What's the difference between SEO and GEO?

SEO aims to get found on a search engine (appearing in Google's list of links). GEO (Generative Engine Optimization) aims to get cited in the answer written by an AI — ChatGPT, Perplexity, Claude, or Google's AI Overviews. In one case you want a click; in the other you want to be the source of the answer.

Why is GEO becoming important?

More and more people are asking their questions directly to an AI instead of searching Google. If the AI doesn't cite you in its answer, you don't exist for that user — even if you rank well on Google. Being the cited source is becoming a channel in its own right.

How do you get cited by AI?

The key habits: clear question-and-answer structure, factual and 'citable' statements, structured data (schema.org, FAQPage), a consistent and identifiable entity (who's speaking, their authority), and files like llms.txt that expose your content to models. In short: clear, sourced, well-marked-up content.

Is GEO an exact science?

No, it's an emerging field and the mechanics of generative engines are opaque and changing. There's no guaranteed recipe: you apply solid principles (clarity, structure, authority, markup) that largely overlap with good SEO, and you observe.

Getting found by AI: GEO explained (and how to get cited)

1. SEO vs GEO: what's the difference

SEO (search engine optimization) tries to get you into the list of links on a search engine — the goal is a click to your site. GEO (Generative Engine Optimization) aims at something different: being the source the AI cites when it writes its answer. Not a click on a list — a mention in the generated text.

SEO

Getting found

A list of links (Google)
Goal: the click to your site
Keywords, backlinks, tech

GEO

Getting cited

An answer written by the AI
Goal: being the cited source
Clarity, structure, authority, markup

Good news: GEO overlaps heavily with good SEO. It's not starting over — it's extending.

2. Why it's becoming critical

Behavior is shifting fast: a lot of people now ask their questions directly to an AI (ChatGPT, Perplexity…) instead of opening Google and comparing ten links. In that world, the battle is no longer "rank first on the list" but "be the brand/source the AI mentions."

The consequence is stark: you can rank very well on Google and be completely absent from an AI's answer on the same topic. GEO is about making sure you also exist in this new channel — the one eating an increasing share of searches.

3. How to get cited by AI

Generative engines are opaque, but a few principles keep coming up — and they're common sense:

Question-and-answer structureHeadings phrased as questions, clean answers right below: that's exactly what AIs love to extract.

"Citable" statementsClear, factual, self-contained sentences (understandable out of context). Sourced when it's a number.

Structured dataschema.org markup (Article, FAQPage, Person…) helps machines understand who's saying what.

Clear entity + llms.txtWho's speaking and their authority (identified, consistent author), plus a llms.txt file that cleanly exposes your content to models.

In one sentence: clear, citable, well-marked-up content, signed by an identifiable entity.

Practitioner honesty: GEO is an emerging field. Nobody sells a serious guarantee of being cited — the mechanics keep changing. But these principles don't expire, because they also serve your human readers.

4. This site as a case study

I'm not theorizing in a vacuum: this Knowledge Hub is my GEO testing ground. One page per question, headings phrased as questions, JSON-LD (TechArticle, FAQPage, Person) on every page, a llms.txt and a llms-full.txt that summarize the whole site for models. That's precisely why it's built in clean, lightweight static HTML: machine readability is a feature, not an afterthought.