According to a report Thursday (April 30) from Bloomberg News, this effort is happening in markets such as Florida, where Walmart stores have begun stocking more Cuban-inspired coffee and beans from a local producer. In other states, the company is offering local brands of condiments like mustard and mayonnaise.

The report adds that although regionally sourced items are nothing new, Walmart is aiming to stretch beyond its current assortment and prioritizing this work based on customer response.

A spokesperson for the retail giant told Bloomberg Walmart is melding together technology and merchant expertise to understand which products local customers value, and then quickly getting them on shelves.

Bloomberg notes there’s a balancing act in play: Local products can draw in more customers, but the vendors behind these items are typically smaller and can face more supply chain issues than national brands.

The report also points out retailers are feeling pressured, as rising gas prices and declining consumer sentiment makes consumers more cautious about spending.

In fact, consumer sentiment is now at a historically bad place because of the price of fuel. Last week, the University of Michigan’s Index of Consumer Sentiment fell to the lowest level recorded in its nearly 75-year history due to gas prices.

The connection between the cost of gas and consumer sentiment was seen earlier in the month, when gas prices softened after the announcement of a two-week ceasefire in the U.S-Iran war, followed by a modest uptick in consumer sentiment.

As for Walmart, research by PYMNTS Intelligence shows that the company and rival Amazon are now courting the same shoppers.

“The data shows that Amazon still leads in the fun, non-essential stuff, while Walmart dominates in necessities,” PYMNTS wrote earlier this month.

For example, Amazon captured 35% of consumer spending on sporting goods, hobby items, music and books, while Walmart enjoys 21% of food and beverage spend. However, both retailers are pushing into the other’s territory while also serving as “each other’s best teachers,” the report added.

“What’s changing is how aggressively both retailers are moving beyond those traditional lanes,” Doug Straton, chief marketing officer at Bazaarvoice (and former chief digital officer of Hershey), said in an interview with PYMNTS.

“Walmart is expanding its digital and marketplace capabilities to compete in more discovery-driven categories, while Amazon is pushing further into everyday essentials and repeat purchases.”

The new integration, announced Wednesday (April 29), is designed to let BigCommerce merchants connect their product catalogs, inventory and order management to “AI surfaces.”

“AI is fundamentally changing how people discover and buy products. Merchants need to meet shoppers in those moments and make it easy to move from discovery to purchase or risk being left out of the journey,” said Sharon Gee, senior vice president of product for AI at Commerce, Big Commerce’s parent company.

“With PayPal Store Sync, merchants can instantly connect their catalog to AI-powered shopping experiences and the PayPal consumer network, ensuring they’re not just present, but positioned to convert in the environments where commerce is evolving.”

PayPal Store Sync is a catalog and order management solution that is designed to link merchant storefronts with emerging artificial intelligence (AI) shopping channels.

An integration enabled by PayPal makes product data like pricing, images, descriptions, reviews and inventory instantly accessible to AI platforms, “where consumers increasingly begin their shopping journeys,” Commerce added in a news release.

The release adds that the integration makes Commerce merchants “discoverable and purchasable” on an expanding network of AI-powered shopping surfaces, such as Microsoft Copilot, Meta and Perplexity.

As PYMNTS CEO Karen Webster wrote in a column earlier this year, the behavioral shift Commerce describes — with consumers beginning their shopping journeys via AI platforms — has gone mainstream.

Research by PYMNTS Intelligence earlier this year found that 41% of consumers have already used dedicated AI platforms to discover new products.

“More striking is that a third say they have fully replaced their prior methods. They are not layering AI on top of old habits,” the column said.

The experience fueling this shift is “genuinely different from traditional search,” Webster added. Rather than through pages of links and sponsored listings, consumers get a structured answer that details the trade-offs between rival products.

That answer can be refined through conversation until it aligns with the actual buying decision, something keyword searches could never provide with any level of precision.

“But then the consumer leaves the conversation and goes somewhere else to complete the purchase,” Webster wrote.

“The question that matters now is not whether agentic commerce will eventually close that gap. It is who becomes a casualty on the agentic highway, and who benefits. And how.”

The company posted its strongest broad-based quarter in recent memory, with every product category and every region gaining simultaneously. CEO Shailesh Jejurikar described it as solid acceleration, calling out broad-based growth as the defining characteristic of the quarter. The result reflected not just improved products but a structural shift in how the company is deploying data, automation and consumer insight together at scale.

