GEO vs SEO comes down to where you show up. SEO gets your page ranked in a list of links. GEO, short for generative engine optimization, gets your brand named or your page cited inside an answer that an AI system writes, such as Google's AI Overviews or ChatGPT. GEO builds on SEO and doesn't replace it. Most of the work is shared, and a few parts are new.
Search "geo vs seo" on Google and you'll likely see an AI Overview before the first link. When I checked on 18 September 2026 (US, desktop), it cited 12 pages. Six of them ranked outside the top ten, and three weren't in the top 19. That's one check on one day, and overviews vary, but it matches the larger studies below.
The pages that rank for this search agree on the verdict: you need both. I agree. They skip the harder question of which GEO advice has evidence behind it, so this guide spends its time there.
Find out what the answers say about you.
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Start freeGEO vs SEO: the differences at a glance
| SEO | GEO | |
|---|---|---|
| Where you appear | A ranked list of links | Inside a written answer, as a named brand or a cited source |
| What gets chosen | A page | A passage from a page, plus brand names gathered from many pages |
| What builds authority | Links to your site | Mentions of your brand across the web, linked or not. So far that's a correlation |
| What the query looks like | A few keywords | A full question, which the engine splits into several searches |
| Who fetches your pages | Googlebot, which runs JavaScript | Googlebot for Google's AI features, plus AI crawlers such as OAI-SearchBot and PerplexityBot, which mostly don't |
| Where it searches | Google's index | It depends on the assistant: Google's index for AI Overviews and AI Mode, other search backends for ChatGPT, Perplexity and Claude |
| How you measure it | A position that mostly holds between checks | A rate across repeated runs, because one prompt gives different answers each time |
GEO vs SEO vs AEO: what the acronyms mean
Four terms cover most of what you'll read:
- SEO, search engine optimization: ranking pages in a list of results.
- GEO, generative engine optimization: getting into answers that an AI system writes from several sources. It's the academic term, from a research paper covered below.
- AEO, answer engine optimization: being the direct answer on any surface that gives one. It was in use by 2018, when it meant voice assistants and featured snippets.
- LLMO, large language model optimization: shaping how the model itself describes your brand, including what it absorbed in training and repeats without searching.
You'll also see AIO, which usually means Google's AI Overviews and sometimes means "AI optimization".
The terms overlap. Wikipedia's GEO article says no consensus definition distinguishing them had been established in the academic literature as of early 2026, and that they're used interchangeably in practice. Its "answer engine optimization" page now redirects to the GEO article.
If one agency pitches you AEO and another pitches GEO, compare the task lists. They will mostly match. In this guide, GEO means the whole job: getting named and cited in AI answers.
What changed
Mentions count for more than links
Ahrefs studied 75,000 brands in May 2025 to see what goes along with being named in AI Overviews. Branded web mentions had a correlation of 0.664 with AI Overview visibility, where 1 would be a perfect match. Backlinks had 0.218. A mention counted whether or not it carried a link.
A December 2025 follow-up added ChatGPT and AI Mode and found the same pattern: web mentions between 0.66 and 0.71, mentions on YouTube strongest at about 0.74, and link metrics "very weak".
Ahrefs flags the limit itself: correlation isn't causation. Well-known brands collect both mentions and AI visibility. Still, the pattern makes sense: an AI system reads many pages and summarises them, so what those pages say about you counts for more than which of them link to you.
One question becomes several searches
Google calls it query fan-out: AI Mode breaks your question into subtopics and runs many searches at once on your behalf. Your page can be cited for a sub-question nobody typed.
So ranking for the main keyword matters less than it did. In July 2025, Ahrefs found that 76% of the pages cited in AI Overviews ranked in Google's top 10 for the same query. Its March 2026 re-run found 38%, with 31% of cited pages ranking outside the top 100.
Between the two studies, Ahrefs improved its citation tracking and AI Overviews moved to Gemini 3, so don't read the drop as exact. Ahrefs' read is that AI Overviews now lean less on the results for the query itself and more on the results for the fan-out queries. That argues for covering a topic's follow-up questions on one solid page over building one thin page per keyword.
Most AI crawlers don't run JavaScript
Vercel and MERJ analysed crawler traffic across Vercel's network in December 2024. None of the major AI crawlers rendered JavaScript, and that included the crawlers from OpenAI, Anthropic, Meta, ByteDance and Perplexity. Googlebot does render pages.
