Omnichannel retailing in fashion: Trends shaping 2026

Buy online, collect in-store. Order in-store, ship home. Purchase on the app, while in-store, return by mail three weeks later. None of this is new in fashion retail. It’s the shape of a fashion journey and what omnichannel retailing actually looks like from the customer’s side.

The infrastructure underneath it? Frequently still organized around a channel model that shoppers left behind years ago. Closing that gap is what the trends below are really about: eight shifts across payments, stores, apps, returns, personalization, and AI, each pointing at the same problem from a different direction.

New ACI Worldwide research, fielded by YouGov among 3,000 US and UK fashion and sportswear shoppers in June 2026, puts hard numbers on this trend. The report uses the term hybrid deliberately. Omnichannel commerce and unified commerce both describe what the retailer builds or aims to build. Hybrid describes what the customer actually does: one purchase journey that crosses more than one channel, assembled on the fly.

The distribution looks like this: Home delivery remains the volume driver, with 68% of shoppers buying online for home delivery. But more than a third (35%) buy online and collect in-store, 28% buy online and return in-store, 20% buy in-store and return by mail or courier, 18% place an order in-store for home delivery or store collection, and 15% use a retailer app while standing inside the shop.

Women lead hybrid behavior: Click and collect is at 41% vs. 28% of men, in-store returns of online orders at 35% vs. 21% of men. Sportswear shoppers go even further on hybrid behavior: They use retailer apps in-store at 21% vs. 15% overall and return online purchases in-store at 34% against 28%.

Geography is the biggest variable. Click and collect runs at 41% in the UK compared to 21% in the US, the widest transatlantic gap in the whole channel dataset. In-store returns of online purchases sit much closer, at 29% in the UK and 26% in the US.

Because respondents could select multiple choices, these aren’t six separate populations. They’re overlapping habits. The average fashion customer isn’t an online shopper or a store shopper. They are both, often within the same transaction. Supporting that behavior touches inventory, payments, store operations, app design, returns, and now AI agents.

While most leading retailers deploy multi-channel strategies, the reality is that many fashion retailers still run eCommerce, retail, and mobile app as separate departments, with a data and operational divide still existing.

Hybrid shoppers cut across channels, and that gap shows up in the customer’s experience as small, specific failures. The store can’t see the online order. The refund has to go back through the original channel, meaning a store can’t refund an online purchase. The card saved in the app has to be entered again on the website. Each is minor on its own, and collectively they’re the reason a hybrid journey converts worse than a single-channel one despite being worth more.

Unified commerce means one customer record, one view of inventory, and one set of payment credentials that every channel reads from and writes to, rather than three systems reconciling overnight. Retailers making that move are also finding they have to change how the channels are measured, because an eCommerce team incentivized on eCommerce revenue has no reason to fund a click-and-collect improvement that books as a store sale.

This trend gets left off most lists, and it has the clearest revenue uplift attached.

First, payment preferences don’t travel well. And preferences shift as much by channel as by country. For fashion purchases, debit cards lead in-store at 68% overall, but that’s 71% in the UK vs. 61% in the US, where 47% still pay cash in-store compared with 30% in the UK. Digital wallets hit 34% in the UK versus 23% in the US, and 51% of 18- to 24-year-olds prefer paying online with a wallet. Nearly one in five shoppers use buy now pay later (BNPL) online.

Miss the right method and the sale goes: 19% abandon when their preferred payment method isn’t available. When a payment fails, 39% give up entirely and 22% go straight to a competitor. Surprise costs at checkout are worse, sending 40% away.

Payment methods used for fashion purchases in-store, and online

Second, the part shoppers never see is where most optimization opportunity sits. ACI merchant data indicates that for large retailers, a 2–6% improvement in payment acceptance rates can translate into millions in recovered revenue.

AI is already performing several tasks in fashion retail. Behind the scenes, it forecasts demand and positions inventory closer to where it will sell. It also screens transactions for fraud in real time, catching patterns a rule-based engine or a human would miss. In front of customers, it handles service inquiries.

In the customer’s hands, AI is still used for recommendations. According to ACI research, 35% of consumers see value in AI-driven price-drop alerts, and 35% in comparing prices across retailers. These are the trusted entry points into agentic commerce. Beyond that, interest drops sharply: 53% are unwilling to let AI make purchases on their behalf under any circumstances, and only 7% would allow an assistant to make purchases without their approval.

