Retail · Pricing Optimization

From manual spreadsheets to automated AI-driven pricing

Replaced a manual Excel-based pricing workflow with ML-driven price elasticity modeling and discount optimization — boosting margin by 20%.

20%

— Margin improvement

6wk

— From kickoff to production

40%

— Less excess inventory

— THE CHALLENGE

A large fashion e-commerce company manually priced products, focusing discounts only on top-sellers. With thousands of SKUs to manage, this approach led to missed margin opportunities on mid-tier products and mounting inventory for slow-moving items. The pricing team spent most of their time in spreadsheets rather than on strategy.

— OUR APPROACH

We built a two-stage ML pipeline: first clustering SKUs by product attributes and sales behavior, then estimating price elasticity per cluster with a tree-based model. An optimization layer recommends discounts that balance revenue, margin, and inventory clearance — all automated and refreshed daily. The pricing team now reviews recommendations instead of building formulas.

— THE IMPACT

The company improved margin by 20%, reduced excess stock on slow-moving items significantly, and freed the pricing team from manual Excel work. The system now runs autonomously with human-in-the-loop review for high-value SKUs.

NEXT STEP

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