P&G is scaling four capability layers across its business: data analytics tools for frontline teams, AI-powered content creation and distribution for marketing, a Molecular Discovery Suite for product innovation, and manufacturing automation including unattended shift operations now live across nine categories.

The unattended shift model is the clearest signal of how the operating model has changed. Factory teams previously running overnight shifts are being upskilled while automated systems run the line. CFO Andre Schulten described the program as proven and now being accelerated, with the goal of pulling forward the company’s longer-term automation vision in response to current cost pressures.

“It took years to build these underlying platforms and capabilities, and we are now in full scaling mode across the company,” Schulten said. “We will close the loop and we believe this will create a new S curve for growth value creation centered around our consumers.”

The consumer-facing impact is already measurable. Germany’s Pantene tripled total consumer reach while cutting media spend by a fifth, deploying social media, influencer partnerships and AI-powered content tools. Content value share rose in Germany year over year. The same data infrastructure is now compressing supplier diversification and reformulation work in response to Middle East disruptions from years into weeks.

What Else Stood Out on the Call

• The Tide liquid upgrade, the biggest reformulation in 25 years on one of P&G’s largest businesses, is delivering mid-teens growth by giving consumers a better product at the same price. Schulten called it the clearest proof that the innovation model works.
• Baby Care is gaining share in most global regions. The U.S. remains the exception. Schulten committed incremental investment and said the playbook is clear. China, where Baby Care is growing double digits with birth rates declining and the overall market negative, is the proof point.
• P&G recorded a significant after-tax gain from the dissolution of its Glad joint venture with Clorox, which closed in January after the agreement expired. Clorox purchased P&G’s minority interest at fair market value.
• The company raised its dividend for the seventieth consecutive year, continuing a streak that stretches back to its incorporation in 1890. P&G has now paid a dividend every year for over a century and a third.
• Greater China grew organic sales in a market where volume is still negative across most channels. The only growth is online and Douyin. P&G said its brands are winning in both.

Topline Growth and Financials

P&G reported net sales of $21.2 billion for the third quarter, up 7% versus prior year, with organic sales up 3% driven by 2 points of volume and 1 point of pricing. Beauty led with 7% organic growth. Grooming grew 1%. Health Care rose 2%. Fabric and Home Care grew 3%. Baby, Feminine and Family Care grew 3%.

North America organic sales grew 4%, volume up 3 points. Europe rose 2%, Enterprise Markets up 6%. Greater China grew 3%. Latin America grew 5%, with Mexico and Brazil each up high single digits. Asia Pacific, Middle East Africa Enterprise grew 4%.

 

These tools enhance customers’ shopping experience, associates’ productivity, and the company’s efficiency across supply chain, operations, management, talent recruitment and talent development, according to the report.

“We are at a pivotal moment, not just for our company, but for the industry, as artificial intelligence fundamentally reshapes how customers shop and how associates work,” Walmart President and CEO John Furner said in the annual report. “We are harnessing its power to enhance our business, guided by our foundational values of service, excellence, respect and integrity.”

In a letter to shareholders released Thursday in conjunction with the annual report, Furner said Walmart is providing associates with technology and information that helps them better serve customers. Walmart-owned Sam’s Club said in September 2025 that it was giving frontline managers AI tools to help them make decisions faster and free them from repetitive tasks.

“Our associates, powered by AI, are delivering faster and more accurately than ever all around the world,” Furner said.

Walmart highlighted in its annual report the companywide AI learning pathways and certifications it offers its associates. The retailer announced in September 2025 that it was preparing to offer its employees free access to an AI certification program from OpenAI. In his letter to shareholders, Furner also spotlighted the retailer’s efforts to provide opportunities for associates to learn new skills.

“Whether it is one of our new programs to certify our associates as AI proficient, obtain a commercial driver’s license to become a Walmart fleet driver, manage a store, or develop their own solutions using our vibe coding platform, we create opportunities to advance their careers,” Furner said.

The retailer said in the annual report that it is reshaping associates’ roles to emphasize uniquely human strengths, identifying areas where AI can automate repetitive tasks, and making its workforce digitally skilled and AI-enabled.

“This includes preparing associates for new roles, technologies and ways of working, as well as deploying digital tools that support associate effectiveness, engagement and performance,” Walmart said in the annual report.

Walmart’s use of AI to enhance customer experiences was highlighted by Furner in his letter to shareholders in the form of the retailer’s AI agent, Sparky. The retailer introduced Sparky in its app in June 2025, saying the AI assistant helps customers find products, answers questions and makes recommendations.

