Adobe Digital Insights measured AI driven referral traffic to US retail sites up 693 percent year over year during the 2025 holiday season, and found AI referrals converted 31 percent better than non AI traffic over the same period.
Those numbers describe traffic arriving somewhere. For most consumer product brands, that somewhere is a retailer, a marketplace, or a review site, because those are the pages carrying the specifications, prices, and reviews that answer product questions.
Brand Sites Usually Lose to Retailers on Product Queries
A brand product page typically carries lifestyle photography, an emotive description, and a buy button. A retailer product page for the same item carries dimensions, materials, weight, compatibility notes, hundreds of reviews, and a price.
Asked which of two products has the longer battery life, a system needs specifications. It goes where the specifications are. The brand's own page describing a product as thoughtfully engineered for modern living provides nothing usable.
This is the same specificity problem that runs through the non-commodity content guide, and consumer brands have it worse than most because brand voice guidelines actively push toward the vague end.
Complete Product Schema Is Not Optional Here
The schema mechanics are covered in the schema markup guide. What changes for physical products is how much of the answer lives in structured attributes rather than prose.
Product schema supports properties most brand sites leave empty. GTIN, MPN, brand, colour, material, size, weight, and dimensions. Each one is a fact a comparison query might turn on, and each empty field is a question your page cannot answer.
The identifiers matter more than they look. A GTIN is how a system knows the item on your page and the item on three retailer pages are the same product. Without it, your page is describing an unlinked product that happens to share a name, which is the disambiguation problem from the entity disambiguation guide applied to inventory.
Offers with real availability and price, kept current. A schema block asserting in stock for a discontinued product is worse than silence.
Specifications Belong in Text, Not Only in a Tab
Product pages commonly hide specifications behind a tabbed interface that loads on click, which puts them in the rendering situation covered in the SSR versus CSR guide.
A specification table built as a real semantic table, present in the server rendered HTML, is readable. The same table rendered by JavaScript when someone clicks Specifications is not, and this is one of the most common patterns on brand ecommerce sites.
The table structure itself matters too, per the data tables guide. Row headers naming the attribute, cells carrying units, no merged cells. Battery life in one column and eighteen hours in another is extractable. A design grid with the same information positioned visually is not.
Reviews Are Where the Answer Actually Comes From
Seer Interactive found review queries trigger an AI Overview 86.3 percent of the time. For physical products, review content frequently is the answer, because durability, fit, and real world performance are things only owners can report.
Brands that host no reviews cede that entirely to retailers and review platforms. Brands that host reviews but strip anything critical produce a corpus that reads as curated, which is both less credible and less useful, for the reasons covered in the review response guide.
Review text carries the citation value rather than the score. A review noting the strap loosened after six months is a specific durability claim. Four stars is not. Prompting reviewers for specifics is the intervention with the highest return here.
The Retailer Relationship Cuts Both Ways
Retailer pages will often outrank and out cite your own for your own product. That is not entirely a loss, since a purchase through a retailer is still a purchase, but it has two real costs.
The retailer's product description is frequently a truncated, out of date version of yours, sometimes with errors introduced during their ingestion. If that page is the answer, their description of your product becomes the description of your product.
And you lose the comparison. A retailer page compares your item against everything else the retailer stocks, on the retailer's terms.
The practical response is supplying retailers with complete, current product data through whatever feed mechanism they support, and checking periodically what they actually published. Feed errors are common and invisible from your side.
Category and Buying Guide Content Is the Available Ground
Brands rarely win the query which product should I buy, because that is a comparison across brands and a brand source is self interested.
What brands can win is the layer beneath. How to choose within this category, what specification actually matters for which use, how to tell whether a given feature is worth paying for. That content is genuinely useful, it demonstrates expertise, and it does not require claiming your product is best.
Seer Interactive's data puts best of queries at an 81.3 percent AI Overview trigger rate. Those answers get built from sources explaining selection criteria, and a brand willing to write honestly about when its own product is not the right choice is an unusually credible source for that.
Discontinued Products Need a Decision
Consumer catalogues turn over constantly and discontinued product pages accumulate. Left live with in stock schema, they misinform. Deleted outright, they break links and lose the accumulated review content.
The reasonable handling: keep the page, update availability in schema to reflect discontinuation, state plainly that the product is discontinued, and link to the current equivalent. That answers the question someone is actually asking when they search for a discontinued product, which is usually what replaced it.
The status code and redirect considerations sit in the status codes guide. Redirecting a discontinued product straight to a category page loses the specific answer and is treated as a soft failure by most crawlers.
Product Variants Create a Duplication Problem
A shirt in eight colours and six sizes can generate forty eight URLs describing what is functionally one product. Left indexable, that is the faceted duplication problem from the canonicalization guide at catalogue scale.
The workable structure is one canonical product page carrying the full specification and review corpus, with variants either handled on that page through selectors that do not change the URL, or given their own URLs carrying a canonical pointing back.
The exception is where a variant has genuine independent demand. A specific colourway people search for by name may warrant its own indexed page. That is a judgement per product rather than a blanket rule, and defaulting to indexing every variant is the more common and more damaging error.
Marketplace Listings Are Not a Substitute for Owned Pages
Some brands conclude that since marketplaces win the queries, the marketplace listing is the real product page and the brand site is marketing. That reasoning is understandable and it concedes something worth keeping.
A marketplace listing exists at the platform's discretion, formatted to their template, alongside competing products, with review content the platform owns. A brand page is the one description of the product the brand fully controls, and it is the source retailers and aggregators draw from when their own data is thin.
The stronger position is treating the brand page as the canonical record: complete specifications, full schema, honest reviews, and current availability. The marketplace listing is a distribution channel fed from it, not a replacement for it.
Checking Who Answers For Your Products
Ask an engine about your own product by name and see which source answers. Then ask a comparison question against a competitor product and see whether you appear at all.
The NotionCue AI Answer Gap Finder shows which sources hold product and comparison queries in your category, which for consumer brands usually reveals a retailer or review site holding ground the brand assumed it owned.
Start your free NotionCue trial and test your three highest revenue products by name. The gap between what your page says and what gets quoted is usually the specification layer.
Open your best selling product page and count how many concrete specifications appear as text rather than in an image or a click to expand tab. If the answer is few, retailers will keep winning queries about your own product.
Common Questions
Should brands sell direct if retailers win the queries anyway?
That is a commercial decision beyond this post. What is clear is that a brand with thin product data loses the query regardless of channel strategy, and fixing the data helps both direct sales and the accuracy of what retailers publish.
Do product images matter for AI visibility?
Less than specifications, and alt text carrying real descriptive detail helps, per the image AEO guide. An image of a specification chart is not a substitute for the specifications as text.
How often should product schema be audited?
Whenever pricing, availability, or specifications change, and quarterly regardless. Feed driven catalogues drift silently and the errors surface as wrong answers rather than error messages.