencies**: |
| ```bash |
| pip install -r requirements.txt |
| ``` |
| 2. **Launch the Dashboard**: |
| ```bash |
| streamlit run app.py |
| ``` |
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| --- |
|
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| ## 🚀 Deployment |
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| 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. |
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| --- |
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| ## 📄 License |
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| This project is licensed under the **MIT License** - see the [LICENSE](LICENSE) file for details. |
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