Markdown optimization: When to discount using data
When to discount fashion inventory using data: sell-through velocity tracking, markdown ROI calculations, and progressive discount schedules that protect margin.
You’re staring at 400 units of a jacket that hasn’t moved in six weeks. The season is half over. Do you mark it down 20% now and risk leaving money on the table? Wait another month and risk needing 50% off to clear it? Or hold firm and carry dead inventory into next year?
This decision repeats constantly in fashion retail. Mark down too early, and you sacrifice margin on items that would have sold at full price. Mark down too late, and you need deeper discounts to move stale inventory. Both mistakes cost real money—thousands per season for small brands, millions for larger ones.
Most fashion retailers make markdown decisions based on gut feeling and panic. “It’s not selling, let’s discount it.” That approach ignores the data sitting in your systems—data that can tell you exactly when to discount, how deep to go, and which items to prioritize.
Why markdown timing goes wrong
Fashion retail operates on emotion. A slow-selling style creates anxiety. That anxiety leads to reactive discounting—cutting prices to make the problem feel solved, even when data suggests patience would pay better.
The opposite happens too. Attachment to certain pieces delays necessary markdowns. “This jacket is beautiful, it will sell eventually.” Meanwhile, the season window closes and that jacket needs 60% off instead of the 25% that would have worked two months earlier.
Both patterns stem from the same root: decisions based on feelings rather than numbers. Data-driven markdown optimization replaces emotion with evidence.
What doesn’t fix this problem
× Calendar-based markdowns
Some retailers mark down everything at fixed dates—30% off starting July 1, regardless of how items are selling. This treats all inventory identically. Fast sellers get discounted unnecessarily. Slow sellers might need earlier intervention. Calendar markdowns are simple but sacrifice margin by ignoring actual performance.
× Matching competitor discounts
When competitors go on sale, the instinct is to match. But your inventory situation differs from theirs. They might be clearing overstock while you’re well-positioned. Following competitor timing means making decisions based on their problems, not yours.
× Across-the-board percentages
Marking everything down 20% feels fair but isn’t strategic. Some items need 10% to move. Others need 35%. Uniform discounting over-discounts some products and under-discounts others. Both outcomes hurt margin.
Here’s what actually works: using sell-through data, velocity patterns, and margin calculations to make item-specific markdown decisions at optimal timing.
4 ways to optimize markdowns with data
1. Track sell-through velocity by SKU
What it is: Monitoring how quickly each item sells relative to expectations and triggering markdowns when velocity falls below threshold.
How it works:
Set target sell-through rates by week (e.g., 15% at week 4, 35% at week 8)
Track actual sell-through for each SKU weekly
Flag items falling more than 10 percentage points behind target
Initiate markdown review for flagged items
Best for: Brands with clear seasonal windows who need systematic early warning for underperformers.
Honest pros/cons:
✓ Catches slow sellers before problems compound
✓ Creates consistent decision framework
✗ Requires accurate initial targets
✗ Doesn’t account for external factors (weather, trends)
2. Calculate markdown ROI before discounting
What it is: Modeling the financial impact of different discount levels before choosing one.
How it works:
Estimate unit sales at current price for remaining season
Estimate unit sales at 20%, 30%, and 40% discount levels
Calculate total margin for each scenario
Choose the discount level that maximizes margin, not revenue
Example calculation: 200 units remaining at $100, 60% margin. At full price, you’ll sell 50 units = $3,000 margin. At 25% off, you’ll sell 120 units = $2,700 margin. At 40% off, you’ll sell 180 units = $2,160 margin. The data says hold price—or try a smaller discount first.
Best for: Retailers who want to maximize profit, not just clear inventory.
Honest pros/cons:
✓ Focuses on margin, not just movement
✓ Prevents knee-jerk deep discounting
✗ Requires estimating price elasticity (improves with historical data)
✗ Takes more time per decision
3. Implement progressive markdown schedules
What it is: Planned discount escalation based on time and sell-through, rather than single markdown events.
How it works:
Define markdown stages: 15% at trigger point, 25% two weeks later, 40% two weeks after that
Set sell-through thresholds that advance items to next stage
Allow items meeting velocity targets to skip stages or exit markdown
Track stage effectiveness and adjust schedule based on results
Best for: Brands managing large SKU counts who need scalable markdown processes.
Honest pros/cons:
✓ Avoids jumping to deep discounts immediately
✓ Systematic and scalable
✓ Allows course correction between stages
✗ Requires discipline to follow schedule
✗ Some items might need faster escalation
4. Analyze historical markdown effectiveness
What it is: Using past markdown data to predict which discount levels work for which product types.
