Retail trends 2027: 14 shifts shaping how people shop

The three biggest retail trends for 2027 are AI shopping agents that start completing purchases, shoppers who expect better service even while they hunt for value, and post-purchase service turning into a revenue channel. All three show up in the fall 2026 data, and all three land on the same place: the conversation a shopper has with your brand before and after they buy.

The backdrop is a steady but careful shopper. Deloitte's 2026 holiday forecast (Sep 10, 2026) puts November through January retail sales at $1.70 trillion to $1.71 trillion, up 4.0% to 4.8%, with ecommerce growing faster at 7.5% to 8.4%. The NRF forecast (Oct 15, 2026) uses a narrower November and December window and expects 4.2% growth to $1.013 trillion. People are still spending, but they're pickier about where, and about how they're treated once they get there.

Here are the 14 shifts worth planning around, with the first eight covering retail as a whole and the last six focused on ecommerce and DTC brands:

1. AI shopping agents start completing purchases

2. Search turns into conversation

3. AI moves from pilot to operating budget

4. Value-seeking shoppers don't settle for worse service

5. Stores become experience and service hubs

6. Trust in AI depends on transparency

7. Lean teams run on AI-assisted workflows

8. Retail media and new revenue streams keep growing

9. Brands fight over where the AI conversation happens

10. Pre-sale and post-purchase collapse into one conversation

11. Returns become exchanges and retention moments

12. Proactive order updates replace “where's my order”

13. Service conversations become a revenue channel

14. Peak season without hiring for peak

1. AI shopping agents start completing purchases

For most of the last decade, AI in retail meant a recommendation widget. The shopper still did the searching, the comparing, and the checkout. In 2026 that started to change, as OpenAI, Google, Shopify, Visa, and Mastercard all shipped or announced ways for an AI agent to place an order on a shopper's behalf.

Usage is real, but it's still early. NIQ found that by September 2026, 51% of US consumers had used at least one AI-powered tool to support their shopping in the past month, up from 42% in May. In that May 2026 NIQ research, only 5% had used fully autonomous AI agents to place orders for them. The gap between those numbers is where 2027 gets decided. Gartner predicted back in August 2025 that 40% of enterprise applications will feature task-specific AI agents by 2026, up from less than 5% in 2025, so the tooling is arriving faster than shopper trust.

AI-referred shoppers are also worth more per visit. Adobe found that in May 2026, AI-referred retail visitors converted at a rate 54% higher than non-AI traffic and generated 53% more revenue per visit. McKinsey sizes the global opportunity at $3 trillion to $5 trillion by 2030, though that figure counts AI-orchestrated revenue, which is broader than purchases an agent completes on its own.

What it means for your team: shoppers will ask an AI to do the legwork, and the brands that get the order are the ones whose product data, policies, and service answers are clear enough for that AI to act on. Our guide to how AI shopping agents are changing the ecommerce funnel walks through where the drop-off points move.

2. Search turns into conversation

Capgemini's retail trends research put a name on this one: “searchless” retail. A shopper types a full question into an AI assistant, gets an answer, and never touches your search bar, your category pages, or your filters. In Adobe's March 2026 survey, 39% of US consumers had used AI assistants for online shopping, and 55% said they turn to AI for inspiration and ideas, most often before they start shopping.

Two things change for retail teams. Off your site, the job becomes making sure AI systems can find, trust, and describe what you sell, which is what answer engine optimization for ecommerce covers. On your site, shoppers arrive expecting to ask a question in plain language and get a real answer, so a keyword search box that returns zero results for “warm boots for a wide foot” now feels broken. Our AI product discovery guide and site search checklist cover both halves.

Smith Optics shows what on-site conversation looks like when it works: Gladly AI resolves 67% of its product help and recommendation conversations.

A quick way to test where you stand is to pull 50 real questions from your chat logs and type them, word for word, into your own site search and into a couple of AI assistants. Note which ones get a useful answer, which ones get a product list that misses the point, and which ones get nothing. The misses are usually the same in both places: thin product attributes, missing fit and compatibility details, and policies buried in a PDF.

