What Is Generative Engine Optimization (GEO)?

Generative engine optimization is the practice of making a brand the answer an AI model reaches for, rather than a link it ranks. It was defined in a peer-reviewed paper before it became a marketing category, and that paper measured which content changes actually move the needle — a rare thing in a field mostly built on assertion.

Key takeaways

• GEO is not a coinage from the SEO industry. It was introduced in a paper at KDD 2024, which reported that its optimization framework could "boost visibility by up to 40% in generative engine responses."
• The three techniques that won were quotations, statistics and citations — scoring 27.8, 25.9 and 24.9 on the paper's position-adjusted word count metric, a 30–40% relative improvement.
• Keyword stuffing scored 17.8 against a 19.3 baseline. It made pages less visible. The most durable habit from classic SEO is actively counterproductive here.
• Brand mentions across the web correlate with AI Overview visibility at 0.664; backlinks manage 0.218. Across 75,000 brands, the top mention quartile averaged 169 AI Overview mentions against 14 for the quartile below it.
• Google's own position is that none of this is a separate discipline. Its documentation says optimizing for generative AI search "is optimizing for the search experience, and thus still SEO."

What is generative engine optimization?

GEO is the practice of shaping content, and the evidence around it, so that generative engines cite and recommend you inside their answers. A generative engine is any system that answers a question by synthesizing sources rather than listing them: Google's AI Overviews and AI Mode, ChatGPT, Perplexity, Gemini, Copilot.

The distinction that matters is the unit of competition. Search engines rank documents. Generative engines assemble answers, then decide which sources deserve attribution inside them. You can be the most relevant page on the internet for a query and still be absent from the answer, because nothing in your page was quotable in the form the model needed.

Where did the term GEO actually come from?

From an academic paper, not an agency. "GEO: Generative Engine Optimization" was published at the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining in August 2024. It framed the problem as an economic one rather than a marketing one:

"While this shift significantly improves user utility and generative search engine traffic, it poses a huge challenge for the third stakeholder — website and content creators. Given the black-box and fast-moving nature of generative engines, content creators have little to no control over when and how their content is displayed."

This origin is worth knowing for a practical reason. Almost everything published about GEO since is downstream commentary. The paper is the only widely-cited source in the field that ran a controlled experiment on a benchmark it released — GEO-bench, 10,000 queries split 8,000 / 1,000 / 1,000 across training, validation and test.

What did the research find actually works?

The team tested nine content modifications against the same source pages and measured how visible each version became in generated answers. The results split cleanly into tiers.

The top three delivered a 30–40% relative improvement on that metric and 15–30% on a subjective-impression metric. What unites them is not style. It is verifiability. A direct quotation, a specific number and a named source are all things a model can carry into an answer without having to vouch for them itself.

Why did keyword stuffing make pages worse?

Because a generative engine is not counting term frequency — it is deciding whether a passage is safe to repeat. This is the finding most GEO advice skips, and it is the most useful one in the paper. The authors put it plainly: "traditional SEO strategies may not translate to success in this new paradigm."

Repetition of a target phrase does not make a passage more extractable. It makes the prose read as lower quality, and it displaces the concrete detail — the figure, the attribution, the quote — that would have earned the citation. The tactic does not merely fail to help. It costs you 1.5 points against simply publishing the page unmodified.

Does GEO work the same way in every industry?

No, and the paper is explicit that it does not. Its abstract flags that "the efficacy of these strategies varies across domains, underscoring the need for domain-specific optimization methods." The best-performing method by topic area:

The practical read: regulated and factual topics reward citation and hard numbers; interpretive topics reward quotation and a confident register. A checklist copied from a B2B SaaS blog and applied to a legal services site is optimizing for the wrong column.

What actually predicts whether an AI mentions your brand?

Content technique is one half. The other half is whether the model has enough independent evidence that you exist. Ahrefs measured this across 75,000 brands in May 2025, correlating various signals against AI Overview brand mentions:

The gap between mentions and backlinks is the whole argument for GEO as a distinct workstream. A backlink is a vote inside a ranking system. A mention is evidence inside a language model's picture of the world — and it counts whether or not it carries a link.

The distribution is brutally top-heavy. Brands in the top quartile for web mentions averaged 169 AI Overview mentions; the quartile immediately below averaged 14. The bottom half averaged between zero and three. Ahrefs adds the caveat that should accompany every number in this field: correlation is not causation, and every factor studied showed only moderate to weak correlation.

Does ranking on Google still get you into AI answers?

Less than it did, and much less than most planning assumes. In July 2025, Ahrefs found 76.1% of AI Overview citations came from pages already ranking in the organic top 10. By March 2026, running 863,000 SERPs and 4 million AI Overview URLs, the same analysis put it at 38%.

