US Returns Hit $850 Billion in 2025: Why US Retailers Are Restructuring Reverse Logistics in 2026

Heading into 2026, US retail and e-commerce logistics leaders are navigating the most concentrated reverse logistics restructuring cycle in recent retail history. The most recent annual benchmark — the 2025 Retail Returns Landscape report from the National Retail Federation, published October 2025 — quantifies the problem retailers are now spending 2026 working through: $849.9 billion in US retail returns last year, representing 15.8% of total annual sales and 19.3% of online sales returned.

The data point that matters most for 2026 operational planning isn’t the headline. It’s that 64% of US merchants reported in late 2025 that updating their returns process was a priority for 2026. Combined with the NRF data showing increasing online sales and reducing return rates as the top 2026 retailer priorities, the operational pressure is unambiguous: retailers are simultaneously trying to grow channels that generate the most returns while reducing the rate at which those channels generate them.

This is a 2026-focused analysis of where US retail reverse logistics restructuring stands now, including the role AI-powered routing and dispatching plays as one of the primary cost-reduction levers retailers are deploying in 2026.

The Six Operational Territories

1. The 2025 Returns Reality Setting 2026 Operating Conditions

Aggregate scale: $849.9 billion in returns across US retail in 2025, that’s 15.8% of total annual sales — and 19.3% of online sales — coming back. The 2024 figure was $890 billion. The category isn’t shrinking, the operational cost is rising, and consumer expectations are rising even faster.

Holiday returns for the 2025 holiday season were around 17% of holiday sales. The implication for 2026 P&L planning: returns are a first-order P&L line item — and one that scales directly with the online sales growth retailers are simultaneously prioritizing.

2. The Customer Experience Economics Shaping 2026 Strategy

Customer expectations escalated materially through 2025. 82% of consumers now cite free returns as a major purchase consideration, up from 76% in 2024, per NRF research. 76% prefer return options offering instant refund or exchange. Gen Z (ages 18-30) makes 7.7 online returns per year on average, more than any other generation.

The retention stakes intensify the strategic pressure. 71% of consumers say they are less likely to shop with a retailer again after a poor returns experience, up from 67% in 2024. Four out of five share negative experiences with friends and family, amplifying impact through word-of-mouth. The 2026 implication: retailers operating returns as a back-office function while building front-office CX teams elsewhere are misallocating attention. The returns experience is the front office for a meaningful share of customer interactions.

3. The Retailer Response Patterns Now in Execution

US merchants entered 2026 with concentrated restructuring commitments. 64% of merchants reported in late 2025 that updating their returns process was a priority for the next six months. Drivers retailers cited for charging for returns: 40% operational cost increases, 40% carrier shipping cost increases, 33% economic uncertainty and tariff risk.

For holiday season management, three operational responses dominate: 49% increased focus on third-party logistics partners. 43% planned seasonal staff hiring and 37% extended return windows — counterintuitively, longer windows often reduce fraud and improve customer experience while smoothing operational peaks. The pattern: US retailers are restructuring how returns get processed rather than trying to suppress return volume directly.

4. The Fraud and Behavior Reality Driving 2026 AI Investment

According to NRF as much as 9% of all returns are fraudulent. Top fraud patterns: 71% overstated quantity, 65% empty box or “box of rocks,” 64% counterfeit decoy returns. Now, 85% of retailers are now employing AI to detect or prevent return fraud — one of the highest concentrations of operational AI deployment in retail.

Consumer behavior compounds the legitimate cost. Close to two-thirds of consumers admit to participating in at least one costly returns behavior — wardrobing, bracketing, sending back different items, empty boxes. NRF highlights that 45% believe “bending the truth” is acceptable when making returns. The 2026 implication: fraud detection investment is table stakes given baseline fraud rates and 85% industry adoption. Retailers without AI-based fraud detection are operating against the prevailing industry standard.

5. The Consolidation Network Shift

The third-party consolidation pattern — 49% of US retailers increasing focus on 3PL partners — has a real-world reference point in Happy Returns, a UPS company, which operates a US-wide Return Bar drop-off network consolidating returns across multiple retailers. Shoppers drop off returns without packaging or labels in under 60 seconds; returns are consolidated, sorted in automated facilities, and bulk-shipped back with item-level verification.

Operational benefits include reduced shipping cost through bulk consolidation, item-level verification at drop-off (which helps prevent fraud), and improved customer experience aligned with consumer preferences (82% want free returns, 76% want instant refunds). For retailers planning 2026 returns infrastructure, the strategic question is whether the operating model fits — and how the routing layer between consolidation points and processing facilities affects total economics.

