Retailers are haemorrhaging hundreds of billions annually through returns they can’t see, secondary markets they can’t trust, and liquidation pipelines built on opacity rather than data. The fix already exists. Most are just not using it yet.

By the Numbers

• $850 billion — Projected value of US retail returns in 2025 alone (NRF / Happy Returns, 2025)
• $200 billion — Annual cost to US retailers to process and recover returned goods (McKinsey, 2026)
• 66% — Of the original item price consumed by returns handling costs alone (TheIndustry.fashion, 2025)
• 19.3% — Average return rate for online purchases — nearly 1 in 5 items (NRF, 2025)

A Trillion-Dollar Process Run on Gut Feel and Guesswork

There is a crisis hiding in plain sight across the retail industry. It does not make headlines the way a failed product launch does, or attract the scrutiny of a bad quarter. But it is costing the world’s retailers more money, more reliably, than almost any other operational challenge they face. It is the problem of returns — and more specifically, what happens to them once they arrive back at the warehouse door.

The numbers are staggering. US consumers returned nearly $850 billion worth of merchandise in 2025, according to the National Retail Federation — a figure that has more than doubled in just four years.^[1] And yet, for most retailers, the returns problem is still being managed the same way it was during the pandemic: with blunt instruments, opaque pipelines, and a chronic underestimation of what good data could do.

The result is a haemorrhage of margin that is, for many retailers, entirely preventable. The question is not whether the tools exist to fix it. They do. The question is how much longer the industry can afford to ignore them.

“Retailers must apply the same rigour, investment, and cross-functional coordination to reverse logistics as they do to forward logistics, treating returns not as a back-end process but as a core stage of the product life cycle.”

— McKinsey Logistics & Retail Practice, 2026

McKinsey’s 2026 analysis of the sector found that supply chain leaders are still managing reverse logistics the way they did during COVID-19 — with one-size-fits-all return policies and disposition decisions that cannot keep pace with the constant flow of returns or the need for faster, smarter choices about where each item should go next.^[2]

That failure to apply forward-logistics rigour to the reverse channel is not a minor operational gap. It is, at scale, a structural profit drain. Handling a return costs the average retailer between $20 and $30 per item — consuming, in some categories, up to 66% of the original item’s sale price in transport, labour, and restocking costs alone.^[3] For fashion and electronics, where return rates regularly exceed 30%, the arithmetic is brutal.

And the problem is accelerating. E-commerce return rates are running at 19.3% nationally in the US, and in online fashion the figure climbs to 30–40%.^[4] European retailers face projected return logistics cost growth of over 20% by 2026.^[5] Return fraud — from empty-box scams to counterfeit swaps — now accounts for an estimated $103 billion of annual return value in the US alone.^[6]

The Returns Crisis at a Glance

• $890 billion in US retail returns in 2024 — more than double the total from just four years prior (McKinsey)
• $103 billion in estimated return fraud value in 2024 — including overstated quantities, empty-box returns, and counterfeit swaps (Appriss Retail / Deloitte)
• 60% of retail executives report having to choose between processing returns and fulfilling new orders (Happy Returns, 2024)
• 9.5 billion pounds of landfill waste generated annually by US retail returns, alongside 24 million metric tons of CO₂ emissions

The Liquidation Market: A Black Hole for Recovered Value

The single most damaging link in the reverse logistics chain is not the returns process itself — it is what happens at the end of it. For goods that cannot be restocked as new, retailers have historically defaulted to the same blunt solution: liquidation. Palletise it. Move it. Take whatever you can get.

The problem is that the traditional wholesale liquidation market is almost entirely opaque. Buyers are routinely asked to purchase pallets with no manifest, no grading, and no reliable indication of what is inside — with no recourse when the contents bear no resemblance to the description. Industry analysis consistently finds that a significant proportion of retailers still negotiate directly with a single liquidation partner, accepting whatever price is offered with no visibility into the true market value of their goods, and no competitive tension to drive better recovery.^[7]

The consequences are predictable. Without access to pricing benchmarks or a competitive buyer pool, retailers are structurally unable to understand what their surplus stock is actually worth. They set reserve prices based on historical relationships rather than live market data. They accept the first offer rather than the best one. And they have no mechanism to know the difference.

“Without clear oversight of the process, retailers face challenges in maintaining brand integrity and controlling distribution channels — and without competitive tension, there is simply no incentive for buyers to pay fair market value.”

— Industry analysis, reverse logistics secondary market, 2025

The buyer experience in this market is equally chaotic. The wholesale pallet sector is rife with unmanifested stock — goods graded loosely or not at all, sold at prices that bear no relationship to the actual condition of the inventory inside. When buyers cannot trust what they are purchasing, they discount aggressively to protect themselves. That discount comes directly out of the retailer’s recovery.