Two honest caveats belong with that halving. Ahrefs attributes part of it to AI Overviews moving to Gemini 3 in January 2026 and leaning more on query fan-out, but also notes it "improved our parsing methodology" — so some of the drop is better measurement rather than pure market change. Treat 76 → 38 as a direction, not a precise delta.

Outside Google the relationship is weaker still. Across 15,000 long-tail queries, only 12% of URLs cited by assistants ranked in Google's top 10 for the original prompt:

Semrush's study of over 500 digital marketing topics found the same shape from the other end: ChatGPT cites pages sitting at organic position 21 or below almost 90% of the time.

What does Google say about all this?

That it is still SEO, and that most GEO tactics are a distraction. This is the counterweight the category rarely prints. Google's own optimization guide for generative AI features states: "From Google Search's perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO." It goes further and tells site owners to "prioritize effective SEO strategies over 'AEO/GEO hacks'."

Specifically, Google says you do not need to break content into small pieces for AI, do not need to write in a special way for generative search, that "structured data isn't required for generative AI search," and that "seeking inauthentic 'mentions' across the web isn't as helpful as it might seem."

Both things can be true. Google is describing its own pipeline, where eligibility flows from being indexed and snippet-eligible. The KDD results and the Ahrefs correlations describe which eligible pages get chosen, and they cover assistants Google does not operate. The reasonable position is that GEO is neither a replacement for SEO nor a bag of hacks — it is a set of editorial and reputational decisions layered on a site that already works.

Do you need an llms.txt file?

Almost certainly not, and for once the data is unusually clear. Google's documentation says "you don't need to create new machine readable files, AI text files, markup, or Markdown to appear in Google Search," and that maintaining one "will neither harm nor help your site's visibility or rankings."

SE Ranking checked roughly 300,000 domains in November 2025 and found 10.13% had the file. Their model found no correlation between having one and AI citation frequency — it performed better with the variable removed entirely. If you already publish one for agent-facing documentation, keep it. It is not a visibility lever.

How do you measure GEO?

Sessions will not tell you. AI referral traffic is small, and much of the value shows up as demand rather than clicks. Measure three things instead:

1. Mention rate. Ask each assistant a fixed set of buying-intent questions on a schedule, and record how often you are named. Cross-model, because coverage is uneven.
2. Citation share. Of the sources named in those answers, how many are yours, versus competitors', versus third-party listicles.
3. Branded demand. Branded search volume and direct traffic, which is where an unclicked mention eventually lands.

Semrush's data offers one reason to care despite low volume: it puts the average AI search visitor at 4.4 times as valuable as an average organic visit, measured by conversion rate, and projects that AI search could send more visitors than traditional search for digital marketing topics by early 2028.

Frequently asked questions

What does GEO stand for?

Generative engine optimization. The term was introduced in a paper presented at KDD 2024, which defined it as a framework for improving content visibility inside generative engine responses.

Is GEO different from AEO?

They emphasize different halves of the same problem. AEO is mostly about making a passage extractable; GEO is mostly about building the entity clarity and third-party evidence that make a model confident enough to recommend you. Most practitioners use the terms loosely and interchangeably.

Does GEO replace SEO?

No. Google's position is that generative AI optimization is still SEO, and a page that cannot be crawled or indexed cannot be cited either. GEO is a layer on a working site, not a substitute for one.

Does keyword optimization help with AI visibility?

Keyword stuffing measurably hurts — it scored below the unmodified baseline in the KDD experiments. Ordinary keyword research still helps you understand demand, but repetition of target phrases is not a GEO tactic.

Do backlinks matter for GEO?

Far less than unlinked brand mentions. Across 75,000 brands, web mentions correlated with AI Overview visibility at 0.664 against 0.218 for backlinks.

Is schema markup required for GEO?

Not for generative AI features. Google states directly that "structured data isn't required for generative AI search," though it still earns rich results in classic search.

How long does GEO take to show results?

Content changes can surface within weeks, because assistants re-fetch pages frequently. The entity and mention side moves on the timeline of earning coverage, which is quarters rather than weeks.

Where to start

Two checks cost nothing and rule out the failure modes that make everything else pointless. Confirm the AI crawlers can actually reach you with the crawler checker, and confirm your pages describe themselves correctly with the meta tags checker. Then decide what you are going to measure with the AI search KPI framework.

If you want the terminology settled before you spend anything, read SEO vs AEO vs GEO. For the extraction side of the work in detail, read what answer engine optimization is, and for the mention-building side, how to get cited by AI.

Sources

• GEO: Generative Engine Optimization (KDD 2024)
• Ahrefs — AI Overview brand visibility across 75,000 brands
• Ahrefs — 38% of AI Overview citations pull from the top 10
• Ahrefs — 12% of AI-cited URLs rank in Google's top 10
• Semrush — AI search and SEO traffic study
• Google Search Central — optimizing for generative AI features
• SE Ranking — llms.txt adoption across 300,000 domains