6. AI-Powered Routing and Dispatching as a 2026 Cost-Reduction Lever

This is where 2026’s restructuring crosses from CX redesign into infrastructure investment. AI-powered routing and dispatching affects returns cost across six specific operational mechanisms — and for US logistics leaders evaluating 2026 cost levers, each is worth assessment against current operational maturity.

Reverse pickup routing optimization. When retailers offer pickup-from-customer returns, route consolidation across multiple pickups in proximity reduces miles per pickup and driver hours per route. AI engines optimizing across both forward delivery and reverse pickup produce different cost profiles than systems treating them as separate problems.

Drop-off network routing. For consolidation models, routing between drop-off points (Return Bars, store-based returns, locker networks) and processing facilities affects consolidation efficiency. Capacity-aware routing across the network reduces dwell time and storage cost.

Returns-aware forward routing. Routing systems incorporating return probability into forward delivery decisions can position high-return-risk shipments closer to consolidation infrastructure or pre-position returns capacity.

Multi-modal returns dispatch. US returns flow across courier pickup, drop-off consolidation, locker networks, and store-based returns. Coordinating dispatch across these modes — rather than treating each as separate streams — captures cost efficiencies through shared capacity and modal flexibility.

Capacity-aware returns processing dispatch. Processing facility capacity varies by day, season, and inbound volume. AI dispatch routing returns to facilities with available capacity reduces dwell time, storage cost, and processing latency.

Round-trip optimization. The structurally largest lever: batching returns pickup with forward delivery routes. A driver completing forward delivery in a neighborhood with a returns pickup nearby executes both on the same route, reducing marginal cost of returns pickup substantially. Magnitude varies by operational density, customer base, and route structure — but operations capturing this lever produce different cost profiles than those treating forward and reverse flow as independent.

The honest framing for VPs of Operations: AI-powered routing affects returns cost through specific mechanisms with magnitude varying by operation. The 2026 evaluation question is which mechanisms apply to your operating model.

The 2026 Evaluation Framework For US Retail Logistics Leaders

Six questions for US retail VP Operations and E-Commerce leaders evaluating reverse logistics restructuring in 2026.

1. Where does our returns rate sit against NRF benchmarks (15.8% overall, 19.3% online), and is variance explained by category mix or operational underperformance?
2. Have we built our returns experience around current consumer expectation data (82% citing free returns, 76% preferring instant refunds, 71% deterred by poor experience), or are we operating on legacy assumptions?
3. Are we deploying AI for fraud detection given 85% industry adoption and 9% baseline fraud rate? If not, what’s our defensible alternative against industry standard?
4. Are we evaluating third-party consolidation networks given 49% of US retailers increasing 3PL focus? How does the routing layer between drop-off and processing affect our economics?
5. Have we mapped the six AI routing mechanisms — reverse pickup optimization, drop-off network routing, returns-aware forward routing, multi-modal dispatch, capacity-aware processing, round-trip optimization — against our operating model to identify which produce material cost impact?
6. Are we measuring returns experience as a customer retention lever given 71% of consumers won’t return after a poor experience, or only as operational cost?

The Real Question for 2026

The 2026 returns landscape isn’t a marginal optimization problem. It’s the active restructuring window with 64% of US merchants executing returns process changes they committed to in late 2025, returns volume rivaling significant P&L line items, and consumer expectations rising faster than most retailers’ operational capacity to meet them.

The strategic question is: given that returns are simultaneously a $850B operational cost burden and a customer retention lever — and given that AI-powered routing represents one of the primary cost-reduction levers available — are we restructuring our reverse logistics infrastructure to capture both, or are we executing 2025’s commitments without the routing layer that determines whether the restructuring delivers economic outcomes?

Frequently Asked Questions

What is the total size of US retail returns and what does it mean for 2026 planning? US retail returns totaled $849.9 billion in 2025, according to the 2025 Retail Returns Landscape report from the National Retail Federation and Happy Returns, a UPS company. This represents 15.8% of total annual retail sales. The 2024 figure was $890 billion. Online retail faces materially higher return pressure: 19.3% of online sales are returned, meaning nearly one in five online purchases comes back. For 2026 planning, the implication is that returns are a first-order P&L line item rivaling significant operational expense categories — particularly for retailers with significant online sales exposure, where the structural pressure is to grow channels that generate the most returns while reducing the rate at which those channels generate them.

