Generative engine optimization (GEO) is the work of making your pages easy for AI search tools such as Google AI Overviews, AI Mode, ChatGPT and Perplexity to find, understand and cite. In practice it is solid SEO plus clear, specific, well-sourced content written in self-contained answers. There is no secret markup, and Google says many suggested GEO "hacks" aren't effective.
What is generative engine optimization and why does it matter?
Generative engine optimization (GEO) is the practice of shaping your pages so AI search tools can retrieve them, understand them and cite them inside the answers they write. The target moves from a position in a list of links to a place in a synthesised answer, ideally as a named, linked source.
Many buyers now ask an AI tool a question and read one combined answer instead of scanning a page of results. That answer is assembled from a handful of sources. GEO is about being one of them, and being described accurately when you are.
Which AI platforms does GEO cover?
The main ones for UK businesses are:
- Google AI Overviews and AI Mode, plus the Gemini app
- ChatGPT Search from OpenAI
- Perplexity
- Microsoft Copilot, which draws on Bing's index
- Claude from Anthropic, when it searches the web
Each retrieves and cites in its own way. They share a pattern, though: find relevant pages, choose a few, write an answer from them and link some of those pages as sources.
What does an AI system look for in a page?
In my view, four qualities matter most. This is my own working checklist:
- Clear structure. Headings that match real questions, with the answer directly beneath.
- Factual precision. Specific figures and names, each traceable to a source.
- Credible sourcing. Signs that a named person with real experience wrote it and stands behind it.
- Plain language. Sentences a model can lift out and quote without losing their meaning.
Does GEO replace SEO?
No. Google's AI features retrieve from the same index and ranking systems as ordinary search, so a page that isn't indexed or can't compete in search rarely gets cited. I treat GEO as a layer on top of good SEO, with more weight on clarity, sourcing and answering the next question.
If you want a second pair of eyes on how your own site is set up for this, Book a Discovery Call and I'll walk through it with you.
What is the technical architecture of generative engines?
The technical architecture of a generative engine pairs a large language model (LLM) with a search system. The model learned language and general knowledge from its training data, but for current questions it usually retrieves live web pages first and writes its answer from them. That retrieval step is where your content has influence.
Training data versus live retrieval
Training data is fixed at a cut-off date. You can't edit what a model has already learned, and you can't see exactly what it read. You can influence what it retrieves, because retrieval reads the web as it stands today.
Retrieval-augmented generation (RAG) is the name for this: fetch relevant documents, then generate an answer grounded in them. Google describes its own version as working "by relying on our core Search ranking systems to retrieve relevant, up-to-date web pages from our Search index."
Microsoft Copilot works in a similar way on top of Bing. ChatGPT Search and Perplexity use their own retrieval setups, which can draw on third-party search indexes. The detail differs by platform. The principle holds everywhere: you can't be cited if you can't be found.
Does ranking in Google still matter for AI answers?
It matters, but the top results are no longer the whole pool. Ahrefs found the share of AI Overview citations from pages that also rank in the top 10 for the same query fell from about 76% in July 2025 to about 38% in its 02/03/2026 update.
The 2026 study covered 863K keyword SERPs and 4M AI Overview URLs, against 1.9M citations in 2025, and Ahrefs widened its counting method between the two. In 2026, about 31% of citations ranked 11 to 100 and about 31% ranked beyond 100. Google is selecting fewer of its cited pages directly from those results.
My reading: ranking gets you into the running, and covering the related questions a buyer asks next now matters more than it did.
What is the three-stage response generation process?
Most generative engines work in three broad stages. They analyse the question and expand it into related searches, retrieve a small set of relevant passages, then write an answer that cites some of them. Each stage gives you a different job, from covering follow-up questions to being easy to quote accurately.
Stage 1: query analysis and fan-out
The system reads the question for intent and the depth of answer needed. It often splits the question into several related searches. Google defines this query fan-out as "A set of concurrent, related queries generated by the model to request more information and fetch additional relevant search results to address the user's query."
Google also warns that creating pages for every fan-out variation to manipulate results breaches its scaled content abuse policy. The better route is one useful page that answers the real follow-up questions. I explain what fan-out does to your reporting in why your Search Console CTR collapsed.
Stage 2: retrieval
Each related search pulls candidate pages from an index. Systems match on meaning as well as words, often using vector embeddings: numeric representations of text that let a model match a passage to a question worded differently. Only a small set of the most relevant passages goes forward.
The practical point is that retrieval works at passage level. I write each section to answer one question on its own, so a passage can be used without the rest of the page. That is a readability choice, not a Google requirement: Google's guide says "There's no requirement to break your content into tiny pieces for AI to better understand it."
Stage 3: synthesis and citation
The model writes an answer from the retrieved passages and links some of them as sources. Not every retrieved page earns a citation, and the wording can drift from yours. In my experience, clear, specific statements are less likely to be misread at this step.
What does the research say?
