Google made considered one of its biggest moves yet in agentic commerce in May when it introduced Universal Cart, a persistent shopping cart that spans Search, Gemini, YouTube, and Gmail. The deep integration allows shoppers to find, compare, and buy across merchants through Google’s ecosystem.
For consumers, the pitch is convenience. For retailers and types, the danger is far larger, as Google moves closer to owning the shopping decision before the patron ever reaches a retailer’s site.
Anthony Ferry, CEO of Wayvia (formerly PriceSpider), sees Google’s Universal Cart as a significant warning sign for brands and retailers. He said it changes who owns the patron relationship, with Google constructing one other walled garden where consumer decisions occur inside its ecosystem, out of sight of brands.
“Retailers face an existential threat. As Google and Amazon win consumer loyalty through sheer convenience, the direct relationship between retailers and customers is crumbling. Retailers that may’t command their very own audience risk becoming essentially achievement centers and low-margin warehouses,” Ferry told the E-Commerce Times.
Visibility of Shoppers’ Insights at Risk
In response to Ferry, brands risk sleepwalking into dependency on a handful of AI-powered platforms. They’re losing visibility into how shoppers make decisions and losing control over where and the way consumers seek for products.
“Smart brands will counteract this by doubling down on their owned media, where they still get first-party data, direct consumer relationships, and shoppable experiences they control. Everyone else will probably be renting visibility from whichever holds the keys to the platform,” he said.
Wayvia is an e-commerce intelligence platform that helps brands track their products online, manage pricing, and switch marketing campaigns into easy buying experiences for shoppers. The corporate has expanded its tools to assist brands adapt to modern artificial intelligence (AI) shopping assistants.
Ferry warned that retailers risk losing control of the mid-funnel, reducing the brand’s website to little greater than a transactional endpoint. Retailers live and die by customer lifetime value (LTV) and repeat purchases. Losing the initial data touchpoint breaks that pipeline.
He suggested that marketing tactics must change when AI agents filter options for consumers. With the black box problem in agentic commerce, brands won’t know whether or not they lost a sale because of price, algorithmic bias, or supply chain metrics.
Unwrapping Agentic Commerce’s Black Box Issues
We asked Ferry to clarify why Google’s Universal Cart is an issue for brands and retailers. He also shared his views on how AI shopping platforms are changing who owns the patron relationship.
E-Commerce Times: In a world with Universal Cart, what happens to the retail website’s traditional role as the first venue for discovery and product comparison?
Anthony Ferry: The retail website doesn’t go away, but its role changes pretty dramatically. For the last decade, retailers have been attempting to pull shoppers into their very own web sites, apps, and loyalty programs, where they’ll shape the basket.
If the patron starts in your site, you possibly can control merchandising, show the promotion, recommend the bundle, promote the private label, capture the e-mail, and convey that customer back. Universal Cart moves a variety of that behavior back into Google’s world.
The cross-sell and upsell issue shows up there. A retailer loses a visit, plus the add-on purchase items. If Universal Cart becomes the place where the basket is assembled, retailers could have to earn that consideration inside Google fairly than their very own aisle.
How does Universal Cart change the retailer’s role within the shopping journey?
Ferry: Retailers like Amazon or Walmart had less reason to advertise their very own house brands on one other platform’s shopping environment. The purpose of a house brand was to win inside its own environment. If Google owns more of the pre-purchase conversation, a retailer’s private label starts to look more like a manufacturer’s brand.
If the basket is built inside Google, the retailer’s website becomes less the front door and more the achievement layer. The product page must be readable by AI. Inventory must be accurate. Pricing must be current. Reviews should support the use case. The checkout path has to work.
If Google manages a persistent cart across Search, YouTube, Gemini, and Gmail, how does a brand optimization strategy shift?
Ferry: On this recent persistent model, brands must give attention to ensuring their products are visible, accurate, and straightforward for an AI system to recommend and place of their customers’ baskets. That sounds easy, but it surely changes a variety of the work behind the scenes.
Product data, retailer availability, reviews, and the standard of the retailer path turn out to be more essential. If the AI sees two products, it has every reason to pick out the one which is cheaper, higher reviewed, easier to grasp, in stock nearby, and available through a cleaner checkout path.
Does SEO effectively turn out to be agent optimization to make sure a product gets placed into that universal cart?
Ferry: In practice, yes. I’d not make the term sound more complicated than the work actually is. search engine marketing was about helping a page get found. That is about helping a product get chosen.
How is AI’s shopping process different from that of a human purchaser?
Ferry: An AI shopping assistant will not be browsing as an individual does. It’s trying to unravel a shopping problem. If a client asks for sunscreen that won’t irritate a child’s skin and might arrive today, the AI doesn’t need a vague brand story. It needs a transparent product, strong proof, accurate inventory, good reviews, and a clean path to buy. That’s where brands have to focus.
When a consumer shops fully contained in the Google ecosystem, what first-party data are retailers missing, and what are the long-term consequences for his or her CRM and retention efforts?
Ferry: The invaluable data is every little thing that happens before the order is placed. Without it, the retailer has a much thinner view of the client. These include the patron’s query, products compared, other retailers considered, expectation of a price drop, and the role of faster delivery.
These other missing aspects also matter: Did Google show a less expensive substitute? Did reviews push one product ahead of one other? Did a loyalty perk matter? Did the patron select the retailer, or did Google effectively select it?
That’s the information retailers use to grasp demand. It’s also the information they need for CRM, loyalty, personalization, and retention.
How can retailers create shopping experiences compelling enough to drag consumers away from Google’s Universal Cart?
Ferry: A brand or owned experience can’t be a brochure anymore. It cannot tell the brand story after which send the patron into the dark. It has to assist the patron make a purchase order. Meaning answering real product questions and giving the brand visibility.
The owned experience also needs to supply something beyond convenience: exclusive products, early access, higher bundles, subscriptions, product education, community, service, and loyalty that really changes behavior.
Will brands be forced right into a race to the underside on price to be the chosen option by Google’s persistent cart?
Ferry: Commodity brands are probably the most exposed. If an AI assistant sees five products that look mainly the identical, it’ll start using the cleanest tiebreakers. Price, delivery speed, reviews, and availability. That’s bad news for brands that lack a transparent reason to be chosen.
Most shoppers aren’t emotionally attached to where they buy batteries, paper towels, shampoo, medicine, pet food, or beauty basics. If the AI finds a very good product, a very good price, and a very good delivery window, that trip may never occur.
But I don’t think this implies every brand gets dragged right into a race to the underside. Differentiated brands still have room. If the brand has a selected use case, strong reviews, clear product content, reliable availability, and an actual repeat-purchase relationship, the AI has more to work with than simply price.