How AI Can Save Your Markdown Budget
Most retailers leave 15-30% on the table with poorly timed markdowns. Data-driven optimization changes that.
Ersel Gökmen
March 22, 2026
Markdowns are one of the largest controllable costs in retail. A typical fashion retailer marks down 30-40% of inventory, often too early (leaving margin on the table) or too late (requiring deeper cuts to clear).
The timing problem is hard because it involves multiple variables: current sell-through, remaining weeks in season, competitor pricing, storage costs, and brand perception.
The Traditional Approach
Most merchants use a rule of thumb: if sell-through is below X% at week Y, mark down by Z%. It's simple and consistent, but it ignores the nuances that separate good markdown decisions from great ones.
What Optimization Looks Like
AI-driven markdown optimization considers each SKU individually: its velocity, its margin, its seasonality pattern, what competitors are doing, and how much runway remains. It can schedule staggered markdowns — 15% in week 1, then 25% in week 3 if needed — rather than a single blanket cut.
In our testing, this approach recovers 8-15% of markdown costs compared to rules-based approaches. For a $50M retailer, that's $400K-$750K annually.