Do we need a separate GEO agency for ecommerce?

Not usually. The work is product data, review handling and page structure, all of which sit with people you probably already employ. Outside help is most useful for the initial diagnosis and for fixing how third parties describe your catalogue.

Will AI shopping features send us traffic?

Some, and less than the visibility suggests, because these surfaces answer in place. Treat it as the top of the funnel changing shape rather than as a new traffic channel with its own report.

What about marketplaces that already outrank us?

You are unlikely to displace them, and you can make sure the copy of your product they hold is accurate. Being described correctly on a source the model trusts beats being described well on a source it does not read.

For ecommerce

AEO for ecommerce

Shoppers ask assistants which product suits them, not which shop stocks it. That question is answered from specifications, reviews and returns policies, which most stores treat as an afterthought.

The short answer

For ecommerce, answer engine optimisation is product data work more than content work. Assistants answering a shopping question need attributes, sizes, materials, compatibility, delivery and returns terms in text a machine can lift. A store whose product pages carry only marketing copy and a gallery has nothing for the model to quote.

What ranked on 23 September 2026: The scraped results for ecommerce GEO agencies were entirely agency pages and roundups, several quoting monthly retainers from five to twenty-five thousand dollars. Nothing on that page was written for a shopper, which says something about who the category currently serves.

What is different about selling products

Retail has a machine-readable layer that other industries do not: the product feed. It already exists for shopping ads, and it is usually more accurate than the website.

Specifications answer the question. Size, weight, material, compatibility and what is in the box are what a shopper asks and what a model can quote
Reviews carry the caveats a model repeats, including the unflattering ones, so the honest summary of complaints is more useful than a five-star average
Delivery, returns and warranty terms decide purchases and are frequently buried in a policy page that says nothing specific
Marketplaces hold copies of your catalogue that may contradict your own site, and a model reconciling two versions of a spec will often use neither
Seasonal and stock language dates badly: a page promising next-day delivery that is no longer true becomes a quoted mistake

Things that sound right and are not

ClaimOur category pages are optimised, so we are covered.
A category page answers a browsing question. Assistants field comparison questions about individual products, which is a different unit of content entirely.
ClaimSchema markup will fix it.
Product schema helps a machine agree with your page and is worth having. It does not add facts the page never stated, and most stores are missing the facts rather than the markup.
ClaimWe should hide negative reviews.
The complaints exist elsewhere regardless, and a page that acknowledges the trade-off gives a model something specific to attribute to you rather than to a forum.

Where to start

01Take your twenty best-selling products and check whether the page states, in text, what it is made of, what it fits, how long delivery takes and how returns work.
02Reconcile your feed, your site and your marketplace listings. Contradictions between them are the most common reason a model quotes a competitor instead.
03Write an honest summary of what reviewers complain about on each hero product, and answer it on the page.
04Add a short comparison section to your own bestsellers, including the case for the cheaper option.
05Ask five assistants for a recommendation in your category and note which retailer they name and why. The reason is usually a source you can influence.

Questions

Do we need a separate GEO agency for ecommerce?: Not usually. The work is product data, review handling and page structure, all of which sit with people you probably already employ. Outside help is most useful for the initial diagnosis and for fixing how third parties describe your catalogue.
Will AI shopping features send us traffic?: Some, and less than the visibility suggests, because these surfaces answer in place. Treat it as the top of the funnel changing shape rather than as a new traffic channel with its own report.
What about marketplaces that already outrank us?: You are unlikely to displace them, and you can make sure the copy of your product they hold is accurate. Being described correctly on a source the model trusts beats being described well on a source it does not read.

Doing this yourself and want a second opinion on what the assistants say about you? Tell me what you are seeing, or read the AEO Playbook for the whole framework.