The product feed has historically been firmly in the domain of PPC teams, and for good reason. After all, for decades, feeds have been the basis for Shopping and the Paid side of this equation is where the biggest spend and revenue sit.<\/p>
For an SEO, it was enough to check Google Search Console Shopping Results, and Bob\u2019s your uncle.<\/p>
Not anymore.<\/p>
Product feeds have (not so) quietly become one of the most structurally important data assets in ecommerce \u2013 for paid, organic, and now agentic. They shape how Google interprets product pages across channels, how discrepancies between different product and category points get resolved, and increasingly, how AI evaluates and surfaces products to users.<\/p>
The feed has outgrown single-team ownership because its surface area has expanded. And, SEO teams have been largely absent from the conversation.<\/p>
The irony is hard to ignore: The industry is obsessing over duplicating our websites in markdown and llm.txt files while neglecting the one asset Google explicitly calls out in their new generative AI search guide as critical for product visibility in AI responses \u2013\u00a0 the Merchant Center (and by extension the feed).<\/p>
This piece is about why that needs to change, what happens when we keep to the status quo, and what it looks like to put it into practice.<\/p>
The Unholy Trinity: 3 Systems, 1 Goal<\/h2>
At last year\u2019s Search Central Live, Google had a running joke about this. You add a standard to unify the standards, only to end up with an even bigger mess.<\/p>
Rather than one unified system for understanding your products, Google is actually managing three distinct layers of data that have different rules, different structure, and, of course, different teams managing them on the organizational end.<\/p>
First, you have the Product Feeds. These are the manual files you push to:<\/p>
- The Google Merchant Center (GMC) contains your core attributes like titles, GTINs, and prices.<\/li>
- The Manufacturer Center containing richer, more detailed product information<\/li> <\/ul>
This is a parallel data structure that exists entirely independently of your website.<\/p>
Next is the on-page structured data. This is most commonly JSON-LD markup tucked away in your code, designed mostly as a point of feed verification but also directly powering some of the ecommerce rich results. And, schema.org is also not the only player in town here. This came up repeatedly at Search Central Live last year, where Google explicitly referenced GS1, UN\/CEFACT, and other ontologies.<\/p>
Finally, there is the Website itself. This is the actual rendered page that a human sees or the machine-readable version that an agent sees, which it verified against the other two sources.<\/p>
The friction comes from the fact that these systems play by different rules and are read differently by humans and machines.<\/p>
Google is well aware that this setup is a headache. Back in 2024, they even discussed the possibility of unifying schema markup and feed data to simplify how merchants provide information. The goal was to move toward a more integrated processing system.<\/p>
Until that unification actually happens, you are stuck managing three separate layers. And, that\u2019s the issue.<\/p>
Time and again, we see brands with feeds in complete disarray with schema that says something completely different and a website that contradicts both. This then forces Google (and agents) to make a judgment call.<\/p>
Usually, that call doesn\u2019t go in your favor.<\/p>
Accuracy across all three isn\u2019t just a \u201cnice to have\u201d anymore; it is the baseline for being discoverable and purchasable. And, a lack of harmony between them can sink your business results.<\/p>
When It All Goes Wrong<\/h2>
Anyone working in ecommerce has seen a long list of issues that arise from this unholy trinity.<\/p>
Some are easier to fix than others because they fall into a shared mental load between the teams. One excellent example of this is feed product titles. Time and time again, PPC managers use SEO-optimized titles to tweak their product feeds using rules or supplemental feeds. They understand that the SEO team has spent hours doing keyword research and tweaking the meta to fit search intent.<\/p>
That kind of informal knowledge-sharing works well when the asset already sits within both teams\u2019 remit.<\/p>
When a PPC manager sees a disapproval spike, their diagnostic instinct naturally goes to feed attributes, quick website check, bid strategy, policy violations \u2026 all within their domain. And, that\u2019s not a failure of skill; it\u2019s a failure of scope. More often than not, they fix what they can see, escalate what they can\u2019t to dev, and SEO never gets the call. Not because the structure failed, but because no single channel team has visibility across all three by default.<\/p>