“Our AI agent, Sparky, is helping customers save time, create solutions, and find the things they want and need at everyday low prices, creating a future for Walmart that is high-speed, convenient and personalized,” Furner said in the letter.

And while it can be viewed, in one sense, as an extension of the traditional retail context for proximity — first physical, then digital and now increasingly cognitive — the emerging battleground is being shaped by the impact of artificial intelligence on customer interfaces.

Amazon and Walmart, for example, are already racing to move beyond the limits of who has the best products or prices to compete over who can best understand and respond to the choices consumers make.

The new end zone for retail innovation is being fought across the “decision layer” of AI commerce. The emerging retail decision layer is not a single product or feature. It is an evolving system of recommendation engines, conversational agents, predictive pricing and fulfillment orchestration that collectively determines what consumers see, consider and ultimately buy.

In this new paradigm, winning is less about stocking shelves or optimizing search results, and more about owning the emergent layer that sits between intent and purchase.

For Walmart and Amazon, the stakes are existential. If third-party AI assistants or platform-agnostic agents become a primary customer interface for shopping, the retailer could risk becoming a commoditized infrastructure layer.

Read also: Amazon and Walmart Want More Than Your Prescription

The Rise of the Decision Layer

Historically, retail competition revolved around assortment, price and convenience. Online platforms like Amazon shifted the balance toward search and discovery, using algorithms to guide users through vast inventories. But the rise of generative AI and conversational interfaces is compressing that journey. Instead of browsing pages of results, consumers increasingly expect a single, context-aware recommendation — or even a fully executed purchase — based on minimal input.

PYMNTS Intelligence’s Prompt Economy work shows how far along this shift already is. Nearly 70% of consumers say they are interested in using artificial intelligence agents to simplify shopping tasks; more than half would like an autonomous agent to monitor and do their weekly shopping for them, or look through personal interactions with a friend to identify and purchase a gift.

Walmart’s recent push into AI can be seen as representing a calculated effort to leapfrog traditional eCommerce limitations and redefine its role in the customer journey. The company has been experimenting with generative AI tools that allow users to describe needs in natural language, such as “plan a week of healthy meals under $100,” and receive curated shopping lists that can be purchased in a single click.

Crucially, Walmart’s advantage lies in its hybrid model. With thousands of physical stores functioning as fulfillment hubs, the company can integrate real-time inventory data into its AI systems, enabling more accurate recommendations and faster delivery. This tight coupling of digital intelligence and physical infrastructure may allow Walmart to compete not just on price, but on certainty, knowing that what is recommended is available and can be delivered quickly.

Read more: Mid-Tier Retailers Caught Between Amazon and Walmart

Amazon, by contrast, is extending its long-standing dominance in algorithmic retail into a more autonomous future. The company has been layering generative AI capabilities into its platform, from enhanced product summaries to conversational shopping assistants that can guide users through complex decisions.

But Amazon’s real strength lies in its end-to-end control of the commerce stack. From product discovery to payment to last-mile delivery, Amazon has built a vertically integrated system that can be optimized holistically. This allows it to experiment with machine-led commerce models where the system not only recommends products but also dynamically adjusts pricing, bundles items, and schedules delivery based on predicted demand and user behavior.

Amazon’s investments in logistics, including same-day delivery and automated warehouses, feed into this system, enabling faster and more reliable fulfillment that reinforces customer trust in machine-generated decisions.

See also: Small Businesses Stop Chasing Amazon on Delivery Speed

Fulfillment as a Determinant of Choice

In the context of the decision layer, fulfillment is not an afterthought but a key input. AI systems must account for delivery times, shipping costs and inventory constraints when generating recommendations. A product that is slightly more expensive but available for immediate delivery may be favored over a cheaper alternative with a longer lead time.

Similarly, as the decision layer evolves, pricing is no longer a static attribute but a dynamic signal that can influence and be influenced by AI systems. The system must balance cost, quality, availability and delivery speed to arrive at the “best” option for the user. This requires integrating pricing data with other variables in a way that is transparent enough to build trust, yet sophisticated enough to maximize margins.

For consumers, the shift happening across retail may promise greater convenience and personalization. For retailers, it can raise new questions about control, differentiation, and trust. And for Walmart and Amazon, it could represent the next frontier in a long-running competition — one that will be decided not just by which company has the best products or prices, but by which one can best understand and shape the choices consumers make.

The home improvement retailer, which has traditionally served do-it-yourselfers, has made “Win the pro” a mantra, according to the report.

Home Depot is pursuing this initiative at a time when the home improvement market has been slowed by high interest rates and by remodeling costs that have leapt 45% since 2019.