The secondary market’s opacity is, in other words, a self-defeating mechanism. Retailers accept low recoveries because they have no data on what better looks like. Buyers pay low prices because they have no certainty about what they are getting. The gap between what goods are genuinely worth and what retailers actually recover remains vast — and largely invisible to both parties.

Stock sitting too long in liquidation warehouses typically results in markdowns of 25–50%, significantly eroding profitability before goods even reach secondary market buyers. In fashion and electronics, where value depreciates rapidly, the cost of delay is compounded by every day that passes without a data-driven disposition decision.^[5]

Why AI Is Not a Luxury — It Is the Only Credible Answer

The core failure of traditional reverse logistics is not logistical — it is informational. The reason retailers make poor disposition decisions is that they do not have the data to make good ones. The reason secondary market buyers pay low prices is that they cannot verify what they are buying. The reason recovery rates remain stubbornly low is that the entire pipeline has been built on opacity, at every stage, by every participant.

Artificial intelligence changes this equation fundamentally — not by automating the physical logistics, but by making the data that has always existed actually usable. McKinsey’s modelling suggests that retailers who apply AI and automation to redesign reverse logistics can convert $200 billion in annual costs into measurable business value.^[2] That is not a speculative projection. It is a description of what data-driven disposition decisions, at scale, actually produce.

“Done right, reverse logistics can shift from a growing cost center to a source of resilience and competitive advantage.”

— McKinsey, From Cost Center to Competitive Advantage, 2026

AI-driven grading and sorting — assessing item condition, category, age, and market demand against real-time pricing data — allows retailers to make item-level disposition decisions rather than the blunt category-level guesswork that characterises most current practice. A returned item that could be restocked should not go to liquidation. A returned item in poor condition should not absorb restocking labour costs. An item with high secondary market demand should reach that market quickly, with accurate information, to maximise competition and therefore price.

The NVIDIA 2025 retail survey found that 69% of retailers report increased annual revenue from AI adoption, while 72% experienced decreased operating costs — a dual benefit that reflects exactly this kind of operational precision applied across the supply chain.^[8] Fraud detection tools that apply machine learning to return behaviour patterns are being used to claw back billions that were previously written off as a cost of doing business.

Three Levers AI Unlocks in the Returns Chain

1. Item-Level Grading at Scale
AI vision systems can assess condition, authenticity, and resale viability in seconds — replacing the slow, inconsistent manual triage that drives poor disposition decisions.

2. Real-Time Market Pricing
Dynamic pricing models trained on live secondary market data ensure retailers receive fair market value — not the floor price of an opaque bilateral negotiation.

3. Full-Chain Transparency
Manifested, graded stock with verified condition data creates buyer confidence — and confident buyers pay more, increasing retailer recovery on every lot.

The Transparency Dividend: What the Market Looks Like When Buyers Can See What They’re Buying

The link between transparency and recovery is not theoretical — it is a market mechanism. When buyers have accurate, verifiable information about what they are purchasing, several things happen simultaneously: competition increases, because more buyers can confidently participate; prices rise, because the risk discount built into blind purchases disappears; and the retailer’s recovery improves — not because the goods have changed, but because the information around them has.

This principle plays out at every level of the secondary market. Manifested electronics pallets with verified grading consistently command materially higher prices than their unmanifested equivalents, even when the underlying stock is identical. A pallet sold with a full itemised manifest, accurate condition grades, and clear category breakdowns gives buyers the confidence to pay closer to true market value. Remove that information, and buyers price for the worst case. The information itself is the value-add.

A well-documented example of what data-driven sorting can achieve: industry operators who have adopted structured grading and manifest-backed listing strategies have reported dramatic improvements in per-unit recovery — in some cases tripling achieved pricing on general merchandise categories, without changing the underlying stock at all. The goods did not improve. The information around them did.^[7]

“Implementing an effective, data-backed resale strategy is essential for items that cannot be restocked on primary shelves. The right approach not only maximises recovery value but also accelerates the movement of goods out of warehouses, minimising holding costs and supporting healthier inventory turnover.”

— Reverse logistics industry analysis, 2025

From a buyer’s perspective, the implications are equally clear. The wholesale pallet market has historically been hostile to professional buyers — a space where information asymmetry systematically favoured sellers who could obscure the quality of their stock, and penalised buyers who lacked the resources or relationships to verify it independently. When buyers know exactly what they are purchasing — down to condition grade, SKU count, and category mix — they can price accurately, source at scale, and build sustainable businesses.

