What Is GEO? Generative Engine Optimization Explained
What is GEO? Generative engine optimization gets your brand named and cited in AI answers. How it works, what Google says, and how to measure it.
GEO, or generative engine optimization, is the work of getting your brand named, cited, and recommended in AI-generated answers from ChatGPT, Gemini, Perplexity, Claude, and Google’s AI Overviews and AI Mode. With traditional search, you get discovered. With GEO, you get recommended: your brand on the AI’s shortlist and your page as the source.
I run SEO and GEO strategy for B2B SaaS companies, and the definitions below come from that work, with the data behind it. This guide is the starting point for my generative engine optimization articles. If you want the work done for your company, here is how I run GEO consulting.
What is generative engine optimization, and where did the term come from?
Generative engine optimization is optimizing a brand’s content and presence for AI systems that write answers from sources, and GEO is its short form. The term comes from a 2023 research paper, “GEO: Generative Engine Optimization”, by six computer scientists including Pranjal Aggarwal and Karthik Narasimhan, later presented at the KDD 2024 conference. The authors built a benchmark of queries across many domains, tested ways of rewriting source content, and found that the right changes could raise a source’s visibility in generative engine responses by up to 40%. They also found the effect varied by domain, which is still true in practice.
A “generative engine” is any system that writes an answer from sources: ChatGPT with search, Perplexity, Gemini, Claude, Copilot, and Google’s AI Overviews and AI Mode. GEO is optimizing for how those systems choose, quote, and describe brands. You will also see it called AEO (answer engine optimization) or LEO (LLM engine optimization); the acronyms are covered below.
What is GEO in SEO?
GEO is the part of SEO that covers AI-generated answers. It shares the same foundation: crawlable, indexed pages, content that answers the question, and authority earned from other sites. What changes is the surface you win on and the scoreboard you read.
Google says so directly. Its guide to optimizing for generative AI features, updated in July 2026, states that “the best practices for SEO continue to be relevant because our generative AI features on Google Search are rooted in our core Search ranking and quality systems.” A page has to be indexed and eligible for a snippet to appear in AI Overviews or AI Mode at all.
That is why GEO SEO is one program with two scoreboards. A brand that is invisible in classic search rarely shows up in AI answers, and a brand that ranks well can still be left out of the answer. The longer argument is in GEO vs SEO.
How does generative engine optimization work?
Generative engine optimization works by influencing the three steps every AI engine runs when it answers a question:
- Retrieval. The engine searches the web, often running several related searches for one prompt, and collects candidate sources. If your pages are not indexed or do not rank for those searches, you are not in the pool.
- Selection. The engine picks which sources to trust and quote. Clear, specific, self-contained passages get pulled; vague pages get skipped.
- Synthesis. The engine writes the answer, names brands, and links some of its sources. It names the brands that appear most consistently across the sources it read.
So GEO has two distinct outcomes. Your brand can be named in the answer, which is what the buyer reads, and your page can be cited as a source, which is what earns the click. The two often diverge: the brands AI recommends are frequently not the ones it links to.
Where AI answers get their information
Most AI answers are built from other people’s websites. In a citation export across six B2B SaaS accounts I track, 88.7% of the sources AI answers cited were independent third parties, 8.7% were competitors, and 2.6% were the brand’s own site. When a brand’s own domain appeared, it ranked about fourth on average as a source about its own category. An independent 2026 study of 40 B2B SaaS categories measured third-party citations at 88.4%, almost the same figure.
That split is the most important fact in GEO. Your own pages are a small slice of what the AI reads about you. Review sites, category lists, forums, YouTube, industry publications, and Wikipedia carry most of the weight, so most GEO work happens off your site. The full breakdown by vertical is in my GEO statistics.
GEO vs SEO vs AEO: what the acronyms mean
GEO, AEO, LEO, LLM SEO, and AI engine optimization all describe the same work: getting a brand into AI-generated answers. The labels come from different vendors and different moments, and the method underneath is shared.
| Term | Stands for | What people use it for |
|---|---|---|
| SEO | Search engine optimization | Ranking in classic search results |
| GEO | Generative engine optimization | Appearing in AI-generated answers across engines |
| AEO | Answer engine optimization | The same goal, older term, often tied to featured snippets and voice |
| LEO | LLM engine optimization | The same goal, framed around large language models |
| LLM SEO | Large language model SEO | The same goal, framed around ChatGPT and other LLMs |
| AIO | AI Overviews (sometimes AI optimization) | Google’s AI answer box, a single surface inside GEO |
My advice is to keep two buckets: SEO for classic results and GEO for AI answers, with everything else filed under one of them. For the model-specific version, see LLM optimization.
What Google says about GEO, and why to read it with a grain of salt
Google’s guide lists several GEO tactics you can ignore for Google’s AI features: llms.txt files, “AI text files,” special AI markup, splitting content into tiny chunks, rewriting pages for AI systems, and chasing inauthentic mentions. In Google’s words, “you don’t need to create new machine readable files, AI text files, markup, or Markdown to appear in Google Search.” Structured data is still recommended as part of SEO, and it is not required for AI features.
Know what Google says, and treat it as Google’s view of Google’s own features. Google is not the full authority on GEO. ChatGPT, Perplexity, and Claude run their own retrieval with their own rules, and some tactics that move answers there are ones Google would never recommend. I have seen success with tactics Google says you don’t need.
Where Google and my data agree is the fundamentals. The pages that earn AI citations on the accounts I run already rank, answer the question in the first lines, and carry specific facts. Build on those first, then test the tactics Google dismisses against your own prompt set and keep what moves the answers.
