Answer engine optimization is the practice of structuring a brand's content, technical access and off-site presence so AI answer engines select it as a source and present it as the answer. Where SEO competes for a position in a list of links, AEO competes to be the single response, or one of the few sources cited beneath it — measured in mentions, citations and share of voice, not keyword rankings.
As of 2026, Asva measures AEO by running a fixed set of buyer prompts across ChatGPT, Perplexity, Gemini, Copilot, Google AI Mode, Grok and Meta AI on a recurring schedule, recording whether a brand is mentioned, with what sentiment, and which sources each engine cites instead. For the short course, start with AEO 101.
Answer engine optimization is the work of getting a brand retrieved, trusted and cited by AI answer engines.
An answer engine takes a question in plain language, gathers relevant material, and returns one written answer instead of a page of results. ChatGPT with search, Perplexity, Google's AI Overviews and AI Mode, the Gemini app and Microsoft Copilot all work this way: the model fetches or recalls a handful of sources, decides which passages answer the question, and names some brands while leaving out the rest.
Being in that first group breaks into three parts, best fixed in this order:
Can the engine reach your pages? The right crawlers allowed in robots.txt, content in server-rendered HTML, fast responses, no login walls on pages you want quoted.
Can a model lift a clean, self-contained claim and attribute it to you? Answer-first sections, plain definitions, tables and specific facts make that easy; long preambles make it hard.
Does the rest of the web agree? Engines weight consensus, so if review sites and communities describe you differently from your own site, the model sides with them.
Keyword stuffing and thin question pages do not produce citations: retrieval ranks passages on how well they answer a query, and models cross-check claims against other sources.
SEO competes for a link in a ranked list; AEO competes to be the answer itself, or a source cited under it.
The three terms carry two real distinctions. SEO and AEO differ in what they compete for: a position on a results page versus the answer a model writes. AEO and GEO differ mostly in emphasis — AEO names the outcome (being the answer), while GEO, generative engine optimization, names the mechanism (being cited inside a generated answer). The tactics are almost identical, so most teams run them as one programme; the full mechanics live in the GEO guide.
| SEO | AEO | GEO | |
|---|---|---|---|
| Competes for | A position in a ranked list of links | Being the answer, or one of the few sources under it | Being a cited source inside a generated answer |
| Where the user ends up | On your page, after a click | Reading the answer; a click is optional | Reading the answer; sometimes following a citation |
| Primary signals | Relevance, links, technical health, intent match | Crawler access, extractable passages, entity clarity, corroboration | The same set, with extra weight on citations and freshness |
| Unit of work | The keyword and the page | The prompt and the passage | The prompt and the source |
| Success metric | Rankings, organic clicks | Mention rate, share of voice, position in answer | Citation rate, referral traffic from AI domains |
Answer engines retrieve candidates from a search index — Google's own for AI Overviews and AI Mode, Bing's for Copilot, and their own crawled indexes for ChatGPT search and Perplexity. A page that is not indexed cannot be retrieved. AEO is a layer on that foundation, not a replacement for it.
Answer engines retrieve pages, split them into passages, and cite the ones that answer the question most directly.
An engine knows about you because it retrieved a page while answering, or absorbed a description during training. Retrieved answers move as soon as the engine re-crawls; training-based answers move only when the model is updated. Most consumer engines now retrieve by default for anything factual, current or commercial. The pipeline runs in five steps:
The engine turns the question into one or more search queries. Google AI Mode calls this fan-out: one prompt becomes several sub-queries, each retrieved separately.
Each query runs against the engine's index. Pages that are not indexed, or outranked for that sub-query, never enter the candidate set.
Candidate pages are fetched by an agent such as OAI-SearchBot or PerplexityBot and reduced to text. Content that appears only after JavaScript runs is often missed.
Pages are scored on how directly each passage answers the sub-query. A paragraph that opens with the answer beats one that reaches it after three lines of framing.
The model writes from the top passages and cites the claims it used. Claims several sources agree on are stated confidently; claims only your site makes are softened or dropped.
One split decides whether crawlers help you.
Fetch pages to build indexes or ground live answers. Blocking them removes you from the answers.
OAI-SearchBot — ChatGPT search indexChatGPT-User — fetches when a user asks ChatGPT to read a pagePerplexityBot — Perplexity indexPerplexity-User — user-initiated fetches inside PerplexityClaudeBot — Anthropic's agentGooglebot / Bingbot — feed AI Overviews, AI Mode and CopilotGovern whether content trains future models. Blocking them does not affect whether you are cited today.
GPTBot — OpenAI trainingCCBot — Common Crawl, used by many training setsGoogle-Extended — Gemini training; does not affect AI OverviewsApplebot-Extended — Apple model trainingDecide on the two groups separately. Check your current rules with the robots.txt AI checker.
AEO work runs in a fixed order — fix crawler access first, then measure, then rewrite, then corroborate.
Check robots.txt for every retrieval agent, confirm pages return full content as server-rendered HTML, and remove login walls from pages you want cited.
Tool: robots.txt checker. View a page with JavaScript disabled to see what a crawler sees.
Run thirty to fifty prompts your buyers actually type across ChatGPT, Perplexity, AI Overviews and AI Mode, Gemini and Copilot, and record mention, position, sentiment and the sources cited instead of you.
Tools: Brand Visibility Tracker for the baseline; Citation Intelligence for the sources winning instead of you.
Every prompt worth winning should have exactly one page that answers it in the first hundred words. Consolidate duplicates and retire thin pages.
