Generative Engine Optimization: Getting Your Store Into AI Answers

A buyer looking for a cat bowl in 2026 does not always open Google, scroll, compare and click. Increasingly they type the question into an assistant and read one answer with a handful of stores named in it.

So the question worth asking about your own store is blunt: when a buyer asks that way, does your name ever come out?

We measured it. Our agent asked ChatGPT and Perplexity three questions a real pet-supplies shopper would type, recorded every store each engine cited, and then checked how many AI answers anywhere mention our storefront's domain. It took a few minutes and cost about twenty cents. The answer was zero — and the interesting part is who did get named.

Where these numbers come from. The engines were queried through DataForSEO's AI Optimization API rather than by typing into a chat window — ChatGPT and Perplexity, US locale, web search switched on, so each answer reflects what the model retrieves today instead of what it memorised in training. The mention counts come from the same vendor's index of AI answers, and the storefront figures from a live crawl of the page. Every number below is one of those three, pulled on the same August day; ask the same questions next month and the names will differ, because these answers are generated fresh each time.

What the engines actually answer with

Here is the run, as the agent reported it.

Read the two right-hand columns: same three questions, two engines, and almost no overlap between them.

Two things jump out of that table, and they point in opposite directions.

The first is the incumbents. Chewy is named in four of the six answers, PetSmart and Petco in three each. For a broad question like "best online pet supply stores", the engines answer with the same handful of retailers a person would have named from memory.

The second is more useful: the long tail is full of shops nobody has heard of. CozyPaw Wear, PawVortex, Toe Beans, Huron Pet Supply, The Kind Pet, Value Pet Supplies — more than a dozen small independent stores were named across those six answers. "AI only recommends the giants" is a comfortable story, and the data does not support it.

That reframes the problem. The gap between those stores and ours is not scale.

The gap is retrievability, not size

Perplexity's citations gave the mechanism away: its answers were built out of published roundup articles — top10.com, the New York Post, Reviewed.com, Business Insider. It was not ranking stores. It was reading other people's "best of" lists and repeating the names it found there.

That is the core difference between classic SEO and its generative cousin. A search engine ranks your page. A generative engine retrieves sources about you and summarises them. Being excellent and unmentioned is a losing position, because there is nothing to retrieve.

The first row is the whole argument: one number is six figures, the other is zero.

We checked both domains against DataForSEO's index of AI answers — the one that records which domains generative engines actually name. Chewy is cited in roughly 290,000 of them; the store we audited, in none. That is not a ranking difference — it is a presence difference, and it is measured in whether anyone has ever written about you in a document a machine can read.

What the audit found on the store itself

Retrievability is the ceiling. The floor is still your own page, and here the same run was unsparing.

Look at the order: the content problems come before anything technical.

The technical checks were mostly clean — HTTPS, canonical tags, no broken links, a 95 on-page score. What the crawl found instead was an absence of substance: a homepage title that says only the brand name, no meta description at all, 205 words on the page, no structured data, and a catalog whose live products were still Shopify's placeholder items.

The order of that list is the lesson. Nobody's citation problem is a missing favicon. It is that there is nothing on the page for a machine to summarise — no category text, no product detail, no answer to any question a buyer might ask. Every store in those AI answers had the opposite: pages that say plainly what they sell and to whom, and enough of them to be worth quoting.

Which makes the fix order unglamorous but clear. Put real products and real descriptions on the site. Say what you sell in the title and the description — Chewy's homepage title is "Shop pet food, products & supplies at Chewy", not "Chewy". Build the category and guide pages that answer buyer questions in your own words. Then go and get mentioned somewhere a machine will read: the roundups, the comparison articles, the community threads your category already has.

Run the check on your own store

None of this requires a new tool. Ask the assistants your buyers use three or four questions in your category, note every store they name, and see whether you are ever in the list. That measurement takes ten minutes and tells you more than any visibility score.

Running it repeatedly is where it gets tedious, which is what our agent is for. SellerClaw is a team of AI agents connected to the stores you already sell on, plus your suppliers and ad accounts — so "do the assistants recommend me, and if not, why not" is a question you ask in a chat: it puts the questions to the engines, collects who was cited, crawls your storefront, and comes back with the ordered list of what is missing. Everything in this article came out of one such run.

The engines are already answering these questions for your buyers today. It costs nothing to find out what they are saying, and knowing you are absent is the cheapest bad news you will get all quarter.