Price Elasticity
A measure of how sensitive customer demand is to price changes. Elastic products see significant volume changes with small price adjustments; inelastic products maintain demand regardless of price. AI ecommerce agents use price elasticity models to optimize pricing: reducing prices on elastic products to capture volume and increasing prices on inelastic products to capture margin—maximizing total contribution across the catalog.
Written by Max Zeshut
Founder at Agentmelt · Last updated Sep 9, 2026
Example
An AI pricing agent discovers that a commodity USB cable has high elasticity (a $1 price drop increases weekly sales by 40%) while a proprietary phone case has low elasticity (a $3 price increase barely changes volume). It lowers the cable price to drive traffic and raises the case price to capture margin.
Frequently asked questions
- How does AI estimate price elasticity?
- By analyzing historical sales data across price points, running controlled price experiments (A/B testing different prices), and factoring in competitor pricing. Machine learning models identify elasticity at the SKU level, accounting for seasonality, inventory levels, and competitive intensity—something manual analysis cannot do across thousands of products.