What Is Answer Engine Optimization (AEO)?
Answer engine optimization, or AEO, is the work of getting your brand named and cited inside the answer an AI gives, rather than ranked in a list of links. Search engines return ten results. Answer engines return one reply. AEO is how you end up in that reply.
AEO meaning, in one paragraph
An answer engine is any system that reads the web and writes a direct answer: ChatGPT, Gemini, Claude, Perplexity, Microsoft Copilot, and the AI Overviews and AI Mode features inside Google Search. When someone asks one of them "which tool should I use for X", the engine names a few brands, often links to a few pages, and the person acts on that. Answer engine optimization is the set of changes that make your brand one of the names and your page one of the links. It borrows most of its methods from SEO. It measures success differently: not position on a results page, but whether you were mentioned, whether you were cited, and who was named instead of you.
You will also see the spelling "answer engine optimisation" and the near-synonyms GEO and AIO. They describe the same job from slightly different angles, covered in the table below.
AEO vs SEO vs GEO vs AIO
| SEO | AEO | GEO | AIO | |
|---|---|---|---|---|
| Stands for | Search engine optimization | Answer engine optimization | Generative engine optimization | AI optimisation |
| The question it answers | Do we rank for this keyword? | Does the answer name and cite us? | Does the generated text draw on our content? | Umbrella term for AEO and GEO together |
| Where it plays out | Google and Bing results pages | ChatGPT, Gemini, Claude, Perplexity, Copilot, AI Overviews, AI Mode | The same assistants, with a focus on how the text is composed | All of the above |
| Main metric | Position, clicks, impressions | Mention rate, citation rate, share of voice on prompts | Citation rate, how often your wording appears | Mentions, citations, AI Overview impressions |
| Origin | Late 1990s | Voice assistants and featured snippets, then LLM chat | A 2023 academic paper on generative engines | Industry shorthand, 2024 onwards |
In practice the terms overlap almost completely. AEO is the one people search for most, so it is the one this guide uses. For a longer look at the SEO side of the split, read Traditional SEO vs AIO.
Why answer engines changed the job
A results page is a menu. An answer is a decision. When a buyer asks ChatGPT for the best CRM for a ten-person agency and gets four names back, those four names are the shortlist. Everyone else is invisible, no matter how well they rank on Google for "best CRM for agencies".
Google's own documentation describes the mechanism. AI Overviews and AI Mode use what Google calls query fan-out, issuing several related searches behind one question and pulling links from the whole set. Google also says AI Overviews appear only when its systems decide the summary is "additive to classic Search". So the answer is built from more sources than a single results page, shown selectively, and read in place of ten blue links. That is why AI referral traffic can fall while AI usage grows: the click became optional, the mention did not.
What Google actually says you need for AEO
Google's page on AI features in Search, last updated 10 December 2025, is the closest thing to an official rulebook, and it is short. The main points, in Google's words:
- "There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary."
- "You don't need to create new machine readable files, AI text files, or markup to appear in these features."
- "There's also no special schema.org structured data that you need to add."
- A page "must be indexed and eligible to be shown in Google Search with a snippet". Beyond that, the technical requirements are the normal ones, and "indexing and serving isn't guaranteed".
- The content advice is the same as for Search: "creating helpful, reliable, people-first content", keeping important content in text, allowing crawling, and good internal links.
Read that as a relief. Nobody can buy their way into an AI answer with a file or a tag. The things that decide it are what your page says, how clearly it says it, and who else on the web says it about you. The source is Google's AI features and your website.
One caveat. Google's rules cover Google. ChatGPT, Claude, Gemini and Perplexity publish no equivalent guide and send publishers no reports. For those, the only evidence of what works is asking the assistant and reading the answer.
How to do answer engine optimization
Seven steps, in the order that pays back fastest.
- Start from buyer prompts, not keywords. Write down the twenty questions a buyer would type into an assistant when choosing something in your category. "Best X for Y", "X vs Z", "is X worth it", "cheapest X that does Y". These are the prompts you will optimise and measure against.
- Answer in the first paragraph. Open every page with a one or two sentence answer to the question the page exists for. Assistants lift the opening. So do featured snippets.
- Use the question as the heading. An H2 that reads "Does Peec AI track Google AI Mode?" gets quoted. An H2 that reads "Platform coverage" does not. Match the words people use.
- Put the facts in a table. Prices, limits, models covered, who it is for. Engines lift rows from tables because the structure makes attribution easy. One good comparison table outranks three paragraphs of prose.
- Get onto the lists that get cited. Assistants cite ranked listicles and comparison pages far more than homepages. Our own study found AI cites lists, not homepages, and that ChatGPT and Claude do not even read the same lists. Find the roundups the assistants quote for your prompts and earn a place on them.
- Keep pages current and kill the dead ones. Engines prefer fresh, dated content, so old pages go invisible. The reverse problem is worse: retired pages keep telling AI what your company does long after you stopped doing it.
- Do the technical basics. Indexable, crawlable by the AI crawlers you want (check robots.txt and your CDN), text on the page rather than in images, structured data that matches the visible text. Nothing exotic.
How to measure AEO
This is where AEO differs most from SEO. Rankings have had a dashboard for twenty years. Answers have three partial ones.
Google Search Console
Impressions and clicks from AI Overviews and AI Mode are included in the Performance report under the Web search type, and Google has been rolling out a generative AI breakdown by page and country. It covers Google's surfaces only. AI overview tracking is how LLM Scout reads that export next to assistant mentions.
Bing Webmaster Tools
Bing's AI Performance report, first spotted in January 2026, shows citations from Microsoft Copilot and partners: total citations, cited pages by day, and the grounding queries that pulled your page in, labelled by intent. It does not show clicks.
Prompt tracking for the assistants
ChatGPT, Claude, Gemini and Perplexity report nothing to publishers. The only way to know whether they name you is to ask them the buyer prompts from step one, on a schedule, and record who is named, who is cited and who is missing. That is the job of an AI visibility tool, and it is what LLM Scout does. The free AI visibility check runs five of your prompts on ChatGPT every week on a company email, with no card, so you can see your starting point before you change anything.
What to do this week
- Write your twenty buyer prompts.
- Run them through the free check, or by hand in ChatGPT, and note every brand named.
- For each prompt where you are missing, find the page the assistant cited and work out how to be on it.
- Rewrite your three most important pages so the first paragraph answers the prompt and the facts sit in a table.
- Check again in four weeks. Mention rate, not rankings, is the number you report.
Citations are the retrieved layer. What the model already believes is covered in what an LLM remembers about your brand.
