Ask an AI engine what generative engine optimization is, and you get a tidy answer with a row of sources under it. We tracked that exact question on October 21, 2026: four AI engines cited 61 sources between them, and our own small site was not one of them. This guide explains what GEO means, where the term came from, what the research really found, and what our trackers measured.
Generative Engine Optimization in One Sentence
Generative engine optimization (GEO) is the work of making your content more likely to be used, mentioned and cited in the answers that AI engines such as ChatGPT, Google AI Overviews and Perplexity write. The 2023 paper that coined the term describes it as a way to help content creators improve “their content visibility in generative engine responses” (Aggarwal et al., arXiv).
Google uses almost the same words. Its guide for site owners says GEO and AEO “are both terms you may see used to describe work specifically focused on improving visibility in AI search experiences” (Google Search Central).
So what is a “generative engine”? It’s any search tool that writes an answer instead of only listing links. It fetches pages, reads them, and summarizes them with a large language model. The pages it leans on show up as citations, and those citations are what GEO tries to win.
Here’s the catch, though. “GEO” is a new label on a goal that is partly old. A lot of what helps you appear in AI answers is the same work that helps you rank in search. The parts that are new are how you measure it and what you can honestly expect.
Key Takeaways
GEO matters because AI answers change how people click: Pew Research Center found that Google users who saw an AI summary clicked a traditional result in 8% of visits, against 15% for users who saw none (Pew Research Center, 2025). Google calls GEO “still SEO,” and the research gains come with conditions. Want the short version? Get crawled, write pages worth quoting, and measure before you change anything.
Where the Term Came From: The 2023 GEO Paper
The term comes from “GEO: Generative Engine Optimization,” a paper by six researchers from Princeton University, IIT Delhi and two independent researchers, first posted on November 16, 2023 and accepted to KDD 2024 (arXiv 2311.09735). Its abstract reports that GEO “can boost visibility by up to 40% in generative engine responses.” Most GEO articles quote that number. Fewer explain how it was measured, so here is what the paper actually did.
How the researchers tested GEO
They built GEO-bench, a benchmark of 10,000 queries drawn from nine sources, including real Bing and Google queries, Reddit’s ELI5 questions, debate questions, queries from Perplexity’s Discover section and queries written by GPT-4. The set was split into 8,000 training, 1,000 validation and 1,000 test queries, with 80% informational queries.
Their “generative engine” was a simple two-step system: fetch the top 5 Google results for a query, then have GPT-3.5 Turbo write an answer from those five pages. They then rewrote one of the five pages with a GEO method and checked whether that page got more space and prominence in the new answer.
The paper tested nine rewriting methods:
- Authoritative: a more persuasive, confident tone
- Statistics Addition: numbers instead of vague claims
- Keyword Stuffing: more keywords from the query, classic SEO style
- Cite Sources: citations to credible sources
- Quotation Addition: quotes from credible sources
- Easy-to-Understand: simpler language
- Fluency Optimization: smoother, more fluent text
- Unique Words: rarer vocabulary
- Technical Terms: more technical vocabulary
What the GEO paper found
The best methods improved on the baseline by 41% on the paper’s word-count visibility metric and by 28% on its subjective impression metric, per Table 1 of the paper (Aggarwal et al., arXiv). Cite Sources, Quotation Addition and Statistics Addition were the top three, with relative gains of 30 to 40% on the first metric.
Three other findings get quoted less often, and they matter more for real sites:
- Keyword stuffing barely helped. The authors found it offered “little to no improvement,” and on Perplexity it did 10% worse than the baseline.
- Tone didn’t move much. A more authoritative tone showed “no significant improvement.”
- Lower-ranked pages gained most. Cite Sources raised visibility by 115.1% for pages ranked fifth in the search results, while the top-ranked page lost 30.3% on average (Table 2 of the paper).
The team also ran the methods on Perplexity.ai, a live engine. There, Quotation Addition did best, with a 22% gain over the baseline on the word-count metric (Aggarwal et al., arXiv).