Lead each section with a self-contained answer, keep one idea per heading, define terms plainly, use tables for "vs" questions, and make claims specific with names, numbers and dates.
Publish JSON-LD for Organization, Article, FAQPage, HowTo and Product where they apply, keep entity data consistent, and add an llms.txt pointing crawlers at the pages worth quoting.
Tools: JSON-LD generator, JSON-LD validator, llms.txt generator, llms.txt validator.
Get the same facts onto the review sites, communities and publications each engine already cites, through earned coverage rather than paid placement.
Earned only. Paid links and directory spam do not build corroboration and can cost you in search. See get cited by AI.
The first pass is a few weeks for a small team; the off-site step and the measurement loop are ongoing. See how SEO and AEO teams structure it.
The method holds across engines; what changes is where they retrieve, how they show citations, and how much freshness counts.
Perplexity is retrieval-first for almost every query, shows numbered sources, and pulls readily from Reddit and forums — so community corroboration matters most here, and it usually reflects a change first. PerplexityBot builds the index; Perplexity-User handles fetches a user triggers directly.
ChatGPT retrieves through its own OAI-SearchBot index and cites inline. ChatGPT-User fetches a page on demand when someone pastes a URL. Neither retrieval agent is affected by a GPTBot block.
Both ride the standard Google index, so the technical work is ordinary SEO. Google-Extended is a training control and has no effect on whether you appear. AI Mode's fan-out can cite a page that answers one narrow sub-question without ranking for the head term.
Gemini grounds answers with Google Search and rewards entity clarity — consistent naming, sameAs links to official profiles and Organization schema.
Copilot retrieves from Bing, where Bing Webmaster Tools and IndexNow give direct control over indexing and freshness.
Platform setup for Shopify, WordPress, Webflow and the rest is in AEO by platform.
Diagnostic tools check access and structure once; a monitoring platform tracks what the engines actually say, on a schedule. The diagnostics below are free and need no account.
Which AI agents your robots.txt allows and blocks, split by retrieval and training.
Build an llms.txt that points AI crawlers at the pages worth quoting.
Check an existing llms.txt for structure and reachable links.
Produce Organization, Article, FAQPage, HowTo and Product schema.
Confirm the schema on a page parses and carries the fields engines read.
Mention rate, position and sentiment across every major engine, over time.
The exact sources each engine cites in your category.
Scheduled prompt runs with alerts when a mention appears, disappears or changes tone.
Separate AI referral traffic from the rest and connect it to conversions.
All four are part of one platform; see pricing or the solutions hub for how teams combine them.
AEO is measured in mentions, citations and share of voice across engines, not in keyword rankings.
Every measure starts from the same input: a fixed prompt set, run on a fixed schedule, across the engines your buyers use. Change the prompt set and the numbers stop being comparable. Report five figures per engine, and track AI referral traffic alongside your organic channel.
How often you are named across the prompt set. Reported per engine, because the engines disagree.
Your mentions against named competitors across the same prompt set.
How often your domain is cited as a source, whether or not you are named in the answer text.
What the engine says about you, and whether it is true. Stale pricing and retired products show up here first.
Where you appear at all: the share of the prompt set that names you.
Sessions from chatgpt.com, perplexity.ai and gemini.google.com, tracked alongside your organic channel. Default analytics under-report it, so separate it deliberately.
The Brand Visibility Tracker runs the schedule; a side-by-side of the platforms that do this is in the best AI visibility tools.
The most expensive AEO mistake is blocking retrieval crawlers with a rule written only for training bots.
A blanket robots.txt disallow removes OAI-SearchBot, PerplexityBot and the rest along with the training crawlers. Split the rules and decide on each group.
Rendering the answer only in the browser hands the fetch agent an empty shell. Server-render the pages you want quoted.
Burying the answer under history or a rhetorical question loses the passage ranking to a page that opens with the claim.
Treating AEO as content-only ignores access, entity data and corroboration, which decide as much as the copy does.
A page can rank first and never be cited, or be cited without ranking. Track mentions and citations directly, per engine.
Stale prices repeat until the underlying sources change. Correct the sources rather than waiting for the model.
AEO stands for answer engine optimization: making a brand's content, technical access and off-site presence easy for AI answer engines such as ChatGPT, Perplexity, Google AI Overviews, Gemini and Copilot to retrieve, trust and present as the answer.
SEO competes for a position in a ranked list of links; AEO competes to be the answer itself, or a source cited under it. SEO is measured in rankings and clicks, AEO in mentions, citations and share of voice. They overlap because most engines retrieve from a web index, so a page that cannot be indexed cannot be cited.
AEO names the outcome — being the answer an engine returns — and GEO (generative engine optimization) names the mechanism — being a cited source inside a generated answer. The tactics are nearly identical, and most teams run them as one programme.
The engine rewrites the question into search queries, fetches candidate pages from its index, splits them into passages, ranks the passages on how directly they answer the query, and attributes claims to the passages it used. Pages win when they are fetchable, answer-first, specific and consistent with other sources.
Run a fixed set of the prompts your buyers ask across each engine on a schedule, and record whether you are mentioned, with what sentiment, and which sources are cited instead of you. Report mention rate, share of voice, citation rate, sentiment and prompt coverage per engine, then connect them to AI referral traffic.
Baseline your mention rate and share of voice across ChatGPT, Perplexity, Google AI Overviews, Gemini and Copilot, and see which sources are cited in your category instead of you.