Returns are a markdown optimization problem

Every retailer knows its return rate. Very few can tell you what the returned units were eventually sold for, or who decided.

That second question is the expensive one. The first is a logistics metric. The second is a markdown optimization problem, and in most mid-market retailers it is being answered several hundred times a week by warehouse staff working from habit rather than from policy.

The number nobody owns

The scale is not in dispute. The National Retail Federation and Happy Returns put total US returns at roughly $850 billion in 2025, or 15.8% of annual sales, rising to 19.3% of online sales. For a specialty retailer doing €80M with a meaningful ecommerce share, that is somewhere between €12M and €15M of merchandise coming back through the door each year.

What happens to it is less well documented, which is what makes new research from ReBound Returns and Advanced Supply Chain worth reading. Their Circularity Index surveyed 150 senior leaders at mid-to-large UK and European retailers. Two findings stand out. On average, 12% of returned items generate no value at all. And only 9% of retailers resell more than half of their returned products at full price.

Read that second number slowly. In nine retailers out of ten, the majority of returned stock is sold at something other than the price it was originally listed at. That is a markdown. It is a markdown taken on a large, recurring, entirely predictable volume of inventory. And in most organisations it sits outside the markdown process entirely.

The same study found that 86% of retailers say they have an established circularity approach to returns, but only 27% treat it as core to how returns are managed. The gap between those two numbers is the gap between having a policy and running one.

Why markdown optimization stops at the warehouse door

Ask a category manager how a clearance price gets set on aged stock and you will get a real answer. There is a cadence, a depth ladder, a margin floor, someone who signs off. Ask how the price gets set on a unit that came back in week three of a season, and the answer usually involves a grading scale and a default discount that has not been revisited in years.

This is not incompetence. It is a structural artefact. Returns arrive through the supply chain function and are processed as a cost to be minimised. Pricing sits in commercial and is measured on margin and price position. The returned unit falls in the seam between them, and the seam is where the money goes.

Three things follow from that split, and all three are costly.

The discount is a constant, not a decision. Grade A gets 15% off, Grade B gets 30%, and those numbers apply equally to a jacket returned in October and the same jacket returned in February. One of those units still has a full season of demand ahead of it. The other does not. Treating them identically means overpaying on one and stranding the other.

The unit is invisible to the pricing engine. If returned stock carries a separate SKU, a suffix, or no SKU at all, it will not appear in competitive price monitoring, it will not be covered by a margin floor, and it will not show up in the category's price index. The retailer is then competing against itself on a channel it is not watching.

Nobody is accountable for the recovery rate. Supply chain is judged on cost per return. Commercial is judged on gross margin. Recovered value per returned unit belongs to neither, so it is not on a dashboard, not in a review, and not improving.

A returned unit is a new SKU with a new demand curve

The useful reframe is simple. A returned item is not damaged inventory. It is a different product, with a different cost basis, a different addressable demand, and a different clock.

Its cost basis is lower than the original in one sense and higher in another. The goods are already paid for, so the relevant question is recovery against a sunk cost rather than margin against landed cost. But the unit has absorbed handling: the InternetRetailing report cites US reverse logistics figures of roughly $6 to $18 per unit to process a return. That is a real charge against whatever you eventually recover, and it is the reason a 90% discount and a write-off are sometimes the same decision financially.

Its demand is different too. A customer shopping open-box or second-quality is a different customer, often price-led, frequently comparing against a different competitive set than the one your primary assortment competes in. Pricing that unit off the full-price competitive benchmark is the wrong reference point, and pricing it off a fixed percentage of your own list price ignores the competitive set it actually sits in.

And its clock runs faster. A returned seasonal item has less residual life than a new one by definition, because it spent part of the season out of the building. Any disposition ladder that does not account for elapsed season is systematically too slow.

The channel is half the price

There is a decision upstream of the discount that usually gets made by whoever is packing the pallet, and it sets the ceiling on everything that follows.