To illustrate the point, here are two recent examples from my agency of how this plays out in practice.<\/p>
Schema, Feed & Website Misalignment<\/h3>
There are attributes that are nice to have and can help your products perform better on organic and paid listings.<\/p>
For example, let\u2019s say you are an ecommerce shop that also sells striped women\u2019s dresses. On those products, you could use g:pattern in your feed and an equivalent Pattern Schema.org Property within Product schema type. Adding it to both might help you a bit when appearing for searches such as [striped women\u2019s dress]. Or you might appear for those searches anyway. It\u2019s likely that your website or feed\/schema titles have some data on the pattern in the text anyway. Your products definitely won\u2019t get disapproved in the GMC if you skip adding them to the feed or the schema.<\/p>
Price is not one of those nice-to-have fields. It is an essential attribute in your feed, markup in your structured data, and information point on your website.<\/p>
Recently, we have noticed across several ecommerce clients how much Google is cracking down on this. Products being disapproved in GMC left, right, and center because of the mismatch in price between the three layers.<\/p>
One such example is our client working in office furniture, whose products started to be disapproved en masse recently.<\/p>
Products like this one, where the website said \u00a334.80, the price in the main feed was \u00a334.80 GBP, and the Merchant decided the price was \u00a333.54.<\/p>
![\"Google](\"https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/google-merchant-centre-product-listing-screenshot-892.png\" "\\"Why")
GMC product listing screenshot (Image from author, June 2026)<\/figcaption><\/figure> And, when we looked at the schema, we were faced with a 4th price of \u00a329.<\/p>
![\"The](\"https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/json-ld-schema-screenshot-665.png\" "\\"Why")
JSON-LD schema markup screenshot for the same product (Image from author, June 2026)<\/figcaption><\/figure> The schema markup on product pages was outputting the ex-VAT price rather than the inc-VAT final price, along with a priceValidUntil field.<\/p>
Google uses schema to verify and sometimes overwrite feed prices via automatic item updates, which is why the wrong figure was showing in GMC and why all those products ended up on the disapproved list.<\/p>
This is the kind of issue that only surfaces when someone has visibility across both systems.<\/p>
And, this is an easy one to spot! Things get even more complex with fields that don\u2019t have a direct schema equivalent or have different rules.<\/p>
For example, fields such as availability.<\/p>
In a GMC feed, Google accepts four standard values:<\/p>
- In_stock<\/li>
- Out_of_stock<\/li>
- Preorder<\/li>
- Backorder<\/li> <\/ul>
Both preorder and backorder require an availability_date attribute \u2013\u00a0 the expected date the product will ship or be available.<\/p>
On the schema.org side, the equivalent is the availability property on an Offer, which uses a different vocabulary:<\/p>
and so on. If you\u2019re managing these separately \u2013 feed in one team, schema in another \u2013 the chances of a mismatch are high.<\/p>
Navigating the Variant Gap (item_group_id vs ProductGroup) is another example here and likely one of the most complex areas to align. Largely because feeds and structured data handle them through completely different architectures.<\/p>
In a Google Merchant Center feed, product variants are submitted as a flat list, tied together by a shared item_group_id. On-page schema requires complex, nested parent-child relationships using the ProductGroup schema, alongside properties like hasVariant and variesBy.<\/p>
Because an ecommerce site might have a feed that is massively larger than its indexable product pages, variant mapping will break down if the PPC team manages the flat feed while the SEO team builds the nested schema in isolation.<\/p>
Infrastructure Failure<\/h3>
Price mismatches and schema conflicts are frustrating, but at least they\u2019re visible. You can audit them, find the discrepancy, and fix it.<\/p>
An infrastructure failure is different and, in some ways, more alarming because everything in your data can be perfectly aligned, and products will still disappear.<\/p>
![\"GMC](\"https:\/\/cdn.searchenginejournal.com\/wp-content\/uploads\/2026\/05\/disapproved-product-listings-in-google-merchant-centre-654.png\" "\\"Why")
