Shopee Thailand Intelligence System 🛍️🚀

An end-to-end data science project for analyzing customer journeys, predicting churn, and optimizing marketing campaigns for Shopee Thailand.

🌟 Key Features

• Exploratory Data Analysis: Visualizing sales trends and product performance.
• Conversion Funnel: Tracking customer behavior from discovery to purchase.
• Churn Prediction (XGBoost): 99%+ accuracy in identifying at-risk customers.
• Campaign Optimization Engine: Automated coupon allocation and targeting based on RFM segments.
• Interactive Dashboard: Built with Streamlit for real-time insight discovery.
• Automated Notifications: Simulated cross-channel messaging (Email & App Push).

🛠️ Tech Stack

• Language: Python 3.9+
• Machine Learning: XGBoost, Scikit-Learn
• Data Processing: Pandas, NumPy
• Visualization: Plotly, Streamlit, Seaborn
• Deployment: Docker, Python-Dotenv

🚀 Quick Start

1. Clone the repo:

   git clone [your-repo-link]
   cd "Shoope Training"

2. Install dependencies:

   pip install -r requirements.txt

3. Run the Dashboard:

   streamlit run app.py

🐳 Docker Deployment

docker build -t shopee-intelligence .
docker run -p 8501:8501 shopee-intelligence

📂 Project Structure

• app.py: Main Streamlit Dashboard
• churn_model_shopee.py: Model training and feature engineering
• campaign_engine.py: Targeting and notification logic
• outputs/: Generated visualizations and model files
• archive (1)/: Dataset directory (excluded from Git)

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Developed by [Your Name] | Powered by Shopee Thailand Data