Search guide
AEO vs GEO vs SEO: what agencies should actually do
SEO improves a website’s discoverability in search. AEO, or answer engine optimization, usually describes helping content answer questions clearly. GEO, or generative engine optimization, usually describes improving visibility in generated answers. The labels overlap; a useful agency plan names the target surface, the buyer question and the outcome being measured.
Key terms
- SEO (search engine optimization)
- Improving a website so search engines can crawl, index and rank its pages for relevant searches.
- AEO (answer engine optimization)
- Making content answer specific questions clearly enough to be used in direct answers, such as featured snippets, voice answers and AI answers.
- GEO (generative engine optimization)
- Improving how often a brand is mentioned or its pages are cited in answers written by generative AI systems.
- AI visibility
- Whether, and how, a business appears in AI-generated answers to its buyers’ questions: mentioned, cited, recommended or absent.
The short version
SEO improves how a website is crawled, indexed and ranked in search. AEO, or answer engine optimization, usually means making content answer specific questions clearly enough to be used in direct answers. GEO, or generative engine optimization, usually means improving how often a brand is mentioned or its pages are cited in answers written by generative AI systems. The labels overlap, and AI visibility is the outcome all three aim at: whether a business is mentioned, cited, recommended or absent when a buyer asks. An agency should first name the target surface, the buyer question and the outcome it will measure. It should then check that the pages are accessible, answer the buyer’s decision clearly, support claims with real evidence and measure comparable observations. Schema, an llms.txt file or a brand mention cannot guarantee a citation, and no agency can guarantee placement in AI answers.
What is the difference between AEO and GEO?
AEO focuses on giving clear, direct answers to specific questions, while GEO focuses on whether a brand is mentioned or cited inside answers that AI systems generate. Both build on SEO, because pages still need to be accessible, relevant and trustworthy. The table compares the typical focus of each label and the evidence it needs.
| Term | Typical focus | Useful evidence |
|---|---|---|
| SEO | Accessible, relevant pages in organic search. | Indexing, relevant search impressions, clicks and qualified conversions. |
| AEO | Clear answers to specific user questions. | Observed answer appearances, linked source pages and whether visitors complete their task. |
| GEO | Brand mentions and source citations in generated answers. | Dated answers, exact questions, collection context and citation URLs. |
A page can support all three. A service page that clearly explains who it helps, where it operates and how its service works can be useful to a search visitor and to a system generating an answer. That usefulness does not guarantee either ranking or citation.
Google says no extra requirements or special optimizations are needed for AI Overviews or AI Mode beyond its existing search guidance. Read Google’s AI feature documentation.
What should an agency do first?
Start with one buyer task and check that the pages answering it are accessible. Then answer the buyer’s decision clearly, support every claim with real evidence, connect related pages and measure comparable observations. Fix observed defects and buyer confusion before speculative tactics. The six steps below are a workflow, not a ranking formula.
- Choose the buyer task. Name the audience, service, decision and location where relevant. “Improve AI visibility” is too broad to define a useful page or measurement plan.
- Check access. Confirm that important pages return usable public HTML and are not accidentally excluded by indexing directives, authentication or hosting rules.
- Answer the decision. Explain suitability, limitations, process, costs where known and next steps. Make the answer easy for the reader to find.
- Support the claims. Use real service details, first-hand evidence and primary references. Label estimates and demos. Remove unsupported performance promises.
- Connect related pages. Link a product page to its methodology and a guide to the relevant next step. Each page should have a distinct purpose.
- Measure comparable observations. Record the question set and collection method. Monitor search traffic and useful actions separately from sampled AI mentions.
How should content answer a question?
State the answer near the heading, then explain the conditions and evidence. Use a comparison table when a buyer is choosing between approaches. Use steps when the reader needs to perform a task. Do not force every answer into an arbitrary word count or repeat the same paragraph across dozens of pages.
What counts as original substance?
Original substance is information a reader cannot easily get elsewhere. It can be a documented process, a clearly reasoned comparison, a useful worksheet or first-hand observations. If you publish measurements, disclose what you sampled and how. Rewriting existing articles with extra keywords does not add the missing evidence.