GMC product status chart (Image from author, June 2026)<\/figcaption><\/figure> In one recent case, we saw a client\u2019s products move from approved to not approved at scale almost overnight. The feed was fine. The schema was fine. The website was fine.<\/p>
But a configuration change to the client\u2019s CDN security settings had inadvertently begun blocking Google\u2019s crawler. Bot protection rules, designed to defend the site, were treating Googlebot as a threat. With the website layer inaccessible, Google couldn\u2019t verify it against the feed and schema data it already held, and with that verification broken, products were pulled.<\/p>
While the fix was pretty straightforward, identifying the cause was definitely not. A PPC manager would have seen the disapproval. But, only someone thinking across crawl behavior, feed health, and site infrastructure simultaneously would have found the root cause.<\/p>
SEO Case For Shared Feed Ownership<\/h2>
The old logic was simple: Merchant Center is primarily Paid Shopping, Shopping is PPC, therefore the feed is a PPC problem. This type of thinking is increasingly outdated.<\/p>
Merchant Center handles paid and free listings, feeds impact rich results, the Google Shopping Graph, and now agentic ecommerce. It\u2019s the infrastructure for your entire product presence. But infrastructure is only as good as the data running through it, and right now, too many feeds are riddled with issues.<\/p>
Shared ownership isn\u2019t a redistribution of credit. For PPC teams, it means fewer disapprovals to firefight, cleaner attribute data to optimize against, and a diagnostic partner.<\/p>
SEOs need to be in the room when decisions are made because:<\/p>
Feed Data Is Written For Databases, Not For Searchers<\/strong><\/h3>
When SEOs aren\u2019t involved in feed management, the feed stays as whatever the platform exports. And, that\u2019s not always driven by search behaviors. Way too often, what the various feed plugins spit out are generic titles, approximate categorizations, and thin attributes.<\/p>
This is the failure that doesn\u2019t show up in the Merchant Center.<\/p>
At best, PPC teams are quietly patching this with feed rules or supplemental feeds, both legitimate tools in the right context, with their own optimization logic, but neither designed to compensate for a primary feed that was never built with search intent in mind.<\/p>
The feed is technically healthy, but if not dealt with,\u00a0 it\u2019s also commercially invisible.<\/p>
Treating the feed as a search asset rather than a data asset means front-loading titles with high-intent keywords, refining taxonomy so products aren\u2019t buried under generalized categories, ensuring attribute depth matches how customers actually filter and query, and maintaining the kind of ongoing hygiene that stops ghost products quietly disappearing from results.<\/p>
These are things SEOs do instinctively elsewhere; they just rarely get asked to apply them here.<\/p>
Structured Data Is The Hidden Variable Across Paid, Organic & Free Listings<\/h3>
When our clients\u2019 price mismatch surfaced, my PPC team could see the disapproval. What they couldn\u2019t see was why, because the answer was in the schema, and schema isn\u2019t a PPC domain.<\/p>
The blast radius also doesn\u2019t stop at paid. The same schema error affects free listings, where Google pulls directly from GMCIn a GMC feed, Google accepts four standard values and applies the same validation logic.<\/p>
And it affects organic rich results \u2013 price, availability, review count appearing in standard SERPs \u2013 which are driven by on-page structured data and carry no disapproval mechanism to flag when something is wrong. Incorrect information just surfaces silently.<\/p>
I found this because I was in the room. If SEO isn\u2019t co-owning the feed, there\u2019s no reason anyone ever looks at the schema when paid goes wrong. And, no reason anyone connects the dots to what it\u2019s doing to free listings and organic rich results at the same time.<\/p>
Feed Quality Is Increasingly A Signal, Not Just A Campaign Requirement<\/h3>
Google has been explicit that Merchant Center feed quality affects more than Shopping ad eligibility. The overall health of a Merchant Center account (things like: disapproval rates, missing attribute warnings, policy compliance\u2026) contributes to how Google evaluates a merchant\u2019s trustworthiness as a data source. A feed with widespread attribute gaps or recurring disapprovals is a signal about data quality at scale, affecting eligibility and display across all Google surfaces. The feed is being read as a proxy for how reliable you are as a data source.<\/p>
