Retail Markdown Strategy: When to Mark Down, and How Deep

A retail markdown strategy sets, before the season starts, the rules for when a slow item gets a permanent price cut and how big that cut is. It rests on three numbers: sell-through against plan, weeks of supply against the weeks left to sell, and the margin each option leaves you after the stock is gone.

This article walks through those rules with a worked example, then shows the weekly reports that let a buyer apply them in minutes. Lightray Solutions builds those reports in Power BI; Edward Pinela, MBA, does the work. It starts with a free 30-minute strategy call, and the build is quoted in writing after it.

“Amazing! Lightray Solutions built us a Power BI dashboard based on my busy restaurant’s quickbooks data that allows me to see my entire business on a daily basis which has been a game-changer! Excellent communication and service!”

— Quinn R., Google review

What counts as a markdown, and how is it different from a promotion?

A markdown is a permanent price reduction on stock you want to clear: the price does not go back up. A promotion is temporary and meant to lift traffic or basket size, after which the item returns to full price. Mixing the two in one report hides the real cost of clearing inventory.

Keep them apart in your point-of-sale data from the start. Markdown dollars, the difference between the original price and the selling price multiplied by the units sold at the lower price, belong to the buy that went wrong. Promotional discounts belong to the marketing plan. Only the first tells a buyer what to change next season.

When should you mark an item down?

When two signals agree: sell-through is behind plan, and weeks of supply exceed the weeks left to sell. Sell-through is units sold divided by units received. Weeks of supply is units on hand divided by the average units sold per week over the last two to four weeks.

One signal alone misleads. A style can trail plan because it arrived late, then catch up at full price. Another can be on plan but slowing sharply, which weeks of supply catches first. Most retailers write their triggers as simple checkpoints:

• Mid-season check. Sell-through below plan by an agreed gap, for example 15 points, and weeks of supply above weeks remaining: first markdown.
• Late-season check. The same test two to four weeks before the exit date: second markdown or move to clearance.
• Age rule. Anything unsold after a set number of weeks on the floor is reviewed, whatever its sell-through.
• Exceptions. Core basics that reorder all year sit outside the seasonal rules and are managed on reorder points instead.

How deep should the first markdown be?

Deep enough to clear the stock by the exit date, and no deeper. The right depth depends on how far behind the item is, how many weeks remain, and how strongly its sales respond to price, which you estimate from how similar items responded to past markdowns. A small gap caught early needs a light cut; a wide gap found late needs a heavy one.

The table works one illustrative case. A style was bought at 1,000 units, cost $20 and priced at $50 for a 12-week season. After six weeks it has sold 300 units, 30% sell-through against a 50% plan, and it is selling about 40 a week, so its 700 units on hand are 17.5 weeks of supply with 6 weeks left. Whatever remains at the end goes to an off-price buyer at $12. The weekly sales at each price are assumptions, of the kind you would estimate from your own markdown history.

In this example a 30% markdown in week 7 leaves the most margin. Holding at full price leaves too much stock for the $12 exit, holding through week 10 and cutting 50% only for the last two weeks wastes most of the selling time, and an immediate 50% cut sells out but gives away margin on units that would have sold at $35.

Which reports support markdown decisions?

Three pages cover the weekly decision, and all three refresh from your sales system before the buyer's Monday review. They turn the checkpoint rules into a short list instead of a spreadsheet hunt, built the same way as any other Power BI dashboard development project: one data model, a few focused pages.

Power BI's what-if parameters let a buyer move a discount slider and see projected units, revenue and margin change on the same page; Microsoft's own example is a discount percentage from 0 to 50% in 5% steps. The response rate behind the projection comes from your past markdowns, stated on the page so nobody mistakes an estimate for a forecast.

• Markdown candidates. Items that fail both triggers this week, ranked by the stock value at risk, with sell-through, weeks of supply and weeks remaining beside each one.
• Sell-through against plan. A curve per style or category showing actual against planned sell-through by week, so a slow start is visible before it becomes a clearance problem.
• Markdown cost and margin. Markdown dollars by category, buyer and vendor, and the gross margin each style finally made after every price change, which feeds next season's buy.

What data does markdown reporting need?

Item-level sales by week and store or channel, units received, units on hand, unit cost, and a price history that records each markdown with its date. Most point-of-sale and retail ERP systems hold all of it; price history is the piece most often missing or overwritten.

Add a planned sell-through per style or category and the season's start and exit dates, which usually live in a buyer's spreadsheet. For the inventory measures behind reordering and dead stock, see retail inventory analytics consulting; for sales, margin and channel reporting across the business, see retail analytics consulting.

What does markdown reporting cost, and how does it start?

A markdown report set is a fixed-price Power BI build, quoted after a free strategy call and a short look at your data. Price history, the number of sales systems and how plans are stored decide the size. Later changes, such as a new category or season calendar, can run on Power BI Flex Support, from $2,500 for 20 hours at $100–$125/hr.

The Power BI guarantee applies to the build: if you don't like working with us within the first 4 hours, you get your money back. It covers the working relationship, not sell-through. Edward has 20+ years and 200+ projects behind him, and Lightray's Google rating is 4.9.

Further reading: Microsoft Learn — what-if parameters in Power BI Desktop.