SEO vs AEO vs GEO: How Search Is Changing for B2B SaaS

In a nutshell

SEO gets you ranked. AEO gets you quoted. GEO gets you recommended.

They run on the same engine (good content, clean site, real authority) but they cash out differently. SEO wins a blue link. AEO wins the answer box at the top. GEO wins a sentence inside a ChatGPT or Perplexity response where your competitor's name could have been instead.

For B2B SaaS, the third one is the scary one, because that sentence is often where the buyer forms an opinion about your category before they have ever heard of you.

What is SEO, and is it dead yet?

Search engine optimization is the practice of getting your pages to rank in a list of results on a search engine. Keywords, backlinks, page speed, internal linking, the whole familiar toolkit.

It is not dead. It is just no longer the finish line.

Here is the thing most people miss: every AI answer engine still needs an index to pull from. ChatGPT's browsing leans on Bing's index plus its own crawler. Google's AI Overviews are built on Google's index. Perplexity runs live web searches. If your page cannot be crawled, indexed and understood by a plain old search engine, it cannot be retrieved by a fancy new one either.

SEO stopped being the destination and became the entry fee.

What is AEO (answer engine optimization)?

Answer engine optimization is the practice of structuring your content so it gets pulled directly into an answer surface: a featured snippet, a voice assistant reply, a knowledge panel, a Google AI Overview.

The defining trait of AEO is extraction. Something on your page gets lifted out and shown to a person who may never visit your site. You are optimising to be the source of a specific, contained answer.

Think of it as writing for the friend who interrupts before you finish the question. If your answer takes three paragraphs of throat-clearing to arrive, it doesn't get used.

What is GEO (generative engine optimization)?

Generative engine optimization is the practice of getting AI systems to cite, reference and recommend you inside responses they generate from scratch.

The difference is subtle but it matters. AEO is about a piece of your content being extracted. GEO is about your brand being understood well enough that the model reaches for you when someone asks a broader question, like "what should a Series A team use for revenue reporting?"

There is no ranking position to win. There is only whether the model brings you up or doesn't.

And here is the uncomfortable part for content teams: a lot of what shapes that answer is not on your website at all. Review sites, comparison roundups, Reddit threads, podcast transcripts, industry publications. The model builds a picture of you from everything it has read, and your own blog is only one voice in that pile. Possibly the least trusted one, since you obviously think you're great.

SEO vs AEO vs GEO: what actually changes

The pattern to notice: as you move right, you lose control and gain influence. You control your page. You partly control what gets extracted from it. You barely control what a model says about you, but you can absolutely feed it better raw material.

Wait, are AEO and GEO different things?

The term GEO came out of a 2023 research paper from Princeton and Georgia Tech. A16z popularised it in 2025, and the acronym stuck. Plenty of practitioners pushed back, arguing that "generative" describes the mechanism while "answer" describes what the user actually receives, and that GEO is a terrible name anyway because it already means geography, geology and geo-targeting.

As of early 2026, academic literature still had no agreed definition separating the terms. In practice, most people use them interchangeably.

So use whichever your team prefers, and don't let anyone bill you extra for owning both acronyms. The work underneath is largely the same.

How do you optimise for SEO in 2026?

The fundamentals did not change, but the priorities shifted.

Still non-negotiable:

What matters more now:

How do you optimise for AEO?

AEO is where content structure does a lot of work.

Answer first, elaborate second

Put a direct, complete answer in the first two or three sentences under every heading. Then expand. If a passage cannot stand alone when ripped out of the page, it will not get used.

Write headings as real questions

"How much does X cost" beats "Pricing considerations". Answer engines match questions to questions.

Make FAQs genuinely self-contained

No "as mentioned above". No "as we discussed". Each answer should make sense to someone who has never seen the rest of the page.

Use structured data where it fits

FAQ, Article, HowTo and Product schema help machines parse what a page is and who wrote it. Author, publish date and last-updated fields matter more than people think, because recency is a selection signal.

