GEO vs SEO: differences, overlap and a pre-launch checklist

Search is no longer just ten blue links. ChatGPT, Perplexity, Claude, Google’s AI Overviews and Gemini answer questions directly, and cite a handful of sources while doing it. Being one of those sources is what GEO (Generative Engine Optimization) is about. The term sounds like a new discipline, but most of it is SEO done properly, plus a few genuinely different things. Here’s where the line is.

SEO vs GEO in one table

	SEO	GEO
Goal	Rank high in a results list	Be quoted or cited inside a generated answer
Unit of success	Position, click, organic traffic	Mention, citation, link inside the answer
Who reads you	Search crawlers (Googlebot, Bingbot)	Search crawlers and LLM crawlers (GPTBot, ClaudeBot, …)
What gets scored	Relevance, links, page experience	Clarity, verifiability, extractable passages, entity authority
Content unit	The whole page	The single passage or paragraph that answers the question
Measurability	Mature (Search Console, rank trackers)	Immature: answers vary run to run, few reliable tools

The honest summary: GEO sits on top of SEO. AI search products mostly retrieve pages using classic search indexes and then summarize them. If you’re not indexable and reasonably ranked, you’re rarely cited. The reverse isn’t true: ranking well doesn’t guarantee being quoted.

Where they overlap (most of the work)

Everything below helps both, so do it first:

Crawlable, indexable pages: correct status codes, no accidental noindex, sitemap, one canonical URL per page. Duplicate URLs hurt both (see how a trailing slash mismatch created duplicate canonicals).
Fast, stable pages: crawlers have timeouts, and users leave. See Core Web Vitals explained with a real case.
Content that answers a specific question well: a clear title, a direct answer near the top, then depth.
Structured data (JSON-LD Article, Organization, BreadcrumbList): it helps search engines understand the page, and gives any machine reader unambiguous facts about author, date and topic.
Authorship and trust signals: real author, dates, an about page, sources. Both systems try to avoid repeating junk.
Multilingual done right: hreflang and one URL per language, as this blog does.

What is actually different in GEO

1. Write passages, not just pages. A generative engine doesn’t cite “a page”, it lifts a chunk that answers the question. Each section should stand on its own: a heading phrased like the question, then a first sentence that answers it without needing the previous paragraph (“This”, “as said above” break when the chunk is extracted).

2. Be specific and verifiable. The paper that introduced the term (GEO: Generative Engine Optimization, Aggarwal et al., KDD 2024) tested tactics on generative engines and found that adding citations, quotations from sources and concrete statistics raised visibility noticeably, while keyword stuffing did not help. Read that as a direction, not a guarantee: results depend on the engine and change over time. But “claim + number + source” is better writing anyway.

3. Let the right bots in, on purpose. LLM-related crawlers are a separate set of user agents, and there are three different purposes worth distinguishing:

Purpose	Examples
Training data collection	`GPTBot`, `ClaudeBot`, `CCBot`, `Google-Extended` (†), `Applebot-Extended` (†)
Search index for AI answers	`OAI-SearchBot`, `Claude-SearchBot`, `PerplexityBot`
Fetch on a user’s request	`ChatGPT-User`, `Claude-User`

† Google-Extended and Applebot-Extended are robots.txt control tokens, not separate crawlers: they tell Google and Apple whether crawled content may be used for AI training/grounding. Blocking Google-Extended does not remove you from Google Search or AI Overviews.

This lets you choose: for example, allow the search bots (so you can be cited) while opting out of training:

User-agent: OAI-SearchBot
Allow: /

User-agent: Claude-SearchBot
Allow: /

User-agent: GPTBot
Disallow: /

User-agent: ClaudeBot
Disallow: /

It’s a business decision, not a technical one. If you want to be cited, blocking everything with Disallow: / under User-agent: * also removes you from AI answers. Check each vendor’s documentation, since user agent names change.

4. Serve content in the HTML. Googlebot renders JavaScript. Many LLM crawlers don’t, or do it inconsistently. A client-side-rendered page can look empty to them. Static or server-rendered output (Astro, Next.js with Server Components, plain HTML) is the safe default. Quick test: curl -s https://yoursite.com/page | grep "your key sentence". If it’s not there, neither is your content for those bots.

5. Build entity clarity. Models associate names with topics based on many mentions across the web. Consistent name, author bio, sameAs links in JSON-LD (GitHub, LinkedIn), and being mentioned in other reputable places help more than any on-page trick. This is the slowest lever and the one that can’t be faked quickly.

6. llms.txt: optional, unproven. It’s a proposed convention (a Markdown file at /llms.txt listing your key pages for LLMs). At the time of writing, no major AI provider has confirmed that it reads it for ranking or citation. Cheap to add, but don’t expect results, and don’t prioritize it over the items above.

What to skip

Keyword stuffing or “AI-bait” phrasing: doesn’t help SEO, and the GEO research didn’t find it helping either.
Hidden text aimed at LLMs (prompt-injection-style instructions in the page): against search engine policies and a reliable way to lose trust.
Mass-generated pages: both systems are getting better at demoting them.
Promises like “guaranteed ChatGPT ranking”: there is no ranking to guarantee. Answers vary between runs and between users.

Pre-launch checklist

Shared (SEO + GEO)

GEO-specific

Main content present in the raw HTML (curl test), not only after JS runs
robots.txt deliberately allows/blocks AI user agents, matching your decision on training vs citation
Each section answers its heading in the first sentence and makes sense out of context
Claims backed by numbers, dates and links to primary sources
Consistent brand/author name, with sameAs links in structured data
Key facts (prices, versions, specs) are in text, not only in images or PDFs
Optional: llms.txt with your most important pages

After launch

Submit the sitemap in Search Console and Bing Webmaster Tools (Bing’s index feeds several AI products)
Check server logs for AI user agents to see who actually visits
Ask the AI tools your target questions every few weeks and note whether you’re cited. It’s manual and noisy, but it’s the only ground truth available

Conclusion

GEO isn’t a replacement for SEO: it’s SEO plus writing for extraction, deciding which bots you allow, and building a recognizable name. If your site is fast, indexable, server-rendered and full of specific, sourced answers, you’ve done ninety percent of both. Do the shared checklist first, then the GEO items.

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