How to Get Your Brand Cited by AI: The AEO Playbook

Five years ago the whole game was ranking on the first page of Google. Today a growing share of buyers never see a page of blue links. They ask ChatGPT, Perplexity, or Google’s AI Overviews a question and act on the answer they get back. If your brand is in that answer, you win the customer. If it isn’t, you are invisible, and you usually don’t even know it.

Getting into those answers is the discipline now called answer engine optimization (AEO), or generative engine optimization (GEO). It is what I work on every day at Geonimo, where I measure and improve how brands show up in AI search. This is the playbook, the version I wish more founders understood before they spend a quarter optimizing the wrong thing.

What is answer engine optimization?

Answer engine optimization is the practice of getting your brand cited inside the answers AI assistants generate. AEO and GEO describe the same thing; I prefer “answer” because it is narrower and more honest about the goal: be the answer, not just a result.

The single most important thing to understand is how those answers are built. When you ask ChatGPT “what’s the best tool for X,” it usually isn’t reciting something it memorized in training. It runs a search, retrieves a set of sources, and summarizes them. Engineers call this retrieval-augmented generation, or RAG. That distinction is the whole game: you are not trying to change the model’s weights, you are trying to influence what it retrieves and how often you appear in it. That layer is live, which is why a brand can go from invisible to cited in weeks rather than waiting for the next training run.

Why AEO isn’t the same game as SEO

Everything that works in SEO still helps in AEO, strong pages, topical authority, real links. But two things change, and they change your strategy completely.

The head is different: mentions beat rank

In Google, if your link is the #1 blue link, you win the click. In an AI answer there is no single winner, because the model is blending many citations into one response. The brand that gets mentioned across the most sources tends to lead the answer. So the objective shifts from “rank my one page first” to “be present in as many of the cited sources as possible.” That is a different muscle, and it is why ranking #1 in Google no longer guarantees you show up: studies have found only around 35% of ChatGPT citations overlap with Google’s top results.

The tail is different: longer questions, faster wins

People type roughly six words into Google. Into a chatbot they type around twenty-five, then ask follow-ups. That means a far larger universe of specific, never-before-asked questions, the kind no one ever built a landing page for. New and niche brands can win those immediately, because being cited doesn’t require years of domain authority. A company that launched last month can be the answer to a precise question tomorrow if the right source mentions it.

The two halves of AEO: your site and everywhere else

Split the work into on-site and off-site. Most teams over-invest in the first and ignore the second, which is backwards.

On-site is traditional SEO plus answering the long tail of specific product questions: use cases, integrations, comparisons, “does it do X.” Your help center matters more than you think here, because that is where the precise, high-intent questions get answered. The rule is simple: the more of the real follow-up questions a page answers, the more likely it is to be cited.

Off-site is the bigger lever, and it is where the citations actually come from. The catch: each engine pulls from different places.

Where AI actually pulls its citations

Treating “AI search” as one channel is the most common mistake. Ahrefs looked at the top 50 most-cited domains across Google AI Overviews, ChatGPT, and Perplexity and found only seven appeared on all three, about 14% overlap. Each engine has its own taste:

• ChatGPT leans on publishers and high-authority media: Reddit, Wikipedia, Forbes, Business Insider, plus licensed outlets. The median domain rating of its top cited pages is around 90.
• Google AI Overviews favor established, authoritative sources and Google’s own properties, YouTube alone is roughly 5.6% of citations, alongside Reddit.
• Perplexity is the closest to classic Google; a large share of its citations come from pages already ranking in Google’s top 10, so existing SEO carries over best here.

The practical takeaway: don’t optimize for “AI” in the abstract. Decide which engines matter for your audience, then earn the kinds of citations each one trusts.

The off-site playbook: how to get mentioned more

If this systems-first mindset feels familiar, it is the same one I bring to outbound: build the engine once, then let it compound. Inbound AI visibility and outbound automation are two sides of the same pipeline.

Don’t trust best practices. Run experiments.

AEO is full of confident advice that nobody tested. The honest answer to “does this tactic work” is: measure it. Take a set of target questions, hold half as a control, intervene on the other half, wait a couple of weeks, and compare. Keep what moves your share of voice and drop what doesn’t, then reproduce it before you believe it. This is the discipline most teams skip, and it is the difference between an opinion and a result. I go deep on the mechanics in how to measure AI search visibility.

Is AEO traffic even worth it?

Yes, and it punches above its volume. The channel is smaller than search today but growing fast, and the visitors convert. Graphite reported that Webflow saw roughly 6x higher conversion from LLM traffic than from Google search, and that AI answers drove about 8% of signups. The reason is intent: by the time someone arrives from a multi-turn conversation, they’ve already narrowed the decision and they trust the recommendation.

One more thing, borrowed from a truth every growth leader eventually accepts: it is not your choice whether to play this game. Your brand is being summarized by these models whether you optimize or not. The only choice is whether you show up, or your competitor does.

This is the work I do at Geonimo: measuring share of voice across AI engines and turning it into a plan to get cited more. See the rest of what I’ve built and the stack I use to ship it.