“With housing turnover as low as it is, totally flat with no growth in new construction, our growth has to come from share capture right now,” Home Depot Chair, President and CEO Ted Decker told the FT.

Professional customers accounted for $90 billion of Home Depot’s $165 billion in sales last year, but the company is targeting a bigger share of the pro market that totals $700 billion, according to the report.

The firm is working to capture more of the pro business by trucking products to construction sites and by acquiring wholesale distribution companies, per the report.

PYMNTS reported in February that the rapid expansion of Home Depot’s professional business was the defining narrative of the company’s 2025 results.

The report said this shift was not merely a cyclical tilt toward contractors during a soft consumer environment, but a structural repositioning of the company’s identity. While Home Depot historically thrived on a balanced mix of DIY homeowners and professional tradespeople, it has increasingly targeted the pros whose spending patterns are more durable because they operate on longer project cycles, contractual backlogs and needs-based repairs.

The Home Depot announced Wednesday (April 15) that it aims to strengthen its same-day and next-day fulfillment strategy with its acquisition of SIMPL Automation, a company that uses advanced engineering and artificial intelligence (AI) technology to help distribution facilities operate faster and more efficiently.

In earlier acquisitions, Home Depot gained a foothold in roofing, landscaping and specialty building products with its integration of SRS Distribution; expanded its capabilities in drywall, ceilings and steel framing with its purchase of GMS; and added heating, ventilation and air conditioning (HVAC) products by entering into an agreement to buy Mingledorff’s.

The plan is outlined in a Restructuring Support Agreement (RSA) the company reached with most of its lenders and will “substantially reduce” the company’s debt, strengthen its financial position and enable it to pursue long-term growth and profitability, QVC Group said in a Thursday (April 16) press release.

Some of QVC Group’s U.S. subsidiaries are included in the Chapter 11 proceedings, but its international operations are not, according to the release.

All QVC Group brands are operating as usual; QVC, HSN and Cornerstone Brands continue to serve customers across all channels and platforms; and all vendors, suppliers and other general unsecured creditors of the filing entities will be paid in full for all goods and services, the release said. The financial restructuring process includes no planned layoffs or furloughs, it added.

“QVC Group is uniquely positioned to compete and win in live social shopping, and we are seeing early momentum in our WIN Growth Strategy,” QVC Group President and CEO David Rawlinson said in the release.

The company has become a top seller on TikTok Shop U.S., expanded its business on streaming and other platforms, consolidated its HSN and QVC operations, struck new deals with social and media partners, and rebalanced sourcing to account for tariffs, Rawlinson said.

“With the support of our lenders and a more appropriate capital structure, we believe we can deliver on our WIN Growth Strategy,” Rawlinson said.

It was reported Feb. 10 that QVC Group had held confidential talks with creditors to restructure its debt in bankruptcy. The company had been struggling with declining viewership, a $6.6 billion debt load and tax liability.

The company said in a Feb. 20 press release that it changed the timing of the release of its fourth-quarter financial results, which had been scheduled for Feb. 26, and would report them “within the timeframe specified as a non-accelerated filer under SEC guidelines.”

PYMNTS reported in February 2025 that QVC Group was addressing challenges presented by a cautious consumer environment and rising competition by reducing debt and expanding its digital presence by focusing on the burgeoning trend of social commerce.

In March, AI traffic converted 42% better than non-AI traffic, marking a “major reversal” from a year earlier, when AI traffic converted 38% worse, Vivek Pandya, director of Adobe Digital Insights, said in a Thursday blog post.

“Rising consumer trust has played a factor, with Adobe’s survey showing that 66% of respondents believe AI tools provide accurate results,” Pandya said. “This is giving shoppers confidence and driving more transaction activity.”

Conversion is a measure of visits to a website that result in purchases, according to the post.

Two related metrics are also higher for AI traffic. Adobe found that in March, individuals who landed on a retail site from an AI source spent 48% more time on the website and browsed 13% more pages than those who landed from a non-AI source.

The PYMNTS Intelligence report “How AI Becomes the Place Consumers Start Everything,” which was published in December 2025, found that dedicated AI environments are beginning to replace traditional discovery.

“Winning attention increasingly depends on whether a brand’s offers, policies and product truths can be interpreted and recommended inside conversational environments,” the report said.

Adobe also announced in its Thursday blog post that the amount of traffic from AI sources to U.S. retail sites saw year-over-year growth of 269% in March and 393% in the three months from January through March.

The company found that 39% of consumers said they have used AI for online shopping and that 85% of those consumers said the technology improved their shopping experience.