What GEO optimization involves in practice
GEO optimization is five kinds of work, in this order:
- A prompt-level baseline. A dated set of the questions your buyers ask AI, such as best-of, versus, alternatives, and problem-first prompts, run across ChatGPT, Gemini, Perplexity, and Google. For each one, record whether your brand is named, cited, or absent, and who appears in its place.
- Source analysis. For the same prompts, list the third-party pages the answers cite. That list is your off-site target list.
- On-page retrievability. Put the answer in the first lines of the page, make each section stand on its own, add specific facts, and map each priority prompt to one URL. Ranking in classic search for the underlying queries is part of this step.
- Off-site presence. Earn mentions and placements on the sources from step 2: reviews, lists, publications, communities, and video. This is PR work, and most B2B companies need a PR owner for it. My guide to earned media covers how that side runs.
- Entity clarity. Make sure AI systems describe your company correctly: consistent descriptions across your site and profiles, and schema markup as part of standard SEO.
Then re-run the prompt set and read the change. The full list of tactics is in AI search optimization strategies.
Generative engine optimization examples
Here are generative engine optimization examples from B2B SaaS accounts I run, anonymized by vertical.
- An on-page retrofit (HR-tech SaaS). Eight low-visibility pages were rewritten with answer-first structure, self-contained passages, better headers, factual specificity, and prompt-to-URL mapping. Average AI-answer presence rose from about 30% to 48%, an 18-point increase, in 30 days.
- A baseline that changed the plan (cybersecurity SaaS). The first prompt-level read showed the brand in 3% of tracked AI responses, while two larger competitors appeared in 26% and 21%. That gap set the priorities for everything that followed.
- A prompt library built for buyers (HR-tech SaaS). The tracked prompt set grew from 139 to 200 prompts, adding CFO-ready ROI questions, competitive versus terms, alternatives, and integration questions, so the measurement covered the questions that precede a purchase.
- AI referral growth (creator-tools SaaS). LLM-referred sessions rose 353.5% from April to May 2026, alongside a 38% rise in organic subscriptions. Several site changes and a shift in ChatGPT’s citations shared that window, so no single tactic gets the credit. The account write-up has the detail.
How to measure GEO
My full measurement method is in how to measure AI visibility. The short version is four numbers, read together:
- AI impressions in Google. Search Console’s Generative AI performance report, launched in June 2026, shows how often your pages appear in AI Overviews and AI Mode. It reports impressions only, with no clicks or queries yet.
- Named and cited rate by prompt. The share of your tracked prompts where the brand is named, and where your page is cited, compared with competitors.
- AI-referred sessions. Visits from ChatGPT, Perplexity, Gemini, and Copilot in your analytics.
- Influenced pipeline. Demos and opportunities from AI-referred visitors and from buyers who say they found you through AI.
A single “visibility score” with no prompt list behind it tells you very little.
GEO in marketing: who needs it
GEO in marketing matters most for companies whose buyers research before they talk to sales, which covers most of B2B. Buyers now ask an AI engine for a shortlist before they visit a vendor site, and the brands on that shortlist get the first call. GEO marketing is the work of making sure your brand is on it.
If you sell to other businesses, have competitors buyers compare you with, and depend on organic search today, GEO belongs in the plan. If you want outside help, my list of the best GEO agencies and consultants is grouped by specialty. My guide to choosing a GEO agency covers how to vet them.
Frequently asked questions
What does GEO mean?
GEO means generative engine optimization: the work of getting a brand named and cited in answers written by AI engines such as ChatGPT, Gemini, Perplexity, Claude, and Google’s AI Overviews. In a marketing context, GEO almost always means this; in geography and mapping, “geo” still means location.
What does GEO stand for?
GEO stands for generative engine optimization. The acronym comes from the 2023 research paper that named the practice, and it has since become the most common label for optimizing for AI answers. The same work is sometimes called AEO (answer engine optimization) or LEO (LLM engine optimization).
What is a GEO in business?
In business and marketing, GEO is the discipline of making a company visible inside AI-generated answers, so buyers who ask an AI for recommendations see the brand named. It sits alongside SEO in the marketing team and usually shares the same owner.
Does GEO replace SEO?
GEO does not replace SEO. AI features draw on the same ranking systems and the same indexed pages, so SEO is the foundation GEO runs on. What GEO adds is off-site presence, prompt-level measurement, and attention to how AI describes the brand.
Is SEO dead now with AI?
SEO is alive, and AI answers depend on it. Google’s AI features are built on its core ranking systems, and on the accounts I run, the pages that earn AI citations are pages that already rank for the underlying searches. What has changed is that fewer searches end in a click, so the scoreboard now includes AI impressions and mentions alongside traffic.
Which generative engine optimization tool is the best?
The best generative engine optimization tool is the one that shows you the prompt list behind every score and separates named from cited results. Start with Search Console’s free Generative AI performance report and a manual prompt set; a paid tracker is worth it once you track more than a few dozen prompts. My review of Scrunch covers the tool I use at work.
Do I need an llms.txt file for GEO?
You do not need an llms.txt file to appear in Google’s AI features, according to Google’s AI optimization guide. Google’s guide only speaks for Google, though, and I have seen tactics Google calls unnecessary work in other engines. Put off-site presence and answer-first pages first, then test extras like llms.txt against your own prompt set.
How long does GEO take to show results?
On-page GEO changes can show within a month: the HR-tech retrofit above gained 18 points of AI-answer presence in 30 days. Off-site work, such as earning placement on review sites and category lists, usually takes a quarter or more to register in AI answers.
What is AI engine optimization?
AI engine optimization is another name for GEO: optimizing a brand’s content and presence so AI engines name and cite it in their answers. The method is the same whichever acronym a vendor uses.