What is answer engine optimization (AEO)?

An answer engine replies in sentences. AEO is the name for the work of showing up in those replies. You'll also see GEO, for generative engine optimization, used for the same thing.

Google's guide to generative AI search describes both as terms for "work specifically focused on improving visibility in AI search experiences." Then it adds its own view: for Google Search, this is still SEO.

So a practical definition has two halves. On Google's account of its own search, AEO rests on the same foundations as SEO. It adds attention to how you appear inside a written answer, in Google and in other tools. The overlap is large enough that the difference between AEO and SEO is mostly one of goal and measurement.

An AI tool can draw on what its model learned in training and on what it retrieves when someone asks. Both matter for this work.

Google's guide describes retrieval in its own search. Its systems pull relevant pages from the Search index and generate a response from them, with links to those pages.

OpenAI keeps the two paths apart in its crawler documentation. OAI-SearchBot surfaces websites in ChatGPT's search features. GPTBot collects content that can be used to train OpenAI's models. A site can allow one and block the other.

The distinction matters because you can't edit what a model has already learned. A page you publish or correct makes new material available to an engine's search, subject to that engine's eligibility conditions. Other engines set their own rules for the steps from a question to a cited page.

Suppose you sell payroll software to restaurants, and your sales team keeps hearing one question: how do we run payroll when servers pool tips? A general article of payroll tips for restaurants wouldn't settle it. The useful answer explains how pooled tips flow into a pay run, works through one example with numbers, and shows how your product handles the split.

That page is the center of the work. Google's guide puts that kind of page ahead of everything else it recommends for generative AI search.

The rest is choosing the right questions and keeping the page reachable. Lean Labs' AEO service page describes building its question set from sales calls and CRM records in HubSpot, the demand Search Console shows, and competitor prompts. It describes writing expert-led answers in HubSpot and connecting them to proof. Starting from sales calls makes sense for the restaurant example, since that's where the tip-pooling question was heard in the first place.

For Google's AI features, the page has to be indexed and able to show a snippet, and the site has to be included in Search generative AI features in Search Console. For ChatGPT, OpenAI says a site that opts out of OAI-SearchBot won't be shown in search answers, though it can still appear as a navigational link.

Google's guide also names tactics its search doesn't need: an llms.txt file, pages broken into small chunks, and copy rewritten in a special style for AI. Structured data isn't required either, though Google still recommends it as part of ordinary SEO.

Those statements cover Google Search only. They also leave the practical setup in place. Your pages still have to be crawlable and easy to keep current, which is where the CMS features that matter for AEO come in.

Those five are different measures, and they don't arrive in a fixed order. An answer can cite your page without recommending you. A sale can follow a recommendation with no tracked visit in between. So the definition covers the work of being found and used, and each outcome gets measured on its own.

On Google, a page that meets every requirement still isn't certain to be crawled, indexed or served.

Since the five can come apart, a careful program reports them separately. Lean Labs describes its reporting in three groups: visibility, which covers mentions, citations and prompt coverage; demand, which covers AI referral traffic and engaged visits; and revenue, which covers contacts, deals and pipeline in HubSpot. For Google's features, Search Console's generative AI performance report counts impressions, meaning the times a link to your site was shown. Visits from other assistants are counted elsewhere, so tracking traffic and referrals from AI answer engines takes more than one tool.

AEO suits a company whose buyers ask questions before they buy, and which has answers of its own to give. The restaurant payroll company has both. A business with nothing to add beyond common knowledge has less to work with, because the page at the center of the work would repeat what's already available. Those two tests are a short version of what kinds of companies benefit most from AEO.

If both are true for you, pick the question your sales team hears most. Record how the assistants your buyers use answer it today, so you have something to compare against after the work starts.