“These figures highlight the durable value that AI is delivering in the eCommerce space, shortening the time it takes for consumers to find what they need or locate relevant discounts,” Pandya said in the post.

Adobe also released new data in the post showing that 66% of the individual product pages on retail websites can be read by large language models (LLMs), meaning that the other 34% of sites have not been optimized for LLMs.

“Retailers have thousands of SKUs, and our data shows that much of the content is currently invisible to LLMs,” Pandya said in the post.

But recent headlines from both Amazon and Walmart underscore that as digital distribution starts to equal the benefits of brick-and-mortar locations, a new category is emerging, one that might be called “continuous care commerce.”

Amazon Pharmacy said it will offer Eli Lilly’s newly approved oral GLP-1 treatment Foundayo with real-time availability, transparent pricing, automatic manufacturer coupons and same-day delivery in nearly 3,000 cities and towns, expanding to 4,500 by year-end.

Walmart, meanwhile, has expanded its Better Care Services platform to support customers who are taking or considering GLP-1 drugs. The retailer is combining virtual care, nutrition services, digital tools and access to its nearly 4,600 pharmacies, while also offering same-day delivery in as fast as an hour in many markets and free delivery for Walmart+ members. The platform now connects customers to a group of third-party providers spanning fitness, dietitian services, AI-supported coaching and telehealth-based obesity care.

This new category of continuous care commerce sits at the intersection of retail, healthcare and subscription services, and it is being defined by ongoing engagement rather than episodic transactions. The GLP-1 drug is merely the entry point for Amazon and Walmart.

See also: Amazon and Walmart Deepen Healthcare Push With Prescription Delivery and Telehealth Expansion 

From Prescriptions to Platforms

On the surface, both GLP-1 announcements are about the same consumer opportunity: meeting demand for high-profile weight-loss therapies, including Lilly’s new oral option. But the operating models of the two retailers are different.

Amazon is leaning into speed, inventory visibility and digital convenience. Its message is that pharmacy should work more like modern eCommerce — customers should know whether a drug is in stock, what it will cost and how quickly it can arrive. Amazon is also pairing home delivery with plans for pharmacist-supported kiosks at select One Medical locations, tightening the handoff between diagnosis, prescription and fulfillment.

Walmart’s strategy is broader and more omnichannel. Its announcement treats medication access as only one piece of a more fragmented weight-management journey that also includes provider access, nutrition support, behavior change and insurance navigation.

That is why Walmart is using Better Care Services as an orchestration layer, bringing together services such as Aaptiv, Berry Street, Curai Health, MyCare by Twin Health and Wheel alongside pharmacy fulfillment, a redesigned GLP-1 destination on Walmart.com and nutrition guidance through its Nutrition Hub.

At a high-level view, it’s becoming apparent to observers that Amazon and Walmart are not just competing to fill prescriptions, they are competing to own more of the digital healthcare journey. GLP-1 medications, which often require long-term use and behavioral adjustments, are uniquely suited to this emerging strategy. Patients need not only prescriptions but also guidance on diet, exercise and side-effect management.

This can create recurring touchpoints and revenue opportunities across multiple domains such as telehealth visits, nutritional products, fitness services and even grocery purchases aligned with treatment plans.

In “The New Checkout: Crimped Consumers Lean Into Online Retail and Digital Wallets,” PYMNTS Intelligence finds that financial pressure is reshaping shopping behavior in ways that go beyond broad spending trends, with high-stress online retail shoppers 34% less likely to buy from Amazon than low-stress shoppers.

See also: Retailers Focus on Data and Payments as Shoppers Pull Back 

The Rise of Continuous Care Commerce

The winning formula in this new landscape may not be about dispensing the most prescriptions or offering the lowest price. The ultimate prize that Amazon and Walmart are chasing is one that sits closer to becoming the default platform through which patients experience care.

For Amazon, that could mean embedding healthcare into its broader ecosystem of Prime services, devices and data. For Walmart, it could mean leveraging its physical footprint and everyday low-price positioning to become the most accessible healthcare destination in the country.

Same-day delivery of prescription drugs, in-store kiosks that dispense medication minutes after a consultation and integrated platforms that guide patients through complex treatment journeys were once disparate innovations. Now they are coalescing into a coherent model.

For payments, banking and FinTech executives, the significance goes beyond healthcare.

GLP-1s are creating a new commerce stack around recurring prescriptions, insurance adjudication, cash-pay pricing, coupon automation, membership benefits and adjacent spending on food, fitness and clinical services.

