Insights · Practical guide · July 2026

SEO vs AEO vs GEO: What's Actually Different, and What Overlaps

SEO, AEO and GEO describe closely related work. Here’s what each term means, where they overlap, and how to choose what to improve first.

Fabian Cid

Founder, Shifter

July 16, 2026
Updated September 2026
10 min read

The 10-second version

Take one buyer, three moments. They search “best project management software for agencies”: SEO decides whether your page is in the results they scroll. They ask “what features should agency PM software have?”: AEO decides whether your content is the answer that gets quoted. They ask an AI “which tool should a 20-person agency choose?”: GEO decides whether your brand is one of the names in the answer.

SEO gets you found. AEO makes you the answer. GEO gets you recommended by AI. More buying decisions now start with a question to an AI instead of a scroll through results.

One good page can win all three. A fast, crawlable comparison page can rank for a high-intent search, hand the answer box its quote, and give an AI the evidence it needs to put you on a shortlist.

SEO: get found by buyers already looking

SEO makes your pages easy to find when someone searches for what you sell. The work is unglamorous: pages that load and crawl cleanly, structure that makes sense, content that answers the query, links that carry authority. The job is not “more traffic.” The job is putting your best page in front of a buyer who already wants what is on it.

This is still the base layer for Google's AI features. In its official generative AI optimization guide, Google is blunt: the existing SEO playbook still applies, and optimizing for AI Overviews and AI Mode is treated as SEO, full stop. If your page can’t be found in Search, no AI feature on Google can use it.

Example

The ops lead at a 20-person agency searches “best project management software for agencies,” finds your comparison page on the first page of results, and clicks through to check pricing.

Measure

Qualified impressions, clicks and demos by landing page, not rank alone.

Tactics

• Make important pages crawlable, indexable, fast, and internally linked.
• Match high-intent questions with useful, differentiated pages.
• Use clear titles, headings, descriptive links, and accurate metadata.

AEO: stop burying your answers

AEO comes down to one editorial habit: when a buyer asks a question you can answer, state the answer first and prove it after. Not on paragraph eight, after the scene-setting. Machines extract answers the way impatient readers do, so the same habit that wins featured snippets makes your pages easy for assistants to quote and cite.

It is not a schema trick. Structured data helps Google understand your page and can earn rich results, but the markup has to describe what is visible on the page. And you can format a passage perfectly and still lose: Google decides whether a page becomes a featured snippet. You cannot mark your own page as the winner.

Example

The same buyer asks “what features should agency PM software have?” Google’s answer box or an AI assistant quotes the checklist from your guide, with a link to the full page.

Measure

Whether your passage is the one quoted, whether it is quoted accurately, and the visits that follow.

Tactics

• Put the direct answer near the relevant heading, then add context and proof.
• Use stable terminology, descriptive tables, lists, FAQs, and semantic structure.
• Add accurate structured data where it represents content users can see.

GEO: get named inside the answer

GEO is about what happens inside the answer itself. An AI response is not a list of links; it is one explanation or shortlist stitched together from a handful of retrieved sources. Three things matter to you: whether your name comes up when buyers ask about your category, what the answer claims about you, and whose content the engine is leaning on when it says it.

The 2023 GEO research paper gave the discipline its name and a way to measure source visibility in generated responses. Worth reading, but keep it in proportion: it studies how sources get represented, not how to make a model endorse you.

One technical detail matters here. OpenAI’s crawler documentation separates OAI-SearchBot, which powers ChatGPT Search, from GPTBot, which collects training data. Blocking GPTBot keeps your content out of training. Blocking OAI-SearchBot keeps your pages out of ChatGPT Search answers. Check which one your robots.txt blocks.

Example

Ready to choose, the buyer asks ChatGPT “which tool should a 20-person agency choose?” and gets a three-tool shortlist built from product pages, reviews and comparison articles.

Measure

Re-run the same buyer prompts on a schedule. Record whether you are named, where you appear, how you are described and which sources are cited.

Tactics

• Close factual inconsistencies across owned pages, profiles, reviews, and listings.
• Create first-hand evidence and earn legitimate third-party coverage where buyers research.
• Keep useful pages accessible to the search crawlers relevant to each platform.

A field example: one recorded AI answer

In July 2026 we checked how AI answers treated one AI SDR company: 10 buyer questions across ChatGPT, Perplexity and Google, 30 checks in total. One question we asked ChatGPT was “Which AI SDR should I use for outbound?” It recommended 11x, Artisan, Regie.ai, AiSDR, Apollo.io, Outreach and Instantly, linked to their websites, and left the company out.

That answer tells you where to look next. Put the recommended tools’ product pages next to the company’s own and check what theirs make obvious that its pages don’t: who the product is for, how it works, and the proof behind it. One answer can’t tell you why ChatGPT chose those tools, so you make the fixes and re-run the same question.

Where they overlap, and why the name wars don't matter

SEO, AEO, and GEO are overlapping outcomes, not mutually exclusive channels.

All three run on the same inputs: content worth citing, structure a machine can parse, evidence a skeptic would accept, and a story that stays consistent across the web. The newer acronyms earn their place only when they change what you do on Monday. Write answers that stand alone. Track citations across a fixed prompt set. Audit how AI describes your brand, not just where your page ranks.