So if your content only appears after JavaScript runs, Google sees your page and ChatGPT may see an empty shell. Nothing errors and your Google rankings don't move, so you won't notice unless you look. The study is nearly two years old and covers one network, but I haven't seen newer data that contradicts it.
Each assistant searches somewhere different
A good Google ranking doesn't carry over to the other assistants on its own. AI Overviews and AI Mode draw on Google's index. ChatGPT search has its own crawler, OAI-SearchBot. When Seer Interactive compared ChatGPT search citations with search results in February 2025, 87% matched a page in Bing's top 20 for the same question, and 56% matched Google. Seer calls its 100-query sample directional. Perplexity runs its own crawler as well.
How to rank in ChatGPT covers which OpenAI crawler decides whether you can be cited, and where ChatGPT looks when it searches.
Answers change from run to run
Ask an AI system the same question twice and you can get two different sets of brands. So being named in an answer is a rate: across 30 runs, you appear in some share of them. A result should read like 32% (24–41%), the share plus the range the sample supports.
One run of one prompt tells you close to nothing. A single "visibility score" with no range hides that. It's the reason Shruwd, the tool we are building, shows every number with its range and withholds any number with fewer than ten responses behind it.
AI visibility: how to measure it sets out what to count, how many runs a number needs, and how to tell a real change from noise.
What didn't change: Google says it's still SEO
Google publishes a guide called Optimizing your website for generative AI features on Google Search. It answers the GEO question in one sentence:
From Google Search's perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO.
The same guide lists things you can ignore for Google Search. One is llms.txt and similar special files, because "Google Search itself doesn't use them". Another is overfocusing on schema: structured data "isn't required for generative AI search, and there's no special schema.org markup you need to add."
Google is speaking for Google Search only, which covers AI Overviews and AI Mode. ChatGPT, Perplexity and Claude find their sources in other ways, and most of the differences above come from there.
Is GEO replacing SEO?
No. GEO depends on SEO. AI systems answer by running searches and reading what they find, so a page that search engines can't crawl, index and retrieve has little chance of being cited. GEO adds a short list of jobs that a classic SEO plan doesn't include.
The skeptics are right about a lot. Much of what gets sold as GEO is technical SEO plus clear writing: direct answers, tables, FAQ sections. Good editorial teams have done that since featured snippets arrived, and a new acronym is a convenient way to sell it again.
Three jobs are new, though:
- Checking that AI crawlers can reach and read your pages.
- Earning mentions on the pages that AI answers draw from, linked or not.
- Measuring with repeated prompt runs and ranges, since there's no stable position to track.
Most of your effort still belongs to SEO.
The "up to 40%" statistic comes from a lab test
One number keeps turning up in GEO pitches: GEO methods can "boost visibility by up to 40%". It comes from the paper that coined the term, by researchers at IIT Delhi and Princeton, published at the KDD conference in 2024.
The authors built their own answer engine. For each of 1,000 test queries, it took the top five Google results and had GPT-3.5 write an answer that cited them. GPT-3.5 then rewrote one of the five sources using one of nine methods, the engine answered again, and the authors measured how much more of the answer drew on the rewritten source.
They report gains of 30 to 40% for their best methods: adding quotations, adding statistics and citing sources. The 40% is the single best case, quotations. Keyword stuffing offered "little to no improvement".
Three reasons to hold the figure loosely:
- The engine was the authors' own. No live AI search product produced the headline number.
- Five sources competed for one answer, so a gain for one is a loss for the others, and relative gains look large.
- GPT-3.5 wrote the rewrites, and the prompts in the authors' published code let it invent what it added. The statistics prompt reads "Add positive, compelling statistics (even if hypothetical)". The test shows that text shaped like evidence gets cited more. It didn't compare real evidence with invented evidence.
The authors also ran 200 queries through Perplexity, uploading the source texts as files because Perplexity wouldn't let them choose its sources. Quotations and statistics still helped there, and citing sources gave mixed results.
The direction is worth keeping: pages with concrete, attributable facts were easier for a model to cite. So publish your real numbers. The 40% describes the authors' test setup and doesn't predict what you would gain.
What to do first
In order of certainty. The first two are pass or fail, and you can check both today.