Amazon’s play is to compress time-to-therapy and digitize the transaction. Walmart’s is to bundle fulfillment with surrounding services and store-based accessibility. Both are turning pharmacy into a strategic platform business, not a back-of-store function. The contest now is over who can remove friction most effectively — from prescription and payment to delivery, adherence and follow-on care.

That scene plays out millions of times a day across grocery stores, retail shops, restaurant apps and eCommerce checkout flows. A deal is out there. A consumer wants it. But the engine to connect them sputters and fails. The store collects the data point on an unredeemed offer and moves on. The brand absorbs the wasted promotional spend and chalks it up to the cost of doing business. The consumer, tired by all the jitter-jive associated with the three or four steps required to find and then redeem a promo code or an offer, eventually stops trying.

“So what,” some merchants and brands might say. The customer still shopped at the store, still bought the product and, bonus, paid full price. What’s so wrong with that picture?

Here’s what’s wrong.  Every one of those unredeemed offers isn’t just a missed connection. It’s a missed connection with a customer who may shop somewhere else next time.

The consumer who never saw the offer and paid full price probably wondered whether they missed out on a deal somewhere else for the same thing. The brand spent the promotional dollar and got nothing back. The merchant lost the chance to win a basket that might have looked different, even bigger, with a customer who might be more loyal had the right incentive arrived at the right moment.

New data from PYMNTS Intelligence finds that 50% of restaurant diners and nearly half of retail shoppers noticed no offer during their most recent visit. The offer was there but they couldn’t find it, didn’t see it. That’s not a rounding error in the redemption data. These are the customers brands most want to reach and are most consistently failing to convert.

A new PYMNTS Intelligence report produced in collaboration with FIS surveyed 2,754 consumers across grocery, restaurant and retail, putting hard numbers to a problem the industry has been tolerating for years. The findings aren’t a gentle critique. They describe an offers economy that’s out of step with the consumers it was built to serve, extracting data and attention at the top of the funnel while failing to deliver value where it matters most. At the bottom of the funnel, when it’s time to close the deal.

What the data reveals is that the breakdown in the offers economy isn’t about coupon mechanics or loyalty app design. It’s about whether the promotional dollars that brands, merchants and issuers collectively spend are achieving the one thing offers are meant to do. Change behavior.

PYMNTS Intelligence data shows they can, and sometimes they do. But the $42 billion gap in the offers economy points to a structural deficiency that has grown too large to ignore.

The right framework for understanding this structural breakdown is FIT: Friction, Inertia and Time. I’ve been writing about these forces for years, drawing on data from dozens of platform inefficiencies to develop it. What I’ve found is that each force operates independently. Together, they’ve created an offers economy that consumes enormous promotional investment while delivering outcomes that fall far short of what new technology, new models and new ways of thinking about offers now make possible.

Read More: Using the FIT Framework in a Digital 3.0 World

The Wanamaker Problem, Still Unsolved

The early department store pioneer John Wanamaker famously said that half of his advertising money was wasted, but he didn’t know which half. That was in the early part of the 1900s, when paper and pen were the most innovative tools available to track those outcomes.

One hundred and twenty-six years later, that dilemma defines the failure of the 2026 offers economy, even as offers have gotten richer and more plentiful and the technology available to serve them is now extraordinarily sophisticated.

Among the consumers who did find an offer, only 13% online and 10% in-store experienced the automatic application of the discount at checkout. The other 87% to 90% had to put a lot of elbow grease into redeeming them, clearing an average of more than two active hurdles just to use a deal they were already aware of, the PYMNTS Intelligence data found.

And when consumers who saw an offer but said “no thanks” were asked why, 40% said the offer wasn’t relevant. Not the obstacle course between discovery and checkout. Irrelevance. The offer had already captured their attention and in many cases their personal data. But returned a deal they didn’t want.

Read More: Personalized Offers Are Powerful — But Too Often Off-Base

This disconnect is commercially more serious than a leaky funnel.

The $42 billion sitting uncaptured in the gap between promotional dollars spent and consumer value delivered is the economic impact of a system that isn’t living up to its potential.

Seven in ten consumers who noticed an offer changed what they bought or how much they bought when the offer actually reached them.

So, every dollar disappearing into the gap between an offer that existed and a consumer who never found it is more than wasted spend. It’s a lost opportunity to change behavior, win a brand switch, build a basket or earn a payment method preference.

The outcomes the offers economy is supposed to produce.

Making the Offers Economy More FIT

My two cents is that the friction in the current offers system isn’t accidental. It’s a deliberate design choice.