Keep formatting scannable

Short paragraphs, clear subheads, tables for comparisons, lists for steps. Not because AI loves bullets, but because clean structure makes the boundaries of an idea obvious.

How do you optimise for GEO?

GEO is less about your page and more about your presence.

Be quotable

Write sentences a model can lift without hedging. Definitions, plain numbers, clear positions. Waffle does not get cited because waffle cannot be verified.

Get corroborated elsewhere

If three independent sources describe your product the same way you do, that description becomes fact in the model's eyes. If your site says one thing and G2, Reddit and a review roundup say another, guess which version wins.

This means part of your content budget belongs somewhere other than your blog. Review profiles, guest contributions, partner content, expert quotes in industry publications, community presence. Unglamorous, but it is where the picture of your brand gets built.

Be an entity, not just a website

Consistent company name, consistent category description, consistent founder and product names everywhere. Models resolve entities. If you describe yourself as three different things in three different places, you get confidently miscategorised.

Publish things only you can publish

Original research, real product benchmarks, opinions from your own team, workflows from actual customers. Models reach for sources that add information rather than repeat it.

Stay fresh

Update dates on evergreen pages, and actually update the content underneath them. Stale pages get passed over when something newer says the same thing.

Why B2B SaaS feels this shift harder than everyone else

Three reasons.

Your funnel starts with a research question. SaaS buying begins with "how do teams usually solve this" long before it becomes "which vendor". That early question is exactly the kind AI answers now, and it is where category perception forms.

Your buying committee has grown. Five to ten people are involved, most of them non-experts in your category, and all of them are asking an AI to explain things they'd rather not admit they don't understand. Every one of those conversations is a place you are either mentioned or not.

Your competitors are named out loud. In consumer search, an AI describes options. In B2B software, it lists vendors by name. There is no partial credit. You are in the list or you're the tool someone brings up later in the meeting and nobody recognises.

What Google says about all of this

Worth knowing before your agency sells you a GEO retainer.

In 2026, Google published official documentation on optimising for generative AI features in Search. Its position is blunt: optimising for generative AI search is still SEO. The guide explicitly tells site owners they can skip chunking content into tiny pieces, creating special AI text files like llms.txt, adding AI-specific schema, or rewriting content in some machine-friendly voice. Google's systems can handle multiple topics on a page and surface the relevant part.

You can read it here: Google's AI optimization guide.

Two caveats before you close all your tabs. One, Google is talking about Google. ChatGPT, Perplexity and Claude retrieve differently, and what Google waves off may still matter elsewhere. Two, "it's still SEO" is true about the foundations and less true about the strategy. Winning a citation in a generated answer and winning position three are different outcomes that need different measurement and different content.

Treat llms.txt as a cheap experiment, not a growth plan.

Best practices that work across all three

If you only do a handful of things, do these.

How do you measure something that doesn't send clicks?

This is the genuinely hard part, and anyone who tells you it's solved is selling something.

Keep tracking: rankings, impressions, clicks, conversions. Still the clearest signal you have.

Start tracking:

Mistakes that may kill your search visibility

FAQs

1. What is the difference between SEO, AEO and GEO? SEO optimises for ranking in a list of search results. AEO optimises for being extracted into a direct answer like a featured snippet or Google AI Overview. GEO optimises for being cited or recommended inside responses generated by AI tools like ChatGPT, Claude and Perplexity. SEO wins links, AEO wins answers, GEO wins mentions.
2. Do I need an llms.txt file? Probably not. Google's own documentation says AI text files like llms.txt are not needed for its generative AI features. It is cheap to test, but it should sit far below content quality, site structure and third-party credibility on your priority list.
3. How do I track AI search visibility? Watch for impressions rising while clicks fall, monitor branded search and direct traffic, run monthly manual prompt tests on the questions your buyers actually ask, and add a self-reported attribution field to your demo form.
4. Should I hire a separate GEO agency? Only if they can show you work beyond your own website. If the proposal is "we'll add FAQ schema and some bullet points", that is AEO basics your existing content team can handle.