That matters for the sector’s long-term health. A secondary market populated by professional, data-literate buyers is a more efficient, more liquid market. It absorbs returned goods faster, prices them more accurately, and returns more value to the retail supply chain than one built on opacity and mistrust.

What Good Looks Like: The Infrastructure the Circular Economy Actually Needs

The retailers best positioned to extract value from their returned and surplus stock share several characteristics. They have moved beyond treating returns as an afterthought and invested in the data infrastructure needed to make disposition decisions in real or near-real time. They have diversified their secondary market channels — moving away from single-buyer bilateral arrangements toward platforms that create genuine competitive tension around their inventory. And they have recognised that the quality of information they put into the secondary market directly determines the recovery they get out of it.

NRF Vice President of Industry and Consumer Insights Katherine Cullen articulated the shift in framing that underpins this approach: “Returns are no longer the end point of a transaction — they provide an opportunity for retailers to create a positive experience for customers and can translate to brand loyalty.”^[1] The same logic extends to the B2B secondary market: returns are not a cost to be minimised, but an inventory stream to be optimised.

“To stay competitive amid rising return rates and behaviours like bracketing, retailers must modernise their reverse logistics to enhance customer satisfaction, reduce fraud, and safeguard their operations in today’s high-pressure retail landscape.”

— David Sobie, Co-Founder & CEO, Happy Returns (a UPS company)

Modernising reverse logistics is not a small undertaking. It requires investment in grading and sorting infrastructure, integration of real-time market pricing data, and a willingness to rethink the secondary market as a strategic channel rather than a disposal mechanism. But the financial case is unambiguous. The retailers and recommerce operators who are already running data-driven secondary market strategies are recovering materially more per unit than those still operating opaque, undifferentiated liquidation pipelines.

The environmental case is equally compelling. Reverse logistics currently accounts for 750,000 tonnes of CO₂ emissions annually in the UK alone, with transport making up nearly 50% of total emissions in the returns chain.^[5] An estimated 9.5 billion pounds of returned goods end up in US landfills every year.^[9] A more efficient secondary market — one that routes goods to their highest-value use quickly, accurately, and with minimal handling — is not just good business. It is the practical infrastructure of circular commerce at scale.

Routing Surplus Stock to Primary Demand — With Data, Not Guesswork

At STOCS, our mission is to route the world’s surplus stock to primary demand. That mission is inseparable from the argument made in this article. The secondary market cannot function efficiently without data. Retailers cannot maximise recovery without transparency. Buyers cannot build sustainable businesses without verified information about what they are purchasing.

Bulk STOCS — our dedicated B2B wholesale pallet platform at bulk.stocs.com — is built around exactly these principles. Every load listed on the platform comes with a full, itemised manifest. All stock is professionally graded and sorted before listing, with condition clearly displayed. New inventory arrives daily, priced against live market data to ensure both fair recovery for suppliers and fair value for buyers.

This is not a niche improvement to the status quo. It is what the secondary market needs to become if retail’s reverse logistics crisis is going to be resolved — not just managed. The technology exists. The data exists. The market demand exists on both sides. What has been missing is a platform built to harness all three.

The reckoning for reverse logistics is not coming. It is already here. The question is which retailers, and which platforms, will be ready for it.

Start Sourcing Smarter

Bulk STOCS is the B2B wholesale pallet platform built for professional buyers — graded stock, full manifests, new loads arriving daily. Register today at bulk.stocs.com.

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Sources & References

1. National Retail Federation & Happy Returns, 2025 Retail Returns Landscape, October 2025. nrf.com
2. McKinsey Logistics & Retail Practices, From Cost Center to Competitive Advantage: Modernizing Reverse Logistics with AI, February 2026. mckinsey.com
3. Zeta Global, Retail Returns & Reverse Logistics: Challenges and Solutions in 2025, July 2025; TheIndustry.fashion, The Reverse Logistics Crisis, October 2025.
4. NRF, op. cit.; TheIndustry.fashion, The Reverse Logistics Crisis: Fixing Fashion’s Most Costly Supply Chain Weakness, October 2025.
5. TheIndustry.fashion, ibid.
6. Appriss Retail & Deloitte, 2024 Consumer Returns in the Retail Industry Report, 2024. Via MakeMyReceipt, Retail Returns Statistics 2026. makemyreceipt.com
7. Reverse logistics industry analysis and operator case study data, 2024–2025.
8. NVIDIA, 2025 Global Retail Report, cited in ArticleSledge, AI Retail 2026, January 2026.
9. Radial, Reverse Logistics: Containing Costs Without Losing Customers, December 2025. radial.com