Google has also formalized this through the Shop Quality program, which evaluates merchants against each other across signals, including approval rates, shipping data completeness, and return policy clarity. Performing well here has a direct, visible impact on listings, with the Top Quality Store badge appearing on placements in both paid and organic results. This makes account health a competitive factor, not just a compliance one.<\/p>
The Shopping Graph layer makes this even more consequential. The Shopping Graph now contains more than 50 billion product listings and feeds directly into AI Overviews, AI Mode, and Gemini. How reliably Google can verify and trust your product data determines your position within that graph.<\/p>
To put it simply, consistency across structured data, landing pages, and Merchant Center feeds is what helps Google trust what it sees, and trust is the difference between an eligible, compelling listing and one that underperforms.<\/p>
The Organic Stakes Are Changing<\/h3>
Organic Shopping has never been invisible to SEOs. We\u2019ve worked on optimizing for organic shopping using strategies such as structured data and on-page elements, and reported on it via Google Search Console. We just didn\u2019t pay much attention to the Merchant Center or the feed. And yet, this is what also powers those results.<\/p>
SERP itself is also quietly restructuring around us.<\/p>
The severity of this shift is brilliantly illustrated by ecommerce SEO expert Brodie Clark, who notes that Google\u2019s search results are increasingly feeling like a product detail page in their own right. Rich results like visual product grids that take up prominent SERP real estate are cannibalizing branded search terms, particularly for brands stocked by major third-party retailers. The issue is compounded on mobile, where they can take up several scrolls before a brand\u2019s own category pages appear at all.<\/p>
This makes the feed an increasingly important data source behind a larger share of the commercial SERP.<\/p>
Agentic Commerce Changes What \u2018Discoverable\u2019 And \u2018Purchasable\u2019 Mean<\/h3>
This is the part that\u2019s easiest to underestimate, and where the stakes of feed neglect shift from significant to structural.<\/p>
Discovery Is No Longer Only Human-Led<\/h3>
AI-powered surfaces like AI Overviews increasingly draw on Merchant Center data to surface products in response to commercial queries. A product with thin feed attributes and minimal structured data starts from a significant disadvantage at the discovery phase. Not just in Shopping, but in the AI layer being built on top of it.<\/p>
This is no longer speculative. Google\u2019s UCP documentation states explicitly that merchants should use their existing GMC account shopping feeds to capture high-intent customers during discovery, with UCP unlocking access to surfaces like AI Mode in Search and Gemini.<\/p>
Google is already extending this further by introducing conversational commerce attributes in Merchant Center, such as compatibility, substitutes, related products, specifically designed to feed AI modes and reduce hallucinations.<\/p>
Purchasability Is A Technical Problem, Not A Content One<\/h3>
Visibility is also only half the problem. If an AI agent then attempts to actually buy that product, it relies on a machine-readable representation of your site \u2013\u00a0the raw HTML, the accessibility tree, and rendered screenshots.<\/p>
The accessibility tree is particularly interesting here. Your tree is a high-fidelity map distilling the page into the roles, names, and states of interactive elements. Non-semantic HTML,\u00a0 i.e., <\/p>
soups where a < button > should be, means your \u201cAdd to Cart\u201d CTA can\u2019t be interpreted or actioned by the agent.<\/p>Layout instability and elements hidden behind overlays compound this even further.<\/p>
The transaction fails before it even starts.<\/p>
The Product Truth Layer<\/h3>
To complicate things further, there is also the Manufacturer Center feed, which has been quietly relevant for years but becomes structurally important in an agentic environment.<\/p>
When an agent evaluates multiple offers for the same product simultaneously, it needs an authoritative source of truth, not just price and availability, but detailed and rich information that sits within the Manufacturer Feed.<\/p>
Gianluca Fiorelli calls this the \u201cProduct Truth\u201d layer, and in an agentic context, that framing has never been more apt.<\/p>
Which brings it back to the unholy trinity. Feed, structured data, website \u2013 as a unified signal environment, not three separate workstreams. And why the SEO skill set, spanning all three, is the one best placed to hold it together.<\/p>
What Shared Ownership Actually Looks Like<\/h2>