Think about your own experience in finding and redeeming offers. The offers ecosystem was built to use the lure of a discount as a mechanism for data capture at the top of the funnel. Sign up for the email. Create the account. Opt into the text notifications. The consumer is asked to “pay” in personal information and future attention before they have any basis for trusting that what comes back will be relevant or worth the exchange.

When 40% of non-redemptions happen because consumers find them irrelevant, it means the data capture is often happening without the personalization payoff that was supposed to justify it. The brand got the email address. The consumer got nothing they wanted.

The “I love it/I hate it” ubiquitous promo code is the most visible symptom of this dysfunction.

A brand distributes codes across email campaigns, coupon aggregator sites and promotional partnerships, loses control of who redeems them and under what conditions, captures no meaningful attribution data from the transaction and builds no relationship with the consumer who found the deal on a third-party site and who will return to that site next time rather than to the brand or merchant. The code is not a marketing tool. It is a markdown without meaningful attribution.

That dysfunction persists not because merchants and brands can’t see it, but because inertia has made it too comfortable to ignore. And, ironically, so durable.

Consumers have adapted to the broken system rather than rejecting it. They use secondary email addresses for promotional signups. They abandon carts and wait for the recovery email that almost always arrives with a better offer. They have learned the game and play it, which creates a false signal for merchants and brands who look at redemption rates and email list growth and conclude that the system is working.

What the metrics don’t capture is the 27% of shoppers who pay no attention to offers at all because the current offers ecosystem hasn’t given them a reason to engage. Those consumers aren’t lost. They’re waiting for an offers experience worth their attention and their loyalty. The longer inertia holds the current system in place, the more the third force, time, works against everyone.

Read More: Embedded Offers: The Billion-Dollar Opportunity Inside Recent Consumer Spending

The dominant offer discovery channels — the merchant apps, checkout screens and in-store signage — all require the consumer to already be inside the purchase flow. The offer arrives after they’ve already finished their shopping. It creates no opportunity to influence what goes in the basket, consider an alternative product or increase spend.

The generational data makes the time pressure across merchants and brands more real. Gen Z is the most likely to shut the door entirely on offers, and therefore brands and stores, when presented with manual steps and promo code hunts.

Read More: The Five Rules of Engagement for Gen Z Spending and Payments

Nearly one in five Gen Z (19%) shoppers who saw an offer and didn’t use it cited too many steps as the reason, compared to one percent of boomers. For this generation, friction is not an inconvenience. It’s a reason to shop with another merchant or stick with the brand they already know rather than try something new.

What a Different System Changes

The  case for a better offers architecture starts with understanding, and then embedding offers, into the customer journey at the start, and not at the end.

Nearly nine in ten consumers say they want to see every relevant discount before they decide what goes in their cart. Before they decide they’re finished shopping and want to call it a day.

An embedded smart offer delivers it at the moment of intent. That shift does more than improve the user experience. It changes the purchase decision itself.

An offer that finds the consumer rather than waiting to be found doesn’t require effort, trust in a coupon aggregator or memory of a promo code under pressure at checkout. It arrives attached to the product in their consideration set, delivered through the card they already use, built on their actual purchase history rather than a demographic bucket.

The data finds that when offers do reach consumers, seven in ten change what they buy. Seven in ten change how much they buy. The goal is to make finding offers the default rather than the exception.

Read More: The $42 Billion Checkout Opportunity Hiding in Plain Sight

One-to-one personalization is what separates this model from every prior iteration of card-linked offers. The card credential carries transaction history across merchants and categories at a level of granularity that no email list or loyalty program can approach.

It knows not just that a consumer shops at a particular grocery chain but which brands they buy consistently, which they have tried once and abandoned, which categories they trade up in and which they treat as commodities.

A dynamic offer built on that data is much more than a discount. It is a precisely timed intervention in a known purchase pattern, served to defend a brand relationship showing signs of fatigue, to introduce a product at the moment the consumer is most likely to try something new, or to reward the specific behavior the brand wants to reinforce.

Read More: AI Pushes Personalization From Guesswork to Growth

According to PYMNTS Intelligence data, four in ten consumers say a form of smart, embedded real-time savings would be highly influential in making a payment method that supports it their default. Seventy-seven percent say it would be at least somewhat influential. The card that delivers embedded smart offers seems influential in winning in the wallet.

New Economics for Merchants and Brands

The attribution crisis at the center of the offers economy is as consequential as the consumer experience problem but gets far less attention.

