Answer Engine Optimization: How to Get Your Business Mentioned in AI Answers

Answer engine optimization (AEO) is the work of making your business the one an AI assistant names when someone asks it a question, instead of a competitor. In practice that means four things: being readable by machines, being consistent about your facts everywhere they appear, being cited or mentioned on pages the assistant can actually retrieve, and having a page that answers the real question directly rather than talking around it. Do those four things well and you have a real shot at a mention. Skip them and it does not matter how good your business is, because the assistant never sees you.

None of this is theoretical anymore. A growing share of people who used to type a search into Google now ask ChatGPT, Perplexity, or Gemini for a recommendation, and Google itself now answers a large share of queries directly with an AI Overview instead of ten blue links. If your business is not part of the material those systems draw on, you are simply absent from that conversation. Below is how these systems actually decide who to mention, and what you can do about it.

What an answer engine is, and why it is not just search

A traditional search engine hands you a list of links and lets you do the work of picking one. An answer engine skips that step. It reads across many sources, decides what the honest answer is, and gives you a short, direct response, usually naming two or three specific businesses rather than ten. That is a fundamentally different kind of result. Being link number six on a results page still gets you some traffic. Not being one of the two or three names in an AI answer gets you nothing, because there is no list to scroll past.

How an AI assistant decides who to name

AI assistants pull information from two places, and understanding the difference matters because you have to work on both.

• Training data. Large models are trained on a huge snapshot of the public web, books, and other text, taken up to a point in time. If your business, your reviews, and mentions of you were part of the web when that snapshot was taken, the model may already "know" something about you, in a loose, statistical way. You cannot directly edit this after the fact.
• Live retrieval. Tools like ChatGPT with browsing, Perplexity, and Google's AI Overviews do not rely on training data alone. At the moment someone asks a question, they run a live web search, pull back a handful of pages, read them, and build the answer from what is actually on those pages right now. This is the part you can influence directly, and it is where most of the practical work happens.

Live retrieval works a lot like a very fast, very literal researcher. It fetches pages, extracts facts from them, cross-checks those facts against other pages, and then writes a short answer citing the sources it trusts most. If your page never gets fetched, is confusing when it is fetched, or contradicts what other pages say about you, you get skipped, even if your business is exactly the right answer.

Why traditional SEO is still the foundation

AI assistants and Google both read the same web, using similar tools. A page that is slow, blocked from crawling, or rendered entirely in JavaScript that a crawler cannot execute is invisible to both. There is no separate, easier path for AI visibility that skips the basics. If Google cannot read your site, the AI assistants that also crawl and retrieve from the web generally cannot either. That is worth checking directly rather than assuming, and can AI read your website walks through exactly what these systems see when they try to load your pages, and how to check yours. If your site has never had a proper look at its technical health, what an SEO audit checks covers the ground you want solid before layering AEO on top.

What to do on your own site

A retrieval system rewards pages that answer a question plainly and quickly. That means writing for the assistant the same way you would write for a person who has thirty seconds and no patience for marketing language.

• Answer the actual question in the first sentence or two. If a page is titled "Emergency Plumbing," the first paragraph should say what emergency plumbing is and what you do, not open with a story about your company's founding.
• Use clear, descriptive headings. A model scanning a page for an answer leans heavily on headings to figure out what each section covers. Vague headings like "Our Approach" tell it nothing.
• Put facts in text, not images. Your hours, address, phone number, and pricing need to exist as readable text somewhere on the page. A fact baked into a graphic or a photo of a sign is invisible to a model reading the page as text.
• Keep your business details consistent everywhere. Name, address, phone number, and hours should match exactly across your website, your Google Business Profile, and every directory listing. A model that finds two different addresses for the same business has a reason to trust neither, and often drops you rather than guess.
• Write in plain sentences a model can extract cleanly. "We serve homeowners in Springfield and the surrounding county" is a fact a model can lift and reuse. A page built entirely of vague taglines gives it nothing concrete to cite.

Structured data: stating facts a machine can trust

Schema markup is a way of stating your facts in a format built for machines rather than humans: your business name, address, phone number, hours, services, and reviews, written in a structured block of code rather than left for a model to infer from paragraphs. It does not guarantee a mention, but it removes ambiguity. A model that finds a clean LocalBusiness schema block does not have to guess whether "Riverside Plumbing" and "Riverside Plumbing Co." on two different pages are the same company. Think of it as reducing the model's work, not persuading it. Machines trust facts they do not have to interpret.

Third-party mentions and reviews

Your own site is only part of the picture. Retrieval systems weigh independent sources heavily, because a business describing itself is a less reliable signal than several unrelated sources agreeing on the same facts. Reviews on third-party platforms, mentions in local press, directory listings, and industry publications all give a model corroborating evidence. If the only place your business appears is your own website, you are asking the model to take your word for it, and it often will not. This is also where consistency comes back in: a glowing review that lists your hours or address incorrectly can work against you rather than for you.

A short, practical checklist

1. Confirm your key pages are actually crawlable and load cleanly, not just readable in a browser.
2. Rewrite the opening paragraph of your most important pages to answer the obvious question directly.
3. Add or fix LocalBusiness (or relevant) schema with accurate name, address, phone, hours, and services.
4. Audit your name, address, and phone number across your site, Google Business Profile, and top directories, and fix any mismatches.
5. Make sure core facts (hours, pricing, service area) exist as plain text somewhere on the site, not only in images.
6. Check whether you have recent, visible reviews on at least one or two third-party platforms.
7. Ask an AI assistant a real question a customer would ask, and see who it names.

That last step is the one most businesses skip, because it is hard to do properly by hand: you would need to ask each assistant the actual questions customers use, more than once, and compare who gets named against who does not. We wrote up a 20-minute method for doing it yourself, and our industry pages each quote a real answer for one trade so you can see what you are testing for. The systematic version is what a full audit tests directly, and if you want a lighter first look, the free check flags the basic readability issues that would block a mention before you spend time on anything more advanced.

Be honest with yourself about one thing: nobody, including us, can guarantee a specific mention from ChatGPT, Perplexity, or any AI assistant. These systems change their answers based on the exact wording of the question, the day, and updates to the underlying model. What you can do is remove every reason a model would have to skip you, and give it clean, consistent, citable facts to work with. That materially improves your odds. It does not fix the dice.

FAQ

What is the difference between SEO and answer engine optimization?

SEO is about ranking in a list of links so a person can click through and decide for themselves. Answer engine optimization is about being one of the few names or facts an AI assistant includes directly in its answer, with no list and no click required. AEO depends on SEO fundamentals working first: a page that is not crawlable or readable cannot be optimized for either.

Can I make ChatGPT recommend my business?

You cannot force a specific recommendation, and anyone who claims they can guarantee one is not being straight with you. You can improve your odds by making sure your site is crawlable, your facts are consistent everywhere, your pages answer real questions directly, and you have some independent mentions or reviews for the model to cross-check against.

Does schema markup help with AI search?

It helps by removing ambiguity. Schema does not persuade a model to mention you, but it makes your facts (name, address, hours, services) unambiguous and easy to extract, which reduces the chance a model skips you for being unclear or drops you because your details conflict with another source.

How do I check if AI mentions my business?

Ask ChatGPT, Perplexity, and Gemini the actual questions a customer would ask, such as "best [your service] in [your city]," more than once and with slightly different wording, and note who gets named. A one-off check with a single question is not very reliable, since answers shift. For a systematic version of this, a full audit runs the real questions and shows you the results word for word.