Did the paper measure Google rankings or traffic? No. The authors say they “didn’t evaluate how GEO methods affect search rankings,” and every test started with the page already among the five sources. Keep that in mind whenever someone quotes “up to 40%.”
What later research says about those numbers
A July 2026 critical survey of 45 GEO studies concludes that the paper’s widely cited gains “are valid within its experimental setting but conditional on a source already being present in a fixed context” (Martinez, arXiv, 2026). In plain words, rewriting helps a page that the engine has already picked up. It doesn’t prove the rewrite gets the page picked up in the first place.
The same survey finds that topical relevance and position in the engine’s context are the most reproducible levers, that generic tips “transfer poorly,” and that “citation-oriented rewrites can impair retrieval.” Its bottom line is blunt: no reviewed technique showed “a stable, longitudinal, cross-platform causal effect on organic discoverability.”
We read that as good news for honest sites, not bad news. The research doesn’t support tricks. It supports pages that are relevant, easy to find and worth quoting.
How Generative Engines Choose What to Cite
Google says its AI Overviews and AI Mode pull from its regular Search index: to be a supporting link, “a page must be indexed and eligible to be shown in Google Search with a snippet,” with “no additional technical requirements” (Google Search Central). Each engine documents only part of its process, so the safest map of how citations work is what the engines publish themselves.
Google AI Overviews and AI Mode
Google’s optimization guide names two techniques. The first is retrieval-augmented generation, also called grounding: Google’s ranking systems retrieve pages from the Search index, and the model writes an answer from them with links to the pages that support it. The second is query fan-out, where the model runs “a set of concurrent, related queries” to fetch more results (Google Search Central).
Fan-out explains something that surprises many site owners. A page can be cited for a question it never targets, because it ranked for one of the hidden follow-up searches. Google’s guide also notes that “a site must be included in Search generative AI features in Search Console to be eligible,” so check your Search Console settings too. For a deeper look at Google’s side, see our guide to how Google AI Overviews work.
ChatGPT search
OpenAI separates its crawlers by job. OAI-SearchBot “is used to surface websites in search results in ChatGPT’s search features,” and “Sites that are opted out of OAI-SearchBot will not be shown in ChatGPT search answers” (OpenAI). GPTBot is a different crawler, used for model training, and you can block it while allowing OAI-SearchBot. OpenAI says robots.txt changes take about 24 hours to reach search. Our ChatGPT search guide covers how ChatGPT finds sources in more detail.
Perplexity
Perplexity documents the same split. PerplexityBot “is designed to surface and link websites in search results on Perplexity,” and it is “not used to crawl content for AI foundation models” (Perplexity). A second agent, Perplexity-User, fetches pages when a user asks a question. Our guide to letting PerplexityBot crawl your site goes deeper on that engine.
What does this tell you? Every engine starts with access and retrieval. If the right crawler can’t reach your page, or your page doesn’t come up in the engine’s search step, no amount of rewriting will get it cited.
GEO vs SEO: What Changes and What Stays the Same
Google’s position is that “optimizing for generative AI search is optimizing for the search experience, and thus still SEO” (Google Search Central). Its AI features page adds that “There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary.” So is GEO just SEO with a new name? Mostly, yes, with real differences in what you track.
| Classic SEO | GEO | |
|---|---|---|
| What you want | A high position in a list of links | A mention or citation inside a written answer |
| Where it shows | Google and Bing results pages | ChatGPT, Google AI Overviews and AI Mode, Perplexity, Copilot and others |
| How a page gets in | Crawling, indexing and ranking | The same crawling and indexing, plus each engine’s own search step |
| Main unit of success | Rank, clicks and impressions | Citations, mentions and share of voice |
| How you measure it | Rank trackers and Search Console | Prompt trackers, plus Search Console for Google’s AI features |
| Stability | Positions move, but slowly | Answers can change from one run to the next |
What stays the same is the foundation. Google’s list of SEO basics for AI features includes allowing crawling in robots.txt and in “any CDN or hosting infrastructure,” internal links, a good page experience, important content in text form, and structured data that “matches the visible text on the page” (Google Search Central).