How is AI-powered routing helping US retailers reduce returns cost in 2026? AI-powered routing and dispatching affects returns cost through six specific operational mechanisms. Reverse pickup routing optimization consolidates customer pickup routes to reduce miles per pickup. Drop-off network routing optimizes flow between consolidation points and processing facilities, reducing dwell time and storage cost through capacity-aware dispatch. Returns-aware forward routing incorporates return probability into forward delivery decisions, positioning high-return-risk shipments near consolidation infrastructure. Multi-modal returns dispatch coordinates across courier pickup, drop-off consolidation, locker networks, and store-based returns rather than treating each as separate streams. Capacity-aware processing dispatch routes returns to facilities with available capacity. Round-trip optimization — the structurally largest lever — batches returns pickup with forward delivery routes, reducing the marginal cost of returns pickup substantially. Magnitude varies by operational density and route structure, but operations capturing these levers produce materially different cost profiles than operations treating forward and reverse flow independently.

What customer expectations should US retailers plan around in 2026? NRF/Happy Returns 2025 data establishes the consumer expectation baseline for 2026 planning. 82% of consumers cite free returns as a major purchase consideration (up from 76% in 2024), 76% prefer return options offering instant refund or exchange, and 71% are less likely to shop with a retailer again after a poor returns experience (up from 67% in 2024). Four out of five consumers share negative returns experiences with friends and family. Gen Z (ages 18-30) makes 7.7 online returns per year on average. The 2026 implication: returns experience is a customer acquisition and retention lever influencing purchase decisions and post-purchase loyalty, not just an operational cost — and expectations continue rising rather than stabilizing.

What is the rate of returns fraud and why is AI fraud detection now table stakes? 9% of all retail returns are fraudulent, per NRF/Happy Returns 2025 data. Top fraud patterns: 71% overstated quantity, 65% empty box or “box of rocks,” 64% counterfeit decoy returns. 85% of US retailers now employ AI to detect or prevent return fraud — one of the highest concentrations of operational AI deployment in retail. Beyond outright fraud, close to two-thirds of consumers admit to costly behaviors including wardrobing, bracketing, sending back different items, or empty boxes; 45% believe “bending the truth” is acceptable. For 2026 operations, fraud detection investment is table stakes against industry standard rather than optional infrastructure — retailers without AI-based fraud detection are operating against the prevailing capability baseline.

What are returns consolidation networks and how do they fit 2026 strategy? Returns consolidation networks are operational models where multiple retailers share reverse logistics infrastructure — drop-off locations, transportation, processing facilities — to capture scale economies. The most visible US example is Happy Returns, a UPS company, operating a nationwide Return Bar network where shoppers drop off returns from participating retailers in under 60 seconds without packaging or printing. NRF/Happy Returns 2025 data shows 49% of US retailers are increasing focus on third-party logistics partners for returns handling. For 2026 strategy, the question is not whether consolidation matters but whether the model fits the operating context — and how the routing layer between drop-off and processing affects total economics. Operational benefits typically include reduced shipping cost through bulk consolidation, item-level verification (which helps prevent fraud), and improved customer experience aligned with the 82% consumer preference for free returns.

Should retailers extend return windows in 2026 given fraud concerns? Extended return windows present a counterintuitive operational dynamic. While longer windows might appear to increase fraud exposure, NRF/Happy Returns 2025 data shows 37% of retailers extended return windows as a holiday returns management strategy alongside fraud detection investment and 3PL partner focus. The operational rationale: longer windows reduce return urgency, smooth operational peaks, align with consumer expectations (76% prefer flexible options), and when paired with item-level verification at drop-off and AI-based fraud detection, fraud risk is manageable. Extended windows reduce wardrobing fraud in some categories by removing time pressure that drives “use and return” behavior. The 2026 strategic question is not extended windows in isolation but extended windows paired with the operational infrastructure — fraud detection, item verification, consolidated drop-off, AI-powered routing — that protects against fraud patterns the windows might otherwise enable.

Sources referenced: National Retail Federation / Happy Returns (UPS company) 2025 Retail Returns Landscape report (October 2025), based on surveys of 358 e-commerce professionals at large US merchants and 2,006 consumers conducted summer 2025; McKinsey & Company research on reverse logistics; Council of Supply Chain Management Professionals (CSCMP) State of Logistics Report. Specific operational and financial outcomes vary materially across US retail implementations based on category mix, customer segment, online sales penetration, route density, and operational maturity.