What is generative engine optimization, and how is it different from SEO?

Generative engine optimization (GEO) is the practice of getting your business named and cited inside AI-generated answers, on engines like ChatGPT, Perplexity, Gemini and Google AI Overviews. It overlaps heavily with SEO — both depend on crawlable, credible, well-structured content — but GEO optimizes for being extracted and attributed inside one synthesized answer, rather than for placing a link in a ranked list of ten.

The practical difference

SEO competes for a position in a list. The user then chooses among ten links, and a position lower down still gets clicks. GEO competes to be inside the answer. There is usually one answer, it names a handful of companies, and if you are not among them the buyer never learns you exist. The distribution is far more winner-take-most.

That changes what you optimize.

	Classic SEO	GEO
Unit of success	Ranked position for a keyword	Named or cited inside a generated answer
Page shape	Comprehensive, keyword-targeted	Question-shaped, answer-first, quotable in isolation
Winner distribution	Ten slots, long tail of clicks	A few names, little consolation for eleventh
Where credit accrues	Mostly your own domain	Often third-party pages that mention you
Measurement	Rank tracking, clicks, impressions	Prompt audits: who is named, and which sources were cited
Volatility	Moves over weeks	Can differ between two runs of the same prompt

What carries over from SEO

More than the "SEO is dead" crowd suggests. Engines still need to crawl you, still weigh whether a source looks credible, and still lean on the same signals of structure and authority. Technically sound sites have a real head start: clean markup, fast pages, a sitemap, schema, no crawler blocks.

Two things carry over so directly that they are effectively the same work: structured data (marking up your FAQs, products and specs so a machine reads them unambiguously) and being referenced by other credible sites. In SEO you called the second one link building. In GEO the mention matters even without the link, because the engine is reading the page, not just counting the edge.

What is genuinely new

Extractability beats comprehensiveness. A 3,000-word guide that buries the answer in paragraph nine loses to a 600-word page that answers in sentence one.
Non-determinism. The same prompt run twice can produce different names. A single check is a snapshot, not a measurement — you need a fixed query set re-run on a schedule before any change means anything.
Attribution is the metric. "Were we mentioned" is the vanity number. "Which pages did it pull from" is the actionable one, because those pages are where the work has to happen.
New surface files. llms.txt and explicit AI-crawler directives did not exist in the SEO playbook.

Terminology

You will see GEO, AEO (answer engine optimization), AI SEO, and LLM optimization used for roughly the same activity. There is no settled standard. We say "AI-search content" because the deliverable is content, and because the label matters less than whether the pages get cited.

Why it matters now for industrial B2B

The buyer behaviour moved before most supplier sites did. 73% of B2B buyers now use AI tools in purchase research, and 51% of B2B software buyers now start their research with an AI chatbot. In a market where the buyer self-guides most of the journey before ever contacting a supplier, being absent from that first synthesized answer removes you from the consideration set silently.

Find out who gets named in your niche

The $500 audit runs 15 real buyer queries across ChatGPT, Perplexity, Gemini and Google AI Overviews, logs who gets cited query by query, and comes back with a 90-day content map and two ready-to-publish articles. Fixed scope, two weeks. The fee is credited to your first retainer month if you continue.

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