Case study

Demand-sensitive pricing across 12 categories.

We augmented an intent-based pricing process with a model that adjusts to current and potential demand alongside category elasticity — recovering margin that flat pricing was leaving on the table.

Industry
Metal trading
Discipline
Build
Engagement
Pricing · 12 categories
Outcomes

Numbers we agreed to move.

Margin leakage
−30%
On promotional SKUs in launch categories, vs. the prior 12-month baseline.
Decision latency
−4 days
Time from price recommendation to deployed list price across the 12 categories.

The challenge

Prices were set by category captains using a mix of cost-plus and historical intent. The result was systematic under-pricing on demand-elastic SKUs and over-pricing on inelastic ones — a margin-shaped hole nobody could see from any single dashboard.

What we did

Two-week discovery to map the pricing workflow end-to-end. We scoped the metric (margin leakage on promotional SKUs) and built a category-elasticity model that produced recommendations inside the existing pricing tool, not alongside it.

Where it landed

The model now feeds recommendations into the captain's daily routine. Captains override roughly 18% of the recommendations — which is healthy. The system is instrumented so every override is a labeled training signal.

"ECALabs didn't sell us a model. They built the workflow our team already wanted, and the forecast made it possible."
— Non-ferrous Metal Sector Company, Türkiye