AEO · Answers
Self-contained answers to the most-asked questions about GEO, AEO, llms.txt, AI crawlers and structured data. Each answer is written to be quotable on its own — by ChatGPT, Google AI Overviews, Perplexity, Gemini, Claude and Copilot.
GEO is the practice of structuring a website's content, metadata and crawler access so generative AI engines — ChatGPT, Google AI Overviews, Perplexity, Gemini, Claude, Copilot — include it in their training, retrieval and answer-synthesis pipelines. Unlike classic SEO, the unit of success is a citation inside an AI answer, not a click on a blue link.
AEO is the practice of writing and marking up content so answer engines (Google AI Overviews, Perplexity, ChatGPT Search, Bing Copilot) cite it directly as the answer to a user's question. The core tactics are answerable lead paragraphs, FAQPage and HowTo schema, semantic HTML, and clear entity identification.
SEO optimizes for the ranked list of links on a search results page. GEO optimizes for inclusion in generative AI training and retrieval. AEO optimizes for being quoted as the direct answer on answer engines. All three overlap but reward different on-page work — GEO and AEO weight structured data, llms.txt and answer-shaped paragraphs much more heavily than classic SEO does.
/llms.txt is a markdown file at your site root that gives AI crawlers a curated table of contents — H1 for the site name, a blockquote summary, then ## sections with markdown link lists. It is proposed at llmstxt.org and read by ChatGPT, Perplexity and Claude when they want to skip the JS shell. You should ship one in addition to sitemap.xml; they serve different purposes.
Name each AI bot explicitly with Allow: / — GPTBot, ChatGPT-User, OAI-SearchBot, Google-Extended, Googlebot, Applebot, Applebot-Extended, ClaudeBot, anthropic-ai, PerplexityBot, Perplexity-User, CCBot, cohere-ai, Bytespider, Amazonbot, DuckAssistBot, YouBot, Meta-ExternalAgent, MistralAI-User. Some bots only check their own block, so the wildcard alone is not enough.
For most sites, no. Blocking GPTBot removes you from OpenAI's training and, depending on the bot, from ChatGPT Search retrieval — meaning you cannot be cited as a source. Block only if you have a legal, licensing or compliance reason. The reach lost is almost always larger than the training data withheld.
Allow GPTBot and OAI-SearchBot in robots.txt, publish an /llms.txt, mark up Organization and Article schema with datePublished and author, write answer-shaped lead paragraphs (one sentence definition, one sentence elaboration), and earn citations from authoritative sites. ChatGPT Search retrieves live pages, so freshness and clarity matter more than backlink volume alone.
Allow PerplexityBot and Perplexity-User, ship FAQPage and HowTo JSON-LD, keep paragraphs short and self-contained, and cite authoritative outbound sources — Perplexity favors pages that already look like research. Recent publish dates help; stale pages are demoted in answer synthesis.
Google AI Overviews draws from the same index as Search, with extra weight on FAQPage, HowTo and Product schema, clear E-E-A-T signals (Organization schema, author bios, About page), and content that answers the query in the first paragraph. Allow Google-Extended in robots.txt so your content is also eligible for Gemini surfaces.
Organization and WebSite sitewide; FAQPage on Q&A pages; HowTo on tutorials; Product with AggregateRating and Review on landing pages; Article with datePublished, dateModified and author on blog posts; BreadcrumbList on deep routes; SpeakableSpecification for voice assistants; SoftwareApplication for tools. Keep schema in sync with what is visible on the page — invented reviews get penalized.
Monthly for stable sites, weekly for sites that publish frequently or that just shipped major changes. OptimAIze offers continuous monitoring that diffs scores over time and alerts on regressions.
Yes. Scans are free and require no signup for the basic report. Paid tiers add continuous monitoring, bulk audits, white-label PDF reports and API access. See https://optimaize.app/pricing.
Full playbooks behind the short answers above.
Get a score, a per-pillar breakdown and deploy-ready fix files for any URL — free, no signup required.
Scan a websiteConnected guides to keep going — short reads, all internally linked.
Start with a precise answer, then add the conditions needed to avoid misunderstanding. Name the product, page or policy involved; define ambiguous terms and distinguish a recommendation from a requirement. Keep important limitations near the answer so quoting a short passage does not turn a qualified statement into a guarantee.
A concise summary works best with a concrete example, a verification step and a primary source. For example, publishing llms.txt provides optional curated context; crawl preferences belong in robots.txt, and private content requires authentication. Adding an FAQ does not make a blocked or factually incorrect page citation-ready.
Save the original URL, input, date and evidence before editing. Verify the deployed page or file, document the changes and repeat the same checks. Separate technical validity, correct answer representation and qualified visits; none should be used as a substitute for the others.
| Check | Evidence to retain | Action |
|---|---|---|
| Access | Public status and useful response body | Fix barriers before rewriting |
| Accuracy | Visible facts and supporting primary sources | Correct unsupported statements |
| Markup | Valid syntax that matches the page | Remove invented reviews and properties |
| Outcome | Comparable responses and referral activity | Report observations without guarantees |
Save the page URL, date, language, target market and exact questions before editing. Record what the page actually says and what each tested answer cites; a mention without a source link is not a citation.
Resolve the clearest failure first, then check the published page rather than only an editor preview. Keep an implementation log so unrelated redesigns, campaigns or product changes are not mistaken for the effect of this work.
Repeat the same questions and technical checks after deployment. Keep engines and measurement conditions consistent, report sample size, and inspect answer accuracy alongside citations. A single response is not a stable ranking.