Openness isn’t evenly spread, and it maps onto hybrid channel behavior. The customers already moving fluidly between retail app, store, and web are the ones most ready to add an agent to that mix. More concretely, sportswear shoppers are the least resistant to AI: Rejection falls to 44% against 53% overall, while price-drop alerts (43% against 35%), price comparison (43% against 35%), and AI help with returns (24% against 17%) all run well ahead. Women show a similar pattern, with 38% rejecting AI shopping tools outright against 42% of men.

All the AI-assisted jobs run on the same foundation: accurate data. Forrester predicts a quarter of shoppers will use retail chatbots or autonomous agents for product discovery in 2026, and an agent checking availability has no tolerance for inventory drift. A human shopper forgives a stale stock figure and picks something else; an agent reads it as unavailable and moves to another retailer, losing the sale before anyone sees the product page.

The store’s role keeps shifting toward experience, fulfillment, returns, advice, and brand trust, with the transaction increasingly initiated elsewhere. More than a third of shoppers buy online and collect in-store, 28% buy online and return in-store, and 18% place an in-store order for home delivery or store collection. None of those began at the till.

The store is also a place where the app gets used. In the same ACI survey, 15% of shoppers use a retailer app while standing inside a shop, rising to 19% among 18- to 24-year-olds. What they want from retailer apps is practical: easier browsing at 34%, order tracking and returns at 33%, discounts and promotions at 32%.

That overlap between a physical visit and an open retailer app is where contactless technology earns its place. NFC tags in garment labels, fitting rooms, or store displays let a shopper tap a phone to pull up sizing, stock in other locations, styling content, or a loyalty offer, without hunting for a code or being asked to download anything. The interaction is short-range and deliberate, which makes it a clean signal of intent. That signal can trigger a discount redeemable in the app or online later, turning an in-store session that ended without a purchase into an identified customer and a personalized offer.

All of it rests on the same condition. A store absorbing the service half of a purchase that started online only works when associates and systems can see the order, the inventory, and the customer in real time. Without that, click-and-collect handoffs become manual reconstruction at the counter, and a tapped coupon becomes an offer the business can’t honor in a different channel.

Personalization in fashion goes beyond recommendations to include customization, made-to-order services, and connected products, with shoppers increasingly expecting an item or an experience shaped around them rather than pulled off a rack.

As the ACI survey shows, another dimension of personalization in fashion is generational. Tailored product suggestions appeal to 25% of 18- to 24-year-olds against 11% of 55- to 65-year-olds, and outfit recommendations to 22% against 10%. Within retailer apps, the perceived benefit of personalization is nearly five times higher among the youngest group (19%) than the oldest (4%). The demand will likely steepen as younger shoppers gain spending power.

Another key issue is where personalization has to work. A customer’s real signals might be a fitting-room visit, a click-and-collect pickup, and an in-store return, none of which a recommendation engine reading web sessions can see. In a hybrid world, relevance depends on the whole journey, which puts personalization on the same foundation as everything else here: one source of truth for the customer, visible across every channel.

Social commerce accounts for roughly 15% of total eCommerce sales according to Statista Digital Market Insights. The ACI data shows how that mirrors in behavior. Social media or influencer trends drive impulse purchases for 22% of 18- to 24-year-olds, double the 11% average. Limited-edition releases move 14% of that group versus 8% overall. Sales and promotional events remain the biggest impulse trigger for everyone at 41%, rising to 49% among sportswear shoppers.

Demand shaped this way is spiky and unseasonal, which puts real pressure on payments and fulfillment infrastructure to scale instantly during flash sales and viral moments.

Returns used to happen where the purchase did. Now they’re a channel decision of their own: 28% of shoppers buy online and return in-store, and 20% buy in-store and return by mail or courier.

That makes the return part of the hybrid journey, and shoppers treat it as a service they judge the brand on. Order tracking and returns is the second most-cited benefit of a retailer app, at 33%, and there’s early appetite for AI here, too: 17% want help managing returns or exchanges.

Operationally, a store refunding an online order needs to see the original transaction, the payment method, and the customer. When returns run on separate systems per channel, the flexibility shoppers value most is exactly where the brand breaks down.

The policy question is just as delicate. Stricter return rules would push 55% of shoppers to buy elsewhere, so tightening for everyone costs more than it saves. The emerging answer is segmentation rather than restriction. Machine-learning models applied at the account level let retailers protect liberal returns for profitable customers while limiting exposure to the accounts that consistently cost more than they contribute.