Interactive AI Price Optimization & Demand Elasticity Engine
Maximizing retail profit margins and revenue projections using custom demand elasticity models.
The Friction
Retailers with large product catalogs struggle to optimize margins dynamically. Standard rules-based pricing tools are rigid, fail to model demand elasticity, and do not let managers simulate revenue impacts or test scenarios before pushing price changes to production.
The Neural Architecture
We built an interactive, web-based AI Price Optimization Simulator. Powered by category-specific demand elasticity modeling, the system dynamically calculates optimal price points based on baseline volumes, historical references, and sensitivity controls. It visualizes current-vs-recommended price bars, projected annual revenue lines, and price-versus-demand scatter charts using Chart.js, enabling pricing managers to preview, adjust, and bulk-apply recommendations with confidence.
Tech Stack Deployed
Impact Report
- Projected a 12.4% average profit margin increase across 60+ synthetic product listings.
- Designed interactive control parameters for time windows and sensitivity to test different pricing strategies.
- Prevented brand-damaging pricing adjustments through mathematically-constrained elasticity boundaries.
- Included one-click bulk apply recommendations, full reset, and CSV report export functionalities.