How it works:
Compile markdown history: item, discount level, pre-markdown velocity, post-markdown velocity
Calculate lift (velocity increase) by discount level and category
Identify patterns: “Dresses need 30% minimum to see meaningful lift” or “Accessories respond to 15%”
Apply category-specific discount levels based on proven effectiveness
Best for: Established brands with multiple seasons of markdown data to analyze.
Honest pros/cons:
✓ Decisions based on actual results, not assumptions
✓ Category-specific insights improve over time
✗ Requires historical data to be meaningful
✗ Past patterns might not predict unusual circumstances
Which approach should you use?
Choose velocity tracking if:
You need early warning systems for slow sellers
Your team can review weekly sell-through reports
You want systematic triggers rather than reactive decisions
Choose markdown ROI calculation if:
Margin preservation matters more than inventory clearance
You have time for item-level decision modeling
You’re willing to accept some carryover inventory
Choose progressive schedules if:
You manage hundreds or thousands of SKUs
You need scalable processes for a small team
You want to avoid deep discounting but still ensure clearance
Choose historical analysis if:
You have 2+ years of markdown data available
You want category-specific discount guidance
Your product mix is relatively consistent season over season
Most successful brands combine approaches. Velocity tracking identifies candidates. ROI calculation determines optimal discount. Progressive schedules manage execution. Historical analysis improves all three over time.
Setting up your markdown analytics
Start with weekly sell-through reporting by SKU. This single report enables most markdown decisions. Include: units received, units sold, sell-through percentage, weeks in inventory, and target sell-through for current week.
Add margin data to sell-through reports. Knowing that an item has 65% margin versus 45% margin changes markdown math. Higher-margin items can sustain deeper discounts while remaining profitable.
Track markdown results religiously. For every markdown event, record: SKU, discount percentage, sell-through before, sell-through after, and margin impact. This builds the historical data that improves future decisions.
Review markdown performance monthly. Which discounts worked? Which didn’t move the needle? Are certain categories consistently requiring deeper discounts? These patterns inform strategy.
Timing considerations for fashion
Fashion has rhythm. End-of-season clearance windows exist for reasons—customers expect sales at certain times and might wait if they anticipate discounts coming.
Early markdowns can train customers to wait. If your audience learns that everything goes 30% off by week eight, they’ll stop buying in weeks one through seven. Be strategic about discount visibility and timing.
Weather affects markdown timing more than calendar does. A warm October delays coat-buying regardless of your markdown schedule. Monitor weather patterns and adjust expectations accordingly.
Competitive dynamics matter despite earlier warnings against matching blindly. If the entire market goes on sale simultaneously, holding full price might be futile. Use judgment alongside data.
The mindset shift
Successful fashion brands treat markdowns as a strategic tool, not a panic response. They buy conservatively, accepting occasional stockouts rather than chronic overstock requiring deep discounts.
Premium positioning requires markdown discipline. Discounting too frequently or too deeply erodes the perception that justifies higher prices. Brands protecting their margins plan markdown strategy before the season starts, not when anxiety peaks.
The pattern: data informs timing, margin calculations guide depth, and every markdown becomes learning for next season. Reactive discounting feels decisive but costs money. Analytical discounting feels slower but preserves profit.
Frequently asked questions
How early should I start considering markdowns?
Monitor sell-through from week one but don’t panic until week four or five. Some items start slowly then accelerate. If an item reaches week six significantly behind target velocity with no improvement trend, it’s time for intervention. Earlier for highly seasonal items with short selling windows.
What discount level should I start with?
Start smaller than you think—15-20% often moves inventory that just needs a nudge. You can always go deeper. Starting at 40% means you’ll never know if 25% would have worked. Test lower discounts first, escalate based on response.
Should I markdown slow sellers or prioritize clearing oldest inventory?
Both factors matter. An item that’s been stagnant for 12 weeks at any velocity needs attention—aging inventory loses value regardless of original performance. Prioritize items that are both slow-selling AND aging. Items that sold well initially but stalled might just need visibility, not discounts.
How do I avoid training customers to wait for sales?
Limit discount frequency and depth. Reserve deep discounts for true end-of-season clearance rather than mid-season promotions. Consider member-only or flash sales that create urgency without permanent price perception changes. And ensure your full-price assortment offers genuine value that justifies not waiting.
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