Why product feeds need an organic strategy for AI search

Ask most ecommerce manufacturers who owns their product feed, and the reply is nearly at all times the identical: the paid media workforce.

Perhaps a feed administration device sits below PPC. Perhaps the purchasing workforce constructed the feed years in the past, and no one’s touched the titles since. Both method, SEO hardly ever has a seat on the desk, and it’s typically forgotten as a part of the broader feed administration technique.

Whether or not you’re frightened about AI search or conventional clicks, you’re lacking out on alternatives by excluding search engine optimisation out of your feed administration technique.

Up to 83% of ChatGPT carousel products match Google Buying’s natural outcomes, in keeping with a current Peec AI research analyzing greater than 43,000 listings. And 60% of these matches got here from Buying positions 1-10.

On Google’s aspect, the Buying Graph now comprises greater than 50 billion product listings and feeds straight into AI Overviews, AI Mode, and Gemini. AI Overviews seem in roughly 14% of purchasing queries, up from about 2% in late 2024. Like many different issues we’ve found about AI search, the generative outcomes are knowledgeable by conventional SERP.

SEO needs to be the strategic quarterback for model authority. This can be a extremely beneficial alternative to work cross-channel towards a standard objective of bettering visibility throughout search surfaces. It actually requires SEOs, commerce, and paid media groups to get in the identical room.

The case for a devoted natural feed

Sometimes, manufacturers run a single product feed optimized for Google paid purchasing campaigns. Titles are written for bid relevance, descriptions are constructed for High quality Rating, and the feed exists to win auctions, with much less consideration for person search behaviors.

As person conduct shifts, search surfaces favor stronger semantic alignment between queries and product knowledge. A title full of paid-friendly modifiers or branded phrases isn’t the identical as a title that mirrors how somebody conversationally searches for a product.

We examined this with a big ecommerce model. Our company’s AI search engine optimisation workforce partnered with the commerce workforce to launch a devoted product feed without spending a dime natural listings, with titles and descriptions optimized particularly for natural visibility, relatively than replicating what was already operating within the paid feed.

After the natural feed was pushed stay:

• Natural itemizing CTR elevated 10% month over month, alongside a 4% elevate in buying charge.
• A product-level take a look at noticed a 92% improve in income without spending a dime listings, with visibility up 83%, and add-to-cart up 14%.
• The natural optimization modifications alone drove 35,000 impressions at a 1.4% CTR, 55% increased than the CTR seen in paid for a similar time interval.

Slightly than changing our paid feed technique, we acknowledged that natural and paid purchasing clear up totally different issues and have totally different wants that require optimizing accordingly.

Natural feed titles ought to mirror how your clients really search, not how your bidding technique is structured.

Dig deeper: How AI-driven shopping discovery changes product page optimization

What to prioritize in an natural feed technique

Not each feed attribute carries equal weight. In the event you’re constructing a devoted natural feed or simply auditing your present feed for gaps, right here’s the place you may begin.

Titles are the highest-impact lever

Google’s algorithm closely favors feed titles when matching merchandise to queries, and its own documentation emphasizes together with necessary attributes to “higher match search queries and drive efficiency elevate.” Take into account how a buyer would possibly describe what they’re on the lookout for in a conversational method, and the way that aligns with product attributes.

World Commerce Merchandise Numbers (GTINs) are non-negotiable

Google’s GTIN documentation makes clear that merchandise with right GTINs obtain considerably extra visibility. Business knowledge has constantly proven that correctly matched merchandise can drive as much as 40% extra clicks. They’re additionally the first sign for aggregating product critiques throughout sources.

Don’t overlook pictures

They’re nonetheless the most typical supply of Service provider Heart disapprovals. Merchandise with each commonplace and way of life pictures sometimes see considerably increased engagement. 

If price range or bandwidth has stored higher product pictures on the again burner, Google’s Product Studio might help deal with a number of the modifying, so you may take a look at and enhance inventive at scale with out a full reshoot. It’s additionally a method for search engine optimisation and inventive groups to collaborate on feed-specific property and testing.

Optimize key product attributes: product_highlight and product_detail 

• product_highlight enables you to add scannable profit statements that seem in expanded Buying views. For example, “waterproof for gentle rain commutes” is doing extra work than “high-quality materials” for each the patron and the AI. 
• product_detail supplies structured specs that energy Google’s faceted filters in natural product grids.

The identical semantic work SEOs are doing to optimize product element pages (PDPs) for conversational search — like defining superb consumers, naming use circumstances, and articulating compatibility — ought to inform feed attributes. 

Product and content material groups already perceive what drives somebody to purchase. That context ought to be within the feed, not simply on a model’s PDPs.

Dig deeper: How to make ecommerce product pages work in an AI-first world

Your feed can also be your agentic commerce basis

Right here’s what makes this funding compound: the feed optimization work carried out immediately for natural purchasing visibility may also assist construct model readiness for agentic commerce requirements and purposes.

Google’s Universal Commerce Protocol, announced in January, is a framework that allows AI brokers to find merchandise, construct carts, and full transactions straight inside AI Mode and Gemini. The patron could by no means land on the model web site to make a purchase order. UCP isn’t a substitute for Google Service provider Heart, as a result of it’s constructed straight on prime of GMC knowledge.

Feeds are how merchandise enter the Buying Graph. The Buying Graph is the dataset AI brokers question when processing a purchasing request. The brand new native_commerce attribute added to feeds is what indicators {that a} product is eligible for the UCP-powered “Purchase” button in conventional and AI-driven Google providers.

Google has additionally introduced the eventual rollout of a number of new Service provider Heart attributes designed particularly for conversational commerce: 

• Product FAQs.
• Use circumstances.
• Appropriate equipment.
• Product substitutes. 

These are additions to an present GMC feed that give AI brokers the contextual understanding they should match merchandise to natural-language queries like “what’s a very good waterproof jacket for bike commuting?” These new conversational attributes are rolling out to a small group of outlets first.

That is the place feed knowledge and on-page content material want to remain tightly aligned. Search surfaces cross-reference a model’s feed in opposition to:

• Structured knowledge. 
• PDP content material.
• Different sources to validate findings. 

When these layers contradict one another, belief erodes on the area degree. 

Dig deeper: 7 organic content investments that drive ecommerce ROI

Constructing a cross-channel technique for AI search

Product feed technique and optimization is a chance for real cross-team collaboration to check, execute, and measure visibility. A holistic method to managing product particulars throughout each floor will profit manufacturers in each conventional and AI-driven search.

• SEOs convey the key phrase intelligence, semantic understanding, and information of how AI techniques match queries to content material. 
• Commerce and market groups personal the product knowledge, product data administration, and relationships with retailers. 
• Paid groups have the feed infrastructure, the instruments, and years of expertise managing feed well being at scale.

These groups should work collectively to coordinate their insights and successfully set up an AI SEO operating system. The product feed sits at that intersection because it’s an owned asset managed by commerce infrastructure that straight feeds AI-powered visibility.

Step one is to drag a present feed and evaluate natural titles to paid titles. The second step is getting the appropriate folks within the room to construct one thing higher. search engine optimisation is most profitable when extra channels align towards the identical objective: higher model visibility.