PricePulse is a modular and scalable price optimization engine designed to help businesses make data-driven pricing decisions. It combines price elasticity estimation, demand forecasting, and revenue optimization into a single pipeline, packaged with an interactive dashboard using Streamlit.
- Price elasticity modeling with log-log regression and XGBoost
- Time-series forecasting using Prophet, ARIMA, and ML models
- Revenue/profit maximization via grid search and numerical optimization
- Interactive dashboard for price simulations and scenario analysis
- Modular pipeline for seamless integration and testing
| Category | Tools and Libraries |
|---|---|
| Language | Python 3.10 |
| Data Handling | pandas, numpy |
| Modeling | scikit-learn, xgboost, statsmodels |
| Forecasting | Prophet, pmdarima |
| Optimization | scipy.optimize |
| Dashboard | Streamlit, matplotlib, seaborn, plotly |
| Utilities | json, csv, datetime |
Inventory-aware pricing and dynamic re-optimization Real-time API integration for price updates Promotion uplift modeling (discounts, bundles, ads) Competitor-aware optimization with web-scraped prices Multi-product and basket-level pricing simulation