What changes is the scoreboard. A page can rank first and still go uncited in the AI answer above it. A small page can be cited without ranking first for the main query, thanks to fan-out. And because one AI answer is a single block of text, there’s no “position 3” to report. That’s why GEO needs its own measurement.
GEO, LLM SEO, AEO and LLMO: One Idea, Several Names
LLM SEO, AEO and LLMO all describe the same goal as GEO: being used and cited by AI answers, and Google treats “AEO” and “GEO” as two names for that work (Google Search Central). The names differ mostly in which word the speaker wants to stress. Which one should you use? Use the one your audience searches for; the work underneath is the same.
| Term | Full form | What the name stresses |
|---|---|---|
| GEO | Generative engine optimization | The engines that write answers; the term from the 2023 paper |
| LLM SEO | Large language model search engine optimization | SEO aimed at tools built on large language models |
| AEO | Answer engine optimization | Getting your content used as “the answer” |
| LLMO | Large language model optimization | The model itself, rather than the search step |
| AI SEO | Artificial intelligence SEO | A loose umbrella, also used for AI writing and SEO software |
So what is LLM SEO? It is GEO under another name. The “LLM” stands for large language model, the technology behind ChatGPT, Gemini, Claude and the models behind Google’s AI features. When people search “llm seo meaning” or “what is llm seo called,” the honest answer is: it’s usually called GEO now, and Google calls it SEO.
One distinction is worth keeping, whatever you call the work: being found by a model’s live search step is not the same as what a model learned in training. The 2026 survey describes GEO as a pipeline that runs from search activation and crawling through retrieval, citation and user behavior (Martinez, arXiv, 2026). Training data is a separate question, and OpenAI and Perplexity both give it a separate crawler.
How Much Interest Is There? What Two SEO Tools Reported
When we looked up “generative engine optimization” on October 21, 2026, Semrush reported 9.9K monthly US searches and SE Ranking reported 3.6K for the same keyword in the same database country. Two respected tools, one keyword, and the bigger estimate is about 2.75 times the smaller one. Which number is right? Neither tool can see Google’s real data, so both are estimates built from their own panels and models.
Here is what each tool showed us, copied from the screen:
| Metric for “generative engine optimization” | Semrush (free account) | SE Ranking (14-day trial) |
|---|---|---|
| US monthly search volume | 9.9K | 3.6K |
| Global monthly search volume | 22.9K | 13.8K |
| Keyword difficulty | 72% (“Hard”) | 78/100 (“NOT EASY”) |
| Search intent | Informational | Informational |
| CPC | $14.49 | $11.78 |
| Competition | Competitive Density 0.60 | 0.54 |
What surprised us was how much the tools agreed on everything except size. Both called the intent informational. Both rated the keyword hard to rank for, and both put the CPC above $11. That agreement tells you more than either volume number: people searching this term want an explanation, and advertisers pay real money to reach them.
A few practical lessons from that lookup:
- Use one tool for trends. Compare a keyword with itself over time inside one tool, not across tools.
- Check the database country. SE Ranking defaulted to a different country in our account, and we had to switch it to the US before the numbers meant anything.
- Don’t plan around global volume if you write for US readers. Semrush’s global figure was more than twice its US figure.
For the full Semrush lookup, metric by metric, see our free-account test of Semrush Keyword Overview. The SE Ranking trial is covered in our SE Ranking review.
What AI Engines Cited When We Asked “What Is GEO?”