One widely cited test is the GEO paper by Aggarwal and colleagues, first published in November 2023 and presented at KDD 2024. In a controlled setup, where each page was already among the sources given to the model, adding citations, quotations and statistics made pages more visible in the answers.
The authors report that GEO "can boost visibility by up to 40% in generative engine responses." That was measured on 2023-era models in a test bench, not in live AI search. I treat it as direction: specific, well-sourced writing helps.
GEO vs traditional SEO: how do they compare?
Traditional SEO aims for a ranking position and a click. GEO aims for inclusion and an accurate description inside an AI answer, which may or may not send a click. The foundations overlap heavily: indexing, crawlability and useful content serve both. The differences are in emphasis and in how you measure success.
| Factor | Traditional SEO | Generative engine optimization |
|---|---|---|
| Primary goal | Rank for a keyword and earn the click | Be retrieved, cited and described accurately in AI answers |
| Unit that competes | The whole page | Individual passages and sections, as a readability choice (Google doesn't require splitting content up) |
| Content structure | Title tags, meta descriptions, keyword targeting | Question-led headings with self-contained answers |
| Authority | Backlinks and topical depth | Named authors, cited sources, brand mentions across the web |
| Success metric | Rankings, clicks, organic traffic | Mention rate, citation rate, answer accuracy |
| Technical base | Crawlable, fast, indexable pages | The same, plus access for AI search crawlers |
Google is clear that the basics carry over. Its AI features page says "While specific optimization isn't required for AI Overviews and AI Mode, all existing SEO fundamentals continue to be worthwhile". Its newer optimisation guide goes further:
> While terms like Answer Engine Optimization (AEO) or Generative Engine Optimization (GEO) are common online, many suggested "hacks" aren't effective or supported by how Google Search actually works.
What kind of content tends to get cited?
Content that answers a question directly and completely. For buying decisions that often means comparison pages, specification guides and clear how-to steps, because they match how people ask AI tools to help them choose.
In practice:
- Phrase headings as the questions buyers actually ask, and answer in the first two sentences beneath.
- Put figures in tables, each with a named, dated source.
- Show real experience: worked examples, the steps you actually follow, the limits you've hit.
- Name the author and their role, and show the date the page was last updated.
- Use plain words, and define each technical term once.
These line up with Google's E-E-A-T framework (experience, expertise, authoritativeness and trust). I go deeper on the writing in how to write content that AI search engines actually cite, and on the wider strategy in how to rank in AI search results.
What does a technical GEO implementation framework include?
A technical GEO implementation framework is mostly good technical SEO with a few AI-specific checks. Pages must be indexed and eligible for a snippet, crawlers must be allowed in, key content must sit in the HTML, and structured data must describe the page accurately. For Google's AI features, there is one extra setting to confirm, and it is on by default.
Eligibility: indexing, snippets and one Search Console setting
For Google, a page must be indexed and eligible to show with a snippet to appear as a supporting link in AI Overviews or AI Mode. Google adds: "There are no additional technical requirements." A nosnippet or very low max-snippet directive limits what can be shown.
There is one setting worth checking. Google's guide says "a site must be included in Search generative AI features in Search Console to be eligible for display in generative AI features on Google Search." Search Console's help page says inclusion "is the default control for all properties", so the job is to confirm nobody has switched it off.
Crawler access and rendering
- Check robots.txt allows the crawlers you want, such as Googlebot, Bingbot, OpenAI's OAI-SearchBot, PerplexityBot, Anthropic's Claude-SearchBot and Applebot. Each vendor publishes its crawler names.
- If your site runs on Cloudflare and you want to keep search visibility, use its "Disallow AI Training" setting rather than Block. Since 15/09/2026, a Training Block also blocks Googlebot, Bingbot and Applebot.
- Google-Extended controls whether your content is used to train Gemini and the models behind Search generative AI features, and for grounding in Gemini apps and Vertex AI. It does not affect inclusion in Search. Inclusion in AI Overviews and AI Mode is controlled by the Search generative AI features setting, snippet controls and noindex.
- Serve key content and structured data in the initial HTML. Not every AI crawler renders JavaScript, so server-side rendering is the safe default.
- Keep HTTPS, fast load times and a clean heading hierarchy (H1, H2, H3).
- Treat llms.txt as optional. It's a proposed file that summarises your site for AI tools. Google says these files "aren't needed for Google Search (and won't negatively or positively impact your visibility or rankings)", and its guide adds that Google Search, including its generative AI features, "doesn't use them". No other major AI search engine documents using the file.
Structured data
Use JSON-LD, the format Google recommends. Structured data makes the facts on a page explicit and machine-readable, but it must match what's visible on the page. These types earn their place on most business sites:
- Organization, with your name, logo and contact details
- Article, with author, publish date and modified date
- BreadcrumbList, to show where the page sits on the site
- Product or Service, for comparison and specification pages
FAQ rich results stopped appearing in Google on 07/05/2026, according to Google's Search Central updates page, so FAQPage markup earns no Google feature. An on-page FAQ is still worth having, because readers use it and AI answers read it. Validate markup with Google's Rich Results Test and the Schema Markup Validator, and watch Search Console's enhancement reports for errors.