People will keep arguing about the names. Google says it is all still SEO. Vendors will sell you AEO, GEO, LLM SEO, and AI visibility, sometimes as four different retainers for the same work. Skip the debate. What matters is whether the work has a clear target, a baseline, and a way to prove movement.

You can’t choose which sources an AI reads. You can make yours the best one it finds.

That means clearer answers, stronger evidence and open technical access on the pages you control. Then check whether the answers change.

What should a B2B SaaS team prioritize?

Prioritize the bottleneck closest to revenue, not the acronym with the most momentum. For most B2B SaaS companies the order is: foundation, then answer clarity, then source coverage. You can run pieces in parallel, but skip the foundation and every later diagnosis gets harder.

1. If high-intent pages cannot be found, start with SEO. Fix crawlability, architecture, query-to-page fit, proof, and conversion paths. You need strong source material before you optimize how other systems reuse it.
2. If you rank but your explanation is vague, add AEO discipline. Rewrite definitions, comparisons, implementation answers, and FAQs so the useful passage is explicit, qualified, and supported.
3. If competitors dominate generated shortlists, investigate GEO. Run buyer prompts, compare recurring names and citations, then close the most credible owned and third-party source gaps.

If external help makes sense, compare specialists by method rather than acronym. Our guide to AEO and GEO agencies lays out the questions I would ask any provider, including Shifter. For ongoing work, Shifter’s plans cover the content, links and AI answer tracking in one monthly service.

Your first 30 days

You do not need a new department. You need one controlled baseline, a small set of commercially important pages, and evidence that the work changed something buyers can see.

1. Days 1–7: define the buyer-question set. Collect 20–30 questions from sales calls, search data, customer interviews, and comparison behavior. Separate informational questions from active-evaluation prompts.
2. Days 8–14: establish the baseline. Record organic visibility and run each priority prompt across the relevant answer engines in clean sessions. Log mentions, citations, competitors, wording, and source domains.
3. Days 15–21: fix the highest-impact sources. Improve two or three owned pages with direct answers, first-hand proof, clear entity facts, internal links, and accurate markup. Resolve crawler blocks and obvious profile inconsistencies.
4. Days 22–30: close one external evidence gap and re-run. Earn or improve a legitimate presence on a source buyers already trust, then repeat the same prompts. Report movement, non-movement, and the next hypothesis—not a victory lap from one favorable answer.

Keep the prompt set stable so your results stay comparable, and revisit it when buyer language shifts. The rhythm matters more than any one-off audit: observe, fix the most suspect source, re-run, and tie the result back to qualified demand.

FAQ

Is AEO or GEO replacing SEO?

No. If your pages cannot be found and crawled, there is nothing for an answer engine to quote or cite. SEO builds the supply of pages worth using. AEO and GEO are additional outcomes you earn on top of that foundation, not replacements for it.

What is the simplest difference between SEO, AEO, and GEO?

SEO gets you found. AEO makes you the answer. GEO gets you recommended by AI. The three overlap heavily, so treat them as outcomes to aim for rather than three separate channels to buy.

Does structured data guarantee an answer-engine citation?

No. Structured data helps machines understand your page and can make it eligible for rich results, but no markup guarantees a ranking, featured snippet, citation, or recommendation. The markup must also describe content that is visible on the page.

Can a company guarantee GEO results?

Not the answer itself: nobody controls which business an AI platform recommends. Treat a promised AI placement as a red flag when it comes without a stated measure, a baseline and a written remedy. What an agency can commit to is the work, how the result will be measured, and what happens if a target is missed.

What should a B2B SaaS team prioritize first?

Foundations first: make sure high-intent pages can be found and crawled. Then make your key answers explicit on those pages. Then close the gaps in the third-party sources AI answers lean on. Measure all three against qualified pipeline, not screenshots of one good answer.

Primary sources

Every technical boundary in this guide traces back to these documents. Read them before anyone's hack thread: they are where “eligible” gets separated from “selected,” and where search crawling gets distinguished from model training.

• Google: Optimizing your website for generative AI features on Google Search Google's current position on SEO, AI Overviews, AI Mode, technical access, content quality, and unsupported hacks.
• Google Search Essentials Core eligibility rules, spam policies and people-first best practices.
• Google: Featured snippets and your website Google systems select featured snippets; publishers cannot mark a page as one.
• Google: Introduction to structured data markup Structured data provides explicit clues and may enable rich-result eligibility when it matches the page.
• OpenAI: ChatGPT Search How citations and sources appear in ChatGPT Search answers.
• OpenAI: Overview of OpenAI crawlers The independent roles of OAI-SearchBot, GPTBot, and ChatGPT-User.
• Aggarwal et al.: GEO: Generative Engine Optimization The original framework and benchmark for source visibility in generative-engine responses.

The conclusion is more boring than the acronyms suggest: build something worth finding, say the answer plainly, and keep your evidence consistent everywhere a buyer or a machine might look. Then ask the same questions again and see what changed. Browse more Shifter Insights for the detail behind that work.

Updated September 2026. The July version of this guide reported 7 appearances in 30 checks. Six came from questions that named the company and one from an organic result below the AI Overview, so it was never a recommendation rate. The research note has the method.