When we tracked the prompt “What is generative engine optimization (GEO)?” in Otterly.AI on October 21, 2026, four AI engines cited 61 sources in total: ChatGPT 37, Perplexity 10, Google AI Overview 9 and Microsoft Copilot 5. ChatGPT alone produced about 61% of the citations for that one question. Our site, a small marketing website our own team runs, was cited 0 times, and brand coverage was 0%.
| AI engine | Citations for “What is GEO?” |
|---|---|
| ChatGPT | 37 |
| Perplexity | 10 |
| Google AI Overview | 9 |
| Microsoft Copilot | 5 |
| All four engines | 61 |
Which page did the engines lean on most? Across the five prompts we tracked, the page Otterly listed as most cited was Google’s own guide to optimizing for generative AI features, cited 7 times. Writesonic, which we ran on the same five prompts, also listed that guide and Google’s “Succeeding in AI search” post among the cited pages.
When we tested this, we expected vendor blogs to dominate the answer about GEO. They were there, but the most-cited page was official documentation. That fits Google’s advice to create “unique, compelling, and useful” content, and it fits the paper’s finding that citations and quotes from credible sources help. Engines like to quote the people closest to the facts.
Two cautions about this data. It is one day, so it’s a snapshot, not a trend. And the counts depend on the tool: Perplexity cited exactly 10 sources on every prompt we tracked, which looks like a fixed limit. The full prompt-by-prompt table is in our Otterly.AI vs Writesonic GEO tools comparison.
How to Start With GEO: The First Three Steps
Start where every engine starts: access. OpenAI says sites that block OAI-SearchBot “will not be shown in ChatGPT search answers” (OpenAI), and Google requires a page to be indexed and snippet-eligible before it can be a supporting link. Three steps get a site from zero to a measured baseline. Why only three? Because the rest depends on what your baseline shows.
- Let the right crawlers in. Check robots.txt, your CDN and your firewall for Googlebot, OAI-SearchBot and PerplexityBot. Decide on GPTBot and Google-Extended separately, since those control training and some other AI uses, not search answers. The free Semrush Site Audit we ran showed a “Blocked from AI Search” panel naming ChatGPT-User, OAI-SearchBot, Googlebot and Google-Extended, which is a quick way to spot a block.
- Write passages worth quoting. Answer the question in the first sentence of each section, add numbers with their sources, and add what only you know. Google’s guide calls this “non-commodity content” and gives first-hand reviews as an example of a unique point of view.
- Take a baseline before you change anything. Write down five to fifteen prompts your customers ask, run them through a tracker or by hand, and save the date, the engines and the results.
We did step 3 first, and it changed our plans. The Semrush audit scored our site’s AI Search Health (beta) at 95%, while both trackers showed 0% visibility. That ruled out a crawler problem and pointed us at content.
A full checklist, with tactics such as content formats and outreach, goes beyond a definition guide. For engine-specific steps, read our guide on how to rank in ChatGPT.
Should you hire someone instead? That’s a fair question, and we’re not neutral on it: the team behind this site also runs a GEO agency. So we keep that topic in a separate guide with the disclosure up front. If you’re weighing outside help, our buyer’s guide to generative engine optimization services lists what to check before you sign.
How to Measure GEO: Visibility, Citations and Share of Voice
GEO is measured with prompt trackers that ask AI engines a fixed set of questions and count how often your brand is mentioned or cited; on our first day, Writesonic’s report covered “5 answers across 3 AI platforms and 5 prompts” and scored our site at 0% AI visibility. Each tool names its metrics differently. Here is what the ones we used actually report.
| Metric | Tool where we saw it | What it roughly tracks | Our day-one value |
|---|---|---|---|
| Brand coverage | Otterly.AI | Share of answers that mention your brand | 0% on every prompt |
| Domain citations | Otterly.AI | Times your domain is cited as a source | 0 |
| AI visibility | Writesonic | Share of answers where your brand is visible | 0% (0 of 5 answers) |
| Share of voice | Writesonic | Your mentions compared with competitors’ | 0% (rank 6 of 6) |
| Citation share | Writesonic | Your share of all cited sources | 0% |
| Generative AI performance report | Google Search Console | How your content performs in Google’s generative AI features | Not checked in this test |
Is a 0% result a failure? No. It’s a starting line. A tracker that tells a small site “nobody quotes you yet” is doing its job, and it gives you something to compare against in a month.