3. AI moves from pilot to operating budget

The pilot phase is ending because the budgets got real. Gartner forecasts that worldwide AI spending will total $2.7 trillion in 2026, a 49.5% increase over 2025. In retail specifically, KPMG's Consumer and Retail CEO Outlook (Feb 2026) found 64% of CEOs cite AI as a top investment priority, up from 57% in 2024, and 73% expect to spend 10% to 20% of their budget on AI in the next year.

Readiness hasn't caught up with spending. TCS's Global Retail Outlook 2026 found 85% of retailers aren't yet using multi-agent AI systems, and 51% call chatbots and virtual assistants their leading AI initiative. Deloitte's June 2026 executive survey found 29% of retailers have no defined approach to agentic commerce yet.

Once AI is an operating line, it gets judged like one. Expect 2027 conversations about AI to sound like conversations about any other channel: what did it resolve, what did it sell, what did it cost per conversation, and did customers come back. If your current AI can only answer the first of those, that's the gap to close before planning season.

4. Value-seeking shoppers don't settle for worse service

Deloitte's holiday forecast describes “value-seeking behaviors across income levels, including switching among brands and retailers and using promotions to manage spending.” Shoppers who are comparing harder are also leaving faster. The NRF and Happy Returns 2025 returns report found about 71% of consumers are less likely to shop with a retailer again after a poor experience, up from 67% in 2024.

A lower price doesn't buy a brand permission to answer slowly or lose track of an order. If anything, the value shopper has less patience, because they already did the work of finding the deal and they'll switch for the next one. That puts service quality in the same planning conversation as pricing and promotions, especially for brands competing with marketplaces on price.

Start by making the cheap parts of service fast. Order status, size questions, shipping cutoffs, and promo code problems are the questions a value shopper asks most, and they're the ones AI can answer in seconds, which leaves your team free for the customer who's about to churn.

It also helps to watch the moments where a value shopper decides whether to come back. A promo code that fails at checkout, a shipping delay nobody mentioned, or a return that takes three weeks to refund will undo the discount that won the order in the first place. Those are service problems more than pricing problems, and they're cheaper to fix.

5. Stores become experience and service hubs

The death-of-the-store story didn't hold up. Placer.ai's June 2026 Mall Index shows first-half 2026 visits up 4.7% at open-air centers and 1.9% at indoor malls compared with the year before, and its retail trends report describes online and offline retail converging through habits like buy online, pick up in store.

What's changing is the job the store does. More of it is service: picking up online orders, returning online purchases, getting fitted, asking an expert. Capgemini found that while shopping in physical stores, 76% of consumers value shelf-scanning apps that quickly highlight relevant products, so even in the aisle, shoppers want a digital assist.

For a brand with stores, the question is whether the store knows what happened online. If a customer chatted about a sizing problem yesterday and calls or walks in today, whoever helps them should be able to see that conversation. That's the idea behind Gladly's lifelong customer context: every conversation and order lives on one customer record that human and AI agents both see.

6. Trust in AI depends on transparency

Shoppers are using AI more and trusting it on their own terms. Capgemini's What matters to today's consumer 2026 (Jan 2026, 12,000 consumers in 12 countries) found 76% want clear rules for when an AI assistant acts, 71% are concerned about how gen AI tools use their data, and 67% expect brands to clearly flag AI-generated ads. Visa's September 2026 Trust Index found only 23% of US consumers trust GenAI to handle payment transactions on their behalf.

The escape hatch matters as much as the AI. A Gartner survey of 3,566 customers found 87% say it's essential for companies to provide an option to reach a human agent when using GenAI (Aug 2026).

Transparency in practice is pretty plain. Say when it's AI. Let the shopper approve anything that costs money. Make the handoff to a person easy, with the context carried over so nobody repeats themselves. Those three rules are most of the trust layer brands need before AI agents shop for customers.

One more thing to plan for in 2027 is consistency. If your on-site AI says one thing about a return window and your email team says another, shoppers lose trust in both. Grounding the AI in the same policies and order data your team uses, and reviewing what it tells customers each week, prevents most of the trust problems before they show up in reviews.