A returned unit can go back to full-price stock, into a second-quality section on your own site, to an outlet store, onto a marketplace, to a liquidator in bulk, or to recycling. Each of those carries its own realistic price band and its own take rate. Own-channel resale recovers the most per unit and costs the most in handling and attention. A liquidator recovers a fraction of retail but clears volume in one transaction with no ongoing cost. Marketplace sits between the two, and brings a competitive dynamic your own site does not have.

Which means the channel is not a downstream consequence of the price. It is an input to it. Choosing "own site, second quality" and then discovering the unit only justifies a liquidation price is how stock ends up sitting in a resale section for months, accruing storage and attention, before going to a liquidator anyway at a worse point in the season.

The fix is to make channel an output of the same rule that sets the price. Condition, weeks remaining, parent sell-through and volume on hand determine the channel; the channel then determines the price band; the competitive data for that channel sets the price inside the band. Run in that order, the sequence is explainable to a category manager and auditable after the fact, which matters when someone asks in March why a line was cleared in November.

It also exposes a decision most retailers never make deliberately. If a category consistently routes to liquidation, the honest reading is not that disposition pricing needs work. It is that the category's return rate, its margin, or its product content needs work, and the returns data is where that shows up first.

What a returns pricing policy actually contains

Most retailers do not need a new system to fix this. They need the returned unit brought inside the pricing process they already run. In practice that means four things.

A rule that reads on elapsed season, not just condition. Grade is an input, not the answer. The disposition price should be a function of condition, weeks of season remaining, current sell-through on the parent SKU, and available stock cover. A Grade A unit returned late in a season that is already clearing should be priced more aggressively than a Grade B unit returned early into a category that is short.

A margin floor that includes handling. If processing costs you €9 a unit, a recovery below that is value-destroying however good the percentage looks. Floors should be set on net recovery, and the rule should be allowed to reach the write-off or bulk-liquidation branch when the floor cannot be met. Deciding not to resell is a legitimate outcome, and it is better made explicitly by a rule than implicitly by a unit sitting in a corner for eleven months.

Visibility in the same competitive frame as everything else. Returned and second-quality stock should appear in price monitoring against the competitive set it actually sells into, not the one the primary assortment competes in. Without that, the resale channel is priced blind.

One number, owned by one person. Net recovered value per returned unit, trended, by category. It is the only metric that makes the trade-off visible, because it goes down when you discount too hard and it also goes down when you hold stock too long. Cost per return does not do that. Neither does gross margin.

None of this is exotic. It is the same rules-based, explainable, auditable machinery that already governs promotional depth and clearance cadence, pointed at a stream of inventory that has been left out of scope.

What this doesn't change

Two honest caveats, because the easy version of this argument oversells it.

First, better returns pricing does not reduce returns. Those are separate problems with separate owners. Fit tools, better product content, and sizing data address the return rate; disposition pricing addresses what the returns are worth once they exist. A retailer with a 35% return rate and excellent disposition pricing still has a 35% return rate, and that is still the larger issue.

Second, the ceiling is real. The Circularity Index found that 82% of retailers believe up to half of their returned stock could generate additional value, and 62% already make regular efforts to recover it. That is a meaningful uplift, not a transformation. If your finance team is modelling this as a margin fix, the number will disappoint. Modelled as recovering several points on 15% of your revenue base, it holds up.

There is also a case for doing less. For retailers in categories with low return rates and low unit values, the handling cost genuinely exceeds the recoverable value on most units, and a simple bulk-liquidation contract beats a sophisticated disposition ladder. The point is to know which situation you are in, rather than to default into one.

Where to start

The diagnostic takes an afternoon. Pull last year's returned units for one category. Find what each one eventually sold for, net of handling. Compare that to what the parent SKU was selling for on the same date.

Most teams who run this find the same two things. A meaningful tail of units that recovered less than they cost to process, which should have gone straight to liquidation. And a set of units discounted by default at a point in the season when the parent SKU was still selling at full price, which is money given away for no reason other than that the rule did not look at the calendar.

Fixing the second one pays for the exercise. Fixing the first one is what makes the policy stick.

If you want to see how disposition rules sit alongside the rest of your pricing logic, our markdown and clearance use case covers the mechanics, and the markdown waves playbook goes deeper on cadence. Happy to look at a category with you if it is easier to argue from your own numbers.