Which crawlers matter for AI search?
The crawlers to check first are the search crawlers behind AI answers, such as Googlebot, Bingbot, OAI-SearchBot, Claude-SearchBot and PerplexityBot. Search access and model-training access are separate decisions. For ChatGPT search, OpenAI points to OAI-SearchBot; GPTBot is associated with potential model training. Allowing one does not require allowing the other. See OpenAI’s crawler roles.
Perplexity identifies PerplexityBot as a search crawler and publishes IP ranges for verification. Its documentation advises checking both robots rules and firewall access. See Perplexity’s access guidance.
A robots rule is only one layer. Your host may still return a challenge, denial or empty response. Ask the technical team to verify actual responses and legitimate crawler requests; do not disable site security broadly to accommodate a user-agent string.
Step-by-step checks: how to check AI crawler access. Short explainers: what is AEO and what is GEO.
Common questions about AEO and GEO
What is answer engine optimization (AEO)?
Answer engine optimization is the practice of making content answer specific questions clearly enough that search features and AI assistants can use it as a direct answer. In practice it means question-led headings, a short answer near each heading, accurate facts and structured data that matches the visible page.
What is generative engine optimization (GEO)?
Generative engine optimization is work aimed at being mentioned or cited in answers that AI systems such as ChatGPT, Gemini, Perplexity and Claude generate. It relies on the same foundations as SEO: crawlable pages, clear entity facts, evidence and primary sources, plus measuring which buyer questions actually produce a mention.
What is AI visibility?
AI visibility describes whether, and how, a business appears in AI-generated answers to its buyers’ questions. It is measured per question, engine and date as a mention, a citation, a recommendation or absence. It is a sampled observation, not a single score that covers every buyer or every conversation.
How can a business get cited by ChatGPT?
No one can guarantee a citation, but a business can remove the obstacles. Let OAI-SearchBot crawl the pages that matter, keep them indexable, answer buyer questions plainly near the top, state verifiable business facts and support claims with evidence. Then sample real buyer questions over time and record which page, if any, is cited.
How do you check whether AI crawlers can reach a site?
Read the robots.txt rules for each crawler by name, then request important pages and confirm they return full HTML rather than a challenge, error or empty shell. Check firewall and bot-management settings too, and verify real crawler traffic in server or CDN logs, because a spoofed user-agent test does not prove access.
Which tools track AI visibility?
Tracking needs a fixed question set, a record of which surface answered, and dated evidence of mentions and citations. Teams use manual sampling in the consumer apps, engine APIs and AI Overview data from search-result providers. Whatever the tool, check that it discloses its collection method and keeps failed collections separate from absent mentions.
Does schema guarantee an AI citation?
No. Structured data can describe the content of a page, but it is not proof of authority or a promise of a search appearance. Mark up real visible facts, keep the markup identical to what the page shows, and choose types that describe the page. Read Google’s structured data introduction.
Do you need an llms.txt file?
No, not for Google. Google does not require AI text files for its search AI features. An llms.txt file is an optional index for other tools; it should not be treated as a proven citation tactic or a substitute for accessible, indexable pages with clear answers. See Google’s requirements.
Can a brand mention prove commercial success?
No. A mention shows that a brand appeared in an observed answer, on one surface, at one time. Revenue requires separate evidence. Connect visibility work to referral visits, qualified inquiries and customer outcomes when you can measure them, and disclose gaps in attribution.
Can you guarantee placement in AI answers?
No. An agency can improve page quality, correct defects and measure sampled results. It does not control what a provider generates, and answers can change between requests. A report should separate shipped work, observed movement and hypotheses about why that movement happened.
Where does Xaeo fit?
Xaeo is building white-label AI visibility fix reports for SEO agencies: buyer questions, observed answers, prioritized fixes and follow-up reporting. The current public experience is an illustrative demo. Beta opens November 2026. Read the methodology or use the agency reporting guide.