In our setup, the trackers also differed in what they demanded. Otterly.AI wouldn’t finish setup with fewer than 15 prompts. Writesonic let us track exactly 5, which our Writesonic review covers in more detail. SE Ranking wouldn’t launch a project without at least one AI prompt, and its project page showed widgets for AI Overview, AI Mode, ChatGPT, Gemini and Perplexity. Pick the tool whose rules fit the list of questions you actually care about.
Don’t skip Google’s own data. Google’s optimization guide recommends the Generative AI performance report in Search Console, and its AI features page says sites in AI Overviews and AI Mode “are included in the overall search traffic” in the Performance report (Google Search Central). It covers Google only, but it’s free. If you’re new to the tool, start with our guide to Google Search Console for SEO.
To choose a tracker, compare the options in our roundup of AI search visibility tools, or start broader with our best AI SEO tools guide.
GEO Myths: Special Files, Special Schema and Guaranteed Placement
Google’s guide lists several popular GEO “hacks” you can ignore for Google Search, starting with llms.txt: creating one “will neither harm nor help your site’s visibility or rankings in Google Search, as Google Search ignores them” (Google Search Central). Why do these myths spread? Because a new field rewards confident advice, and checking it takes time. Here are five we see most often.
Myth 1: You need an llms.txt file or AI-only markup. Google says you don’t need new machine-readable files, AI text files or Markdown to appear in its AI features. Other services may read such files, so add one only if a service you care about asks for it.
Myth 2: You need special schema for AI. Google says “there’s no special schema.org markup you need to add.” Structured data still helps with rich results, as long as it matches the visible page.
Myth 3: Chop content into tiny chunks. Google says there’s “no requirement to break your content into tiny pieces for AI to better understand it” and that there’s “no ideal page length.” Clear headings help readers, and that’s reason enough.
Myth 4: Add quotes and statistics everywhere and citations follow. This one comes from a misreading of the 2023 paper. Those gains came from pages that were already among the engine’s five sources, and the 2026 survey warns that “citation-oriented rewrites can impair retrieval” (Martinez, arXiv, 2026). Add numbers and quotes where they help a reader, not as a formula.
Myth 5: Someone can guarantee AI placement. Google says “No third-party tool has access to our internal ranking or AI systems.” No agency or tool controls what ChatGPT or Perplexity cites either. Treat any guarantee as a red flag.
Notice the pattern. Every myth sells a shortcut that skips the slow parts: being relevant, being reachable and being worth quoting. The evidence so far, from Google’s documentation to the 2026 survey, keeps pointing back to those three.
What GEO Means for Your Site Right Now
For most sites, GEO in 2026 means good SEO plus a new habit of measurement: Google says its AI features “are rooted in our core Search ranking and quality systems” (Google Search Central), so the foundation you already have still counts. What’s new is checking, on a schedule, whether AI answers mention you. Where should you begin this week?
A short plan you can follow:
- Today: Check that Googlebot, OAI-SearchBot and PerplexityBot can reach your key pages.
- This week: Write down five questions your customers ask an AI engine, and record what each engine answers.
- This month: Improve the pages that should answer those questions, with first-hand facts and clear sources.
- Next month: Run the same questions again, the same way, and compare.
Our own site started at 0% in every tracker. That’s not a reason to panic; it’s the honest first entry in a log. GEO rewards the sites that keep that log and keep improving the pages behind it.
References
- Aggarwal et al.: GEO: Generative Engine Optimization (arXiv 2311.09735, KDD 2024)
- Martinez: Optimizing Visibility in Generative Engines: A Critical Survey of Generative Engine Optimization (2023-2026) (arXiv 2607.14035)
- Google Search Central: Optimizing your website for generative AI features on Google Search
- Google Search Central: AI features and your website
- OpenAI: Overview of OpenAI Crawlers
- Perplexity: Perplexity Crawlers
- Pew Research Center: Google users are less likely to click on links when an AI summary appears in the results (2025)