# Markdown cadence and full-price sell-through: benchmarking the promotional calendar
A buyer at a mid-size US apparel chain checks her dashboard four weeks after a new denim line hits the floor. She has sold 38% of the units. The house rule says anything below 40% at the four-week mark gets flagged for an early markdown. She has to decide, right now, whether to wait or cut the price. This is the daily reality behind one of retail's most important financial disciplines: sell-through management.
Sell-through rate (STR) is the percentage of received inventory units sold in a given period.
Formula:
Sell-through rate = (Units sold / Units received) x 100Worked example: a buyer receives 1,000 units of a jacket style. After 4 weeks, 320 have sold.
STR = (320 / 1,000) x 100 = 32%That single number drives markdown timing, reorder decisions and vendor scorecards. It is one of the most watched metrics in merchandise planning, the function that matches inventory buys to expected demand.
US apparel buyers commonly use a rule of thumb: if a style is not tracking toward roughly 80% sell-through at full price
The logic: apparel has a short shelf life driven by fashion risk and seasonality. Unsold units at season end become clearance inventory, sold at 40 to 70% off, or worse, pushed to off-price channels like TJ Maxx or liquidators. Every week a style sits unsold, its recovery value drops. The benchmark exists to force a decision before the cushion for full-price recovery disappears.
Retailers typically set interim checkpoints against a full-price sell-through target, not just a season-end number. A common cadence for a 12 to 16 week selling window:
These interim benchmarks are directional planning tools used across US specialty and department store buying offices; exact figures differ by retailer and are treated as internal targets rather than published standards.
A blouse style: 1,200 units received, planned 12-week full-price window.
| Week | Units sold (cumulative) | STR | Target STR | Status |
|---|---|---|---|---|
| 4 | 300 | 25% | 25-30% | On track |
| 8 | 540 | 45% | 50-55% | Slightly behind |
| 12 | 780 | 65% | 70-75% | Behind, markdown likely |
At week 12, the gap to the 70% floor (roughly 840 units) is 60 units short. That gap, combined with the trend line from week 4 to week 8, is what triggers the markdown conversation, not any single week in isolation. Buyers read the slope, not just the snapshot.
A style at 32% in week 4 sounds weak against a 40% target. But if week 1 to 4 velocity is accelerating (say, driven by a marketing push landing late), the buyer may hold. Conversely, a style at 38% that decelerated each week is a stronger markdown signal than the raw number suggests.
This is why experienced buyers track weekly unit velocity (units sold per week) alongside cumulative STR:
Week 4 velocity = units sold weeks 1-4 / 4Flat or declining velocity into week 4 is a worse signal than a strong week 1 that tapers, because tapering into a markdown decision point usually continues.
Delaying a markdown is not free. Consider the same 1,200-unit blouse, cost $10/unit, original retail $30/unit (a 66.7% initial markup, IMU, the gap between cost and original retail price).
If the buyer waits from week 8 (540 sold at full price) to week 12 (780 sold at full price) and then marks the remaining 420 units down 30%:
Had the buyer marked down earlier at week 8 (540 sold full price, 660 units marked 30% off starting week 9):
In this simplified illustration, waiting produced a better margin outcome because sell-through kept improving without a discount. This is the actual tension buyers manage: markdowns protect against unsold inventory risk but sacrifice margin the moment they are applied. There is no universal answer; the benchmark exists to standardize the decision point, not replace judgment.
European fashion retail, particularly in markets like Germany, France and the UK, often runs on structured seasonal sale periods rather than continuous promotional cadences. Many countries historically regulated when sales (soldes in France, Schlussverkauf in parts of German-speaking Europe) could occur, though EU liberalization has loosened fixed windows in most member states over the past two decades. Retailers like Zara (Inditex, Spain) and H&M (Sweden) still concentrate markdown activity around January and July seasonal sale periods more heavily than US retailers, who markdown continuously throughout the year. Full-price sell-through targets in European fashion retail tend to be benchmarked against these fixed sale windows rather than a rolling 12-week clock, an important distinction when comparing sell-through data across the Atlantic. These are general market patterns, not codified figures, and vary by country and retailer.
Knowledge check
1. What does the sell-through rate (STR) formula fundamentally measure?
2. Why does apparel merchandising rely on a full-price sell-through benchmark (like 80%) rather than just waiting until the end of the season to react?
3. A buyer's denim line is at 38% sell-through at the four-week checkpoint, just under the 40% house rule threshold. What does this scenario best illustrate about sell-through benchmarks?
4. Select ALL correct answers about what happens to unsold apparel units as a season progresses without a markdown decision.
Select all the correct answers.
5. Select ALL correct answers about factors that explain why promotional/markdown cadence differs across retail formats.
Select all the correct answers.
Public, retailer-specific sell-through figures are rarely disclosed outside earnings calls in general margin terms. For grounding in actual retail financial disclosure practices, the NRF (National Retail Federation) research hub publishes US retail performance data, and the U.S. Census Bureau's Monthly Retail Trade Survey provides verified US retail sales figures useful for context on seasonal apparel demand swings.
🎬 [VIDEO: "How Fashion Retailers Decide When to Markdown Inventory" - youtube.com - search for retail merchandising channels covering markdown strategy and open-to-buy planning for a visual walkthrough of the buyer's decision process]