7. Lean teams run on AI-assisted workflows

Retail support teams aren't getting bigger, and most leaders aren't planning mass layoffs either. Gartner's April 2026 survey of 321 service leaders found 85% are expanding human agent responsibilities despite expectations of mass AI layoffs. Deloitte's 2026 Global Retail Industry Outlook found nearly 68% of retail executives expect to deploy agentic AI for operational and enterprise activities within 12 to 24 months.

In practice, AI takes the repetitive volume while people move up to the conversations that need judgment: the angry customer, the complicated exchange, the VIP. For a growing DTC brand without a 40-person contact center, this is the trend that levels the field. A small team with AI that already knows each customer's order history can answer as fast as a much bigger operation.

The handoff is where this works or falls apart. When the AI passes a conversation to a person, the person should see everything that happened, and the AI should keep helping in the background. That's how AI agent assist works in Gladly.

8. Retail media and new revenue streams keep growing

Retailers have figured out that their customer data and site traffic are assets they can sell. EMARKETER estimates US advertisers spent $60.32 billion on retail media in 2025 and will spend $71.09 billion in 2026, growth of 17.8%.

Retail media is mostly a large-retailer play, but the idea underneath it applies to everyone: every place a shopper engages with you can earn revenue if you treat it that way. Ads on your site, paid memberships, subscriptions, and service conversations that turn into orders all come from the same insight. For most mid-size and smaller brands, the revenue stream that's closest at hand is the service channel, which is where trend 13 picks up.

If you do sell ads or sponsored placements, the same trust rules from trend 6 apply. Shoppers expect sponsored results to be labeled, and an AI assistant on your site that quietly favors paid placements over the product that fits the shopper's question will cost more in returns and lost loyalty than it earns in ad revenue.

The next six trends are about ecommerce, specifically the service side of the online buying journey. (For the commerce side, like social selling, checkout, and payments, see our ecommerce trends post. For a closer look at personalization, self-service, and returns, see our ecommerce customer experience trends.)

9. Brands fight over where the AI conversation happens

The first big ecommerce question for 2027 is where the AI conversation takes place. A shopper can ask ChatGPT, Gemini, or Perplexity about your product, or they can ask the AI on your own site. Bain's May 2026 research found shoppers trust retailers' on-site agents three times more than third-party agents, and Bain also found AI accounts for up to a quarter of referral traffic for some retailers while still making up less than 1% of total traffic.

You'll need to show up well in both places. A conversation on a third-party AI surface doesn't carry your brand voice, your return policy, or anything you know about that customer from their last order, so the on-site experience is where you can win on knowledge and follow-through. Adobe expects AI traffic to US retail sites to rise 130% this holiday season, so the shoppers who click through from an AI answer are arriving in larger numbers, and they expect your site to keep the conversation going.

In practice, that means three jobs. Keep your product feed and policies clean so third-party AI describes you accurately. Give your own site an AI that knows things an outside assistant can't, like the shopper's order history, loyalty status, and past conversations. And make sure a shopper who arrives from ChatGPT with a question can ask it again on your site and get a better answer.

10. Pre-sale and post-purchase collapse into one conversation

Most ecommerce brands still run two separate experiences. A sales chatbot or product finder helps before the purchase, and a support tool takes over after it, with its own bot, its own queue, and no memory of what the shopper asked an hour ago. Shoppers don't see a difference. To them, “does this run small?” and “can I swap this for a size up?” are the same conversation with the same brand.

In 2027, the brands that win will merge those two experiences. Adobe's survey found 69% of shoppers who use AI are less likely to return an item they bought with the help of an AI assistant, which suggests that better help before the sale shows up in the numbers after it.

Balsam Hill runs pre-sale and service in one AI conversation, and in the first 30 days, nearly one in five shoppers who viewed a product in chat added one to their cart. That's the idea behind Gladly's conversational AI for sales: one conversation that stays with the shopper before the purchase and after it.

