🛒 RetailPulse: Online Retail Analytics Dashboard

👨‍💻 Authors : Dhruv Garg, Farhan Bin Faisal, Gilbert Akuja, Lixuan Lin

🎯 Motivation and Purpose

Retail operations managers face challenges in managing inventory, tracking sales trends, and identifying market expansion opportunities. Making informed decisions swiftly is crucial to staying competitive. RetailPulse was created to bridge this gap by providing an interactive, data-driven dashboard 📊 that enables retailers to gain real-time insights into their business performance. By leveraging historical transactional data, the dashboard uncovers key patterns in revenue trends 💰, customer retention 👥, and product performance 🏆, empowering managers to make strategic, evidence-based decisions that drive business growth.

📂 Data Attribution

This project uses data from the Online Retail Dataset available on UC Irvine Machine Learning Repository.

🚀 Features & Demo

✔ Monitor Sales Trends 📈 – Track sales performance over time with interactive line charts.
✔ Analyze Customer Retention 🔄 – Identify repeat customers and assess retention trends.
✔ Explore Market Expansion Opportunities 🌍 – Use interactive maps to visualize sales distribution across different regions.
✔ Evaluate Product Performance 📦 – Gain insights into top-performing products through bar charts and word clouds.

The dashboard provides an intuitive interface for exploring retail insights across multiple dimensions.

🛠 Running the App Locally

1️⃣ Clone the repository

git clone https://github.com/UBC-MDS/DSCI-532_2025_15_RetailPulse.git

2️⃣ Navigate to the project directory

cd DSCI-532_2025_15_RetailPulse

3️⃣ Create a conda environment

conda env create -f environment.yaml

4️⃣ Activate the environment

conda activate retailpulse

5️⃣ Run the application

python src/app.py

6️⃣ View the dashboard

After running the app, open your browser and navigate to: http://127.0.0.1:8050/

🔹 You should now see the RetailPulse Dashboard live!

7️⃣ Run the tests using pytest

pytest tests/

💡 Support

For any issues regarding running the dashboard or feature requests, please contact the team using GitHub Issues 🛠️

🤝 Contributing

The team welcome meaningful contributions to the project. Please find more details on how you can contribute in the contribution guidelines ✨

📜 License

The RetailPulse software code contained in this project is licensed under the MIT License. See the LICENSE file for more details.

The project report is licensed under the Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License. See the license file for details. If reusing any part of this code or report, please provide proper attribution by linking to this repository.

📚 References

• Dataset Source 🔗
• Documentation: Dash 📊, Altair📈, Pandas 🐼