Brands spread promotional budgets across email, coupons and loyalty programs and get back data that is too weak and too delayed to guide the next decision. Money goes out and redemption rates come back, but whether an offer drove new behavior or simply discounted a purchase that would have happened anyway is largely unknowable.

It is the Wanamaker problem, 126 years later, still unsolved.

Using the card credential as the delivery layer could address this at its root. The card is present at every transaction, which means a brand funding an offer at this layer knows exactly what was purchased, where, by whom and whether the behavior was incremental, such as a trial, a basket expansion or a brand switch.

The promotional dollar no longer buys impressions. It buys outcomes. Return on investment is not inferred. It is measured, attributed and immediately actionable.

For merchants, this changes the economics in a meaningful way.

Brand-funded offers become a source of incremental revenue rather than a cost center. For merchants, this reframes offers from an expense to manage into an asset that drives acquisition and retention.

The result is a reallocation of promotional spend away from impression-based marketing with uncertain outcomes and toward incentives tied to specific products, merchants and behaviors. A fundamental shift in how the offers economy works.

The Card’s Untapped Commercial Position

For issuers, this creates something new. It is a commercially meaningful position at the center of the offers economy that no ad network, email platform or coupon aggregator can replicate.

It is grounded in trust, verified transaction data and full visibility across the purchase journey. The question is whether issuers recognize the opportunity and move with the urgency it demands.

PYMNTS Intelligence data suggests the consumer is already there. Among those most willing to engage with embedded and personalized offers, 75% are willing to share data with banks and 78% with retailers.

These consumers are high frequency and high value. They skew toward millennials and bridge millennials and have established financial relationships.

This is the audience brands want to reach, and they’re ready to let the card be the platform that connects them.

Why Agentic Commerce Shortens the Window

The case for a better offers economy stands on its own in the current environment. But agentic commerce makes the window for building it shorter than most issuers and merchants currently appreciate.

AI-powered agents already assist consumers with purchase decisions. The next generation won’t assist. They’ll execute. A consumer sets preferences and constraints and the agent handles the research, the selection and the transaction. In that environment, the offers ecosystem as currently constructed isn’t just inefficient. It’s irrelevant.

Read More: What Happens to Stores When AI Agents Do the Shopping?

An AI agent doesn’t hunt for promo codes. It doesn’t sign up for email lists. It doesn’t activate loyalty IDs. If an offer can’t be accessed programmatically through a credentialed interface the agent can query and apply without intervention, the offer doesn’t exist for that transaction. The promotional dollars behind it simply don’t connect.

A tokenized smart credential is best positioned to survive this transition. An offer embedded at the card credential layer doesn’t need the consumer or the agent to do anything. It’s queried, surfaced, applied and attributed automatically. The agent selects the payment credential that delivers the most value at the point of purchase. The card with the richest offer layer wins the transaction by default, without ever competing for attention at a checkout screen.

Read More: Demystifying AI’s Capabilities for Use in Payments

The card that hasn’t built this capability will not lose that competition gradually. It will lose it at scale, as agent-mediated commerce moves from a niche behavior to a default one over time.

The Offers Economy Bet Worth Making

The argument for a better offers economy ultimately rests on a behavioral claim the PYMNTS Intelligence report makes with data-driven clarity.

Offers change what people buy, how much they buy and which payment method they use to buy it.

According to the data, these aren’t incremental improvements. They’re substantial shifts in commercial outcomes driven entirely by the presence of a relevant, timely, frictionless offer.

The current offers economy captures only a fraction of this behavioral potential because it was designed around data extraction rather than value delivery, and because the friction it introduces at every stage causes the majority of consumers to never encounter the offer at all or to abandon it before redemption.

An embedded smart offers model inverts this logic entirely. The offer finds the consumer. It’s relevant because it’s built on verified transaction data rather than demographic stereotypes.

It’s applied automatically, so the behavioral effect does not depend on the consumer remembering to act at the right moment or clearing two, three or more hurdles to redeem it, if they see it in the first place.

And it creates a data loop that allows brands to observe outcomes directly and improve targeting with each iteration.

The consumers most ready to engage with this model represent more than half the U.S. adult population.

The brands most likely to fund it are the ones watching their promotional budgets produce diminishing returns in channels that can’t demonstrate attribution.

The merchants most likely to benefit are the ones that need new sources of promotional revenue that don’t require them to sacrifice already thinning margins.

The issuers most likely to build it are the ones that understand the card credential is no longer just a payment instrument. It’s foundational for building a relationship with their customer.

 

Until NEXT time.

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