We\u2019ve been trying to better align SEO, dev, and PPC teams since all three industries were in their infancy. Easier said than done. And, calling for \u201cshared ownership\u201d in feed management is no different. Implementing this is hard because it requires some structural changes to how most ecommerce marketing teams work.<\/p>
Yet it absolutely needs to happen!<\/p>
While I certainly don\u2019t have all the answers, there are some practical things we could all be doing to make things easier here:<\/p>
Build A Cross-Department Monitoring Layer<\/h3>
The CDN case is a good example of cross-team thinking in practice. The disapprovals were caught, the cause was diagnosed across all three layers, and the client received a clear explanation rather than a vague escalation. That kind of response builds trust in a way that routine reporting never does.<\/p>
But it also prompted us to think about how to make that instinct a process. Stage two for us is an automated monitoring layer. One that alerts on disapproval spikes and routes that signal to SEO and PPC simultaneously, not just whoever happens to be in Merchant Center that morning. The cross-department conversation shouldn\u2019t start after someone notices something is wrong. It should be triggered the moment the data suggests it might be.<\/p>
Combine Health Catch Ups With Regular Cross-Team Feed Reviews<\/h3>
Brooke Osmundson makes the case for adding feed health to regular performance reviews alongside spend, ROAS, and CPA. I strongly agree!<\/p>
And, I would go even further here. Make that your weekly cross-team cadence, but layer on top of it a monthly structured audit that compares feed attribute completeness against on-page structured data and website.<\/p>
Use these reviews to answer questions such as:<\/p>
- Are availability values consistent across all three layers?<\/li>
- Are prices matching?<\/li>
- Are required attributes present in both feed and schema for key product types?<\/li> <\/ul>
That\u2019s where the real gaps surface.<\/p>
A Documented Source Of Truth For Product Data<\/h3>
One of the root causes of feed-to-structured data conflicts is that product data lives in multiple systems, i.e., the CMS, the ERP, the feed management platform, the schema template, and nobody has defined which one is authoritative for which attribute.<\/p>
For most ecommerce teams, the answer is \u201cthe feed wins,\u201d because it\u2019s the most structured and most regularly updated source. Make this explicit and start ensuring schema is generated from or validated against the feed rather than just spat out by a Schema plugin.<\/p>
SEO Involvement In Feed Architecture Decisions<\/h3>
When a development team is setting up a new feed management solution, SEO should be at the table.<\/p>
Not to veto decisions but to ensure that feed attribute choices, the website, and structured data implementation are being made with a shared understanding of how Google reconciles the three.<\/p>
Custom labels are another area worth exploring jointly. Right now, they\u2019re almost always set up by PPC for bidding purposes and left at that. But with five slots available, there\u2019s likely an opportunity to build in labels that serve organic analysis and audit work, too, by search priority, content category, or campaign alignment.<\/p>
What those look like will depend on the catalog and the strategy, but they\u2019re much harder to retrofit once the feed architecture is set. It\u2019s a conversation that needs SEO in it from the start.<\/p>
And, SEOs can\u2019t credibly be at that table without a working understanding of GMC feed attributes, how they map (and where they don\u2019t) to structured data vocabularies, and what mismatches look like in practice. Google\u2019s feed documentation is detailed but readable, and it helpfully cross-references schema markup where a direct equivalent exists. That\u2019s the baseline.<\/p>
Co-owning The Feed Is A No-Brainer<\/h2>
The question was never really whether the product feed is an SEO asset. It clearly is \u2013 for organic, for paid, for free listings, and increasingly for the agentic layer that sits on top of all three.<\/p>
The real question is whether SEO teams are willing to co-own that. Not to take the feed away from PPC, but to bring the systems thinking that the feed has always needed and rarely had.<\/p>
The brands that get this right won\u2019t just have cleaner data. They\u2019ll have a product presence that holds up under conditions that most of their competitors aren\u2019t even thinking about yet.<\/p>
In my opinion, a much more valuable effort than debating whether to duplicate your website in markdown files.<\/p>
More Resources:<\/strong><\/p>
Featured Image: ImageFlow\/Shutterstock<\/em><\/p> <\/div><\/div>
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