11. Returns become exchanges and retention moments

Returns are big enough to matter on their own. Retailers estimated in October 2025 that 15.8% of annual sales would be returned, totaling $849.9 billion, with an estimated 19.3% of online sales coming back. The same NRF and Happy Returns research found 76% of consumers are more likely to choose a return option that gives them an instant refund or exchange.

For 2027, treat the return request as the start of a conversation. A shopper who wants to send back a jacket because it's too tight is a shopper who still wants a jacket. If the first response is a size suggestion and a one-click exchange, the brand keeps the sale. If it's a return label, the brand hopes for the best. (We dig into why returns decide so much loyalty in a separate post.)

The same logic applies to cancellations and subscriptions. Ollie's team saves 45% of at-risk customers who reach out about canceling, and MaryRuth's has a 20% cancellation save rate, with those saves bringing in three times their cost per contact in revenue. Both teams treat a cancellation request as a problem to solve with the customer, and they answer fast enough to solve it before the customer gives up.

12. Proactive order updates replace “where's my order”

“Where's my order” (WISMO) is the question every ecommerce support team knows best, and it's almost entirely preventable. A Forrester data snapshot (Sep 2025) found 80% of US shoppers say it's important for retailers to offer an order confirmation with specific delivery or pickup dates, and three-quarters value status-update notifications.

More brands will get ahead of the question in 2027. The WISMO playbook is short: send the delay notice before the customer notices, let the AI answer order status instantly across chat, email, and SMS, and save the human conversation for the package that's actually lost. KÜHL saw a 44% reduction in WISMO emails after rolling out Gladly.

The brands that do this well also tie order updates to the rest of the conversation. If the delay notice goes out by SMS and the customer replies with a question, the reply should land with an AI or agent who can see the order, the delay, and the customer's history, so the answer is specific to that shipment.

13. Service conversations become a revenue channel

For years, the contact center was a cost line. That framing is falling apart, because the person contacting support is often a shopper with a credit card in hand and a question standing between them and the next order.

Kate Showalter, VP of Customer Care at Crate & Barrel, put it simply:

The numbers from other Gladly customers point the same way. KÜHL drove a 120% increase in revenue per call, and at Rothy's, over 20% of customers made a purchase after connecting with an agent. In both cases, AI took the routine questions off the team's plate, which gave agents time to help people buy.

Expect the scorecard to change, too. More brands will measure service on revenue alongside cost: conversion from chat, average order value on assisted orders, and saves on cancellations.

14. Peak season without hiring for peak

Seasonal hiring is shrinking. Challenger, Gray & Christmas reported that retailers added 461,500 workers in the fourth quarter of 2025, the smallest seasonal gain since 2008. NRF expects 325,000 to 375,000 seasonal hires for 2026, in line with last year, and Adobe expects the biggest jumps in AI traffic on Thanksgiving, Black Friday, and Cyber Monday, when support volume tends to spike too.

The brands handling this well let AI absorb the spike in routine questions and keep their experienced people on the conversations that need them. BSN Sports cut peak season staffing needs by 57%, going from 70 temporary workers to 30. Lauren Inman-Semerau, Head of Customer Experience at Rothy's, described the change this way:

If you're planning for holiday 2027, the time to set this up is the spring before, when volume is low enough to tune the AI on real conversations. Our post on preparing for peak season like Crate & Barrel has the checklist.

How to prioritize these retail trends

Fourteen trends is too many to act on at once. Pick by team size:

• Small teams (under 10 agents): start with trends 11, 12, and 14. Proactive order updates and AI on routine questions free up the most time, and that time goes to saving returns and cancellations.

• Mid-size teams: start with trends 10 and 13. Merging pre-sale and post-purchase into one conversation is the change that lets service start earning revenue.

• Enterprise retailers: start with trends 1, 9, and 6. Get product data and policies ready for AI agents, decide what your on-site AI does that a third-party AI can't, and set clear rules for when AI acts and when a person steps in.

Whatever size you are, trends 4 and 7 apply. Value shoppers will leave after one bad experience, and a lean team only keeps up if AI and people work in the same conversation.