1. Check that AI crawlers are allowed in
Open yoursite.com/robots.txt and look for rules naming OAI-SearchBot, ChatGPT-User or PerplexityBot. OpenAI documents its crawlers separately: GPTBot collects content that may be used for training, and OAI-SearchBot surfaces sites in ChatGPT's search results. A site that blocks the second one to stay out of training data has blocked the wrong bot. If you find a block you didn't intend, remove that rule. Shruwd lists every AI crawler worth knowing, what each one fetches for, and which of them fetch pages to answer a live question. Its free crawler access check reads a site's robots.txt against all of those tokens at once.
Then check your CDN or firewall. A bot rule there can refuse AI crawlers whatever robots.txt says. Cloudflare, for one, has a setting that blocks AI bots, and it's easy to forget who switched it on.
If you use Search Console, check one more switch. Since 31 August 2026 every property has a Search generative AI control, and a site has to be included there to appear in Google's AI features. Include is the default. Confirm nobody changed it.
2. Check that your content is in the raw HTML
Open a key page, view its source (Ctrl+U, or Cmd+Option+U on a Mac) and search for a sentence you can see on the page. If the sentence isn't in the source, a crawler that doesn't run JavaScript can't see it either.
For a number, run this in PowerShell. It ships with Windows. On macOS or Linux, install PowerShell and start it with pwsh.
$url = "https://example.com/pricing"
$html = (Invoke-WebRequest -Uri $url -UseBasicParsing).Content
$text = $html -replace '(?s)<script.*?</script>|<style.*?</style>', '' -replace '<[^>]+>', ' ' -replace '\s+', ' '
"{0} characters of visible text in the raw HTML" -f $text.Trim().Length
A full page returns thousands of characters. A few hundred, on a page that looks complete in your browser, means the content arrives by JavaScript. The fix is server-side rendering or static generation, and it comes before everything else on this list.
3. Keep doing SEO
AI systems find their sources by searching, so being crawlable, indexed and useful still comes first.
4. Find the pages that answers cite, and get onto them
Ask ChatGPT and Google the questions your buyers ask, several times each, and note which sources keep coming back. When I checked Google for 11 buying keywords in my own category in September 2026, one search each, 49 of the 84 citations in its AI Overviews went to pages owned by vendors in the category, and YouTube videos were cited in 8 of the 11 answers. Yours will differ, so look. The sources that keep coming back are your outreach list.
5. Write passages that can be lifted
Put the question in a heading and answer it in the first two or three sentences underneath. Use real numbers, names and dates. Adding statistics is the part the GEO paper tested. The rest is ordinary good editing.
6. Measure with repeated runs
Pick 20 to 50 questions your buyers ask. Run each one several times on each engine. Track how often you're named, as a rate with a range, and wait for a change bigger than the run-to-run noise before you credit any fix.
What can wait
Schema markup as an AI-citation tactic, and llms.txt. Google says neither is needed for its AI features. Keep schema for rich results, where it does work.
LLM SEO: five levers with evidence grades both of these, and the five tactics that do have evidence behind them.
Shruwd runs most of these checks for you. It reads your server logs to see which AI crawlers reach your pages and which get refused. Every week it asks your buyers' questions on Google AI Overviews and ChatGPT and reports how often you're named, with a range on every number. Each problem becomes a finding that names the page and the fix, and after you make the change, it measures again.
Frequently asked questions
What is GEO in digital marketing?
GEO stands for generative engine optimization. It's the work of getting your brand named and your pages cited in answers written by AI systems such as ChatGPT, Google's AI Overviews and Perplexity. The term comes from a research paper published in 2024. In practice it sits on top of SEO, because those systems find their sources by searching.
Is SEO dead because of AI?
No. Clicks do drop when an AI summary is on the page: Pew Research tracked 900 US adults in March 2025 and found they clicked a search result on 8% of visits when an AI summary appeared, against 15% when it didn't. But AI answers are assembled from pages that search engines can crawl, index and retrieve. Most of the work that gets you found in search also gets you into the answer.
How do you measure GEO?
With a fixed set of questions your buyers ask, run repeatedly on each AI engine. Count how often your brand is named, how your share compares with competitors, and how often your pages are cited. Report each as a rate with a range, because answers vary between runs. Shruwd's docs explain how to tell a real change from noise.
Does schema markup or llms.txt help with GEO?
For Google's AI features, Google says neither is needed: structured data "isn't required for generative AI search", and Google Search doesn't use llms.txt. When Ahrefs tracked 1,885 already-cited pages that added schema, their AI citations barely moved. Schema still earns rich results in classic search, so keep it for that. llms.txt is useful for pointing coding agents at developer documentation, which is a different job from search visibility.
