How to Get Your Brand Into AI Recommendations

The question in the title is asked in a slightly hopeful way, as though there is a form to fill in. There isn't. But the mechanism is less mysterious than the GEO industry makes it sound, and once you see it, the list of things you can do gets short and a bit boring.

What is happening when an engine recommends anybody

Someone types "best tools for X" into a grounded assistant. The assistant does not consult an internal ranking of brands. It runs one or more searches, retrieves a small number of pages, reads them, and writes a summary of what those pages collectively say. Then it lists the names that appeared, usually with the descriptions those pages used.

So being recommended is a chain with three links: a page that mentions you exists, that page is in the retrieval set for the question, and the mention is clear enough to survive being summarised. Break any link and you are not in the answer.

This is also why the answer changes when you re-run it. The retrieval moves. I have watched the same question return a different mix of names on consecutive days. Anybody promising you a stable position is describing a system that does not behave that way.

Lever one: be readable

The floor. If an engine's crawler can't fetch your pages, or your homepage is a single line of marketing over a JavaScript bundle, you are excluded from direct retrieval and every mention of you has to be second-hand.

Concretely: let the AI crawlers in (GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot are the ones worth naming in robots.txt), serve real HTML for your important pages, put a plain sentence saying what your product is and who it is for somewhere a machine can find in the first paragraph, and keep your pricing public. Structured data and an llms.txt file are worth adding and are not worth agonising over. Our free readiness checker runs this set of checks; there is nothing magic in it and you can do most of it by hand.

The reason this is lever one and not the main event: it removes a reason to exclude you. It does not create a reason to include you. A large amount of GEO advice consists entirely of this lever, which is why so many people do all of it and see no change.

Lever two: be described by other people

This is the actual work, and it is where the ranked-list format earns its reputation. In the one sample we have published — 23 URLs cited by Perplexity across six buying questions in mid-2026 — seven were ranked lists and fourteen sat on a vendor's own domain. Ranked lists are a tiny share of the web and about a third of what got cited. They are dense with exactly what an answer needs: several named options, each with a short description and a use case.

So the highest-yield move is usually getting your name into the specific lists your category's engines retrieve. Not lists in general. The ones that get cited, which you find by running the questions and counting the hosts. The mechanics of landing them are in how to get added to a best-tools listicle.

The fourteen-vendor-pages finding matters too, and it surprised me. Half the cited vendor pages were ordinary blog posts and feature pages on small tools with no authority to speak of. Engines are willing to quote a small vendor describing itself. That makes publishing the page that answers a buying question directly a cheaper first move than most people assume.

Lever three: be described consistently

Models compress. When five pages describe you five different ways, the summary that comes out is vague, and vague names lose to specific ones in a list of options. When those five pages all say roughly "the cheap AI-visibility tracker for solo consultants", that phrase is what gets repeated.

This is a positioning problem wearing a technical hat. Pick the sentence, use it on your own site, put it in every pitch you send to a list owner, and use it in your own writing. Fight for it in the twelve words next to your name in someone else's article, which matters more than the link attached to it.

Lever four: be the answer to a specific question

The category-level question ("best X tools") is contested by everybody and usually returns the same four incumbents. The narrow question ("how do I see which listicles ChatGPT cites for a niche B2B category") has almost nobody answering it well, and the person asking it is much closer to buying.

Long-tail answer pages are the only part of this that resembles ordinary content marketing, with one difference: you are writing for retrieval rather than ranking, which means being blunt and answering in the first paragraph instead of building to it. Engines quote the paragraph that answers the question. If your answer arrives in paragraph nine after some throat-clearing about how the industry is changing, it gets skipped.

The order, and what usually goes wrong

Readable, described, consistent, specific. In that order, but with a measurement step in front of all of it, because which lever is binding depends on your category. If five hosts supply half your category's answers, lever two is nearly everything and the rest is rounding. If citations are spread across forty hosts with no gatekeepers, lever four is where the wins are and pitching lists is a poor use of a month.

The common failure is doing lever one thoroughly, seeing nothing change, and concluding the whole thing is hype. Schema and crawler access and an llms.txt file cannot cause an engine to retrieve you. They only make sure that when something does cause it, you're legible.

If you want the longer version of the underlying mechanism, the GEO pillar guide covers it, and how AI engines choose brands to recommend goes deeper on corroboration. To see where you stand right now, the visibility checker answers "does it name me" and the citation source radar answers the more useful follow-up, which is who it is naming instead.