Images, video and voice
- Descriptive filenames and alt text on images
- Transcripts for video, so the content exists as text
- VideoObject markup on video pages
- Speakable markup only if you publish news, since Google supports it in limited cases
Freshness and recrawling
Bing said on 06/05/2026 that its index now puts more weight on accuracy, attribution and freshness when it supports AI answers, so review your key pages and update them when facts change. After a meaningful update, request a recrawl through URL Inspection in Search Console. Google notes that "Crawling can take anywhere from a few days to a few weeks."
For Copilot, verify your site in Bing Webmaster Tools and submit your sitemap there too. Bing also supports IndexNow, a protocol that tells search engines when a URL changes.
The check I run on a page
- URL Inspection in Search Console: is the page indexed, and are snippets allowed?
- robots.txt: are the AI search crawlers I care about allowed?
- View source: is the main content in the HTML, without waiting for scripts?
- Headings: does each read like a buyer's question, with the answer in the first two sentences?
- Live test: ask the page's main question on three or four AI platforms and note who gets named and linked.
How do you measure performance in generative AI engines?
Measure GEO with a fixed set of buyer questions, asked on the same platforms at regular intervals, alongside your own analytics. Track how often you're named, how often you're linked and whether the description is accurate. AI answers vary between runs, so the trend over months tells you more than any single check.
The metrics that matter
| Metric | What it tells you | Where it comes from |
|---|---|---|
| Mention rate | Share of tracked questions where your brand is named | Manual checks or a tracking tool |
| Citation rate | Share of tracked questions where your page is linked as a source | Manual checks or a tracking tool |
| Answer accuracy | Whether the AI describes your services, prices and location correctly | Manual review of each answer |
| AI referral visits | Sessions arriving from AI assistants | GA4 custom channel group or segment |
| Impressions and clicks | How Google Search, including AI features, surfaces your pages | Search Console Performance report |
| Google generative AI impressions | How often Google's generative AI features show your pages, by page, country, device and date. Impressions only, no clicks | Search Console Generative AI performance report |
| Bing AI citations | How often Copilot and Bing's AI summaries cite your pages, with Intents, Topics and Citation Share. Citation Share shows no competitor domains | Bing Webmaster Tools AI Performance |
A worked example
Say you track 20 buyer questions across four platforms each month. That's 80 checks. If you're named in 12 answers, your mention rate is 12 in 80; if your pages are linked in 5, your citation rate is 5 in 80. These numbers are illustrative, not a benchmark.
The figure to watch is the change. A move from 12 to 18 named answers over three months says more than either number alone. For tools, costs and when manual checks are enough, see my guide to AI visibility tracking.
Analytics: what you can and can't see
In GA4, build a custom channel group or segment that matches AI referrers such as chatgpt.com, perplexity.ai, gemini.google.com, copilot.microsoft.com and claude.ai. Clicks from AI Overviews and AI Mode arrive as ordinary Google organic traffic, so they don't separate out. Some AI visits carry no referrer at all and land in Direct.
Search Console still counts AI Overviews and AI Mode within its Web search totals. Since 31/08/2026, every property also has a separate Generative AI performance report, which shows impressions but no clicks. Fan-out can also inflate impressions relative to clicks, so read CTR alongside clicks and enquiries.
Automating the checks
Running 80 checks by hand every month is slow, repetitive admin, which makes it a good candidate for automation. At AI Agency Plus I build n8n workflows that ask a fixed question set on a schedule, log each answer to a spreadsheet, flag when your brand appears or drops out, and send a short monthly summary.
Answers pulled through an API can differ from what people see in the apps, so the workflow handles the bulk of the asking and logging while you spot-check the apps and read the answers that changed.
What future strategic considerations should shape your GEO plan?
Plan for AI answers to keep changing while the fundamentals stay put. Google's guide says "Creating content that people find unique, compelling, and useful will likely influence your website's presence in generative AI search in the long run more than any of the other suggestions in this guide." That's the safest bet.
Three shifts worth watching
- Agentic search. AI assistants are starting to compare options and complete tasks for users as well as answer questions. Clear prices, service areas and booking details help an agent represent you correctly.
- Mentions beyond your site. AI answers can draw on reviews, forums such as Reddit, LinkedIn posts and YouTube as well as company websites. Being discussed accurately where your buyers already read is part of GEO.
- Measurement gaps. ChatGPT, Perplexity and Claude share little data about AI answers today. A baseline built now lets you see change later.
When GEO isn't worth the spend yet
If your buyers find you through referrals or local word of mouth and rarely research suppliers with AI tools, heavy GEO work won't pay back quickly. Fix indexing, write clear service pages and run a handful of checks each quarter. Scale up when you see AI tools naming your competitors.
Where to start
Generative engine optimization comes down to being findable, quotable and accurate: indexed pages, open crawler access, self-contained answers, named sources and a steady way to measure what AI tools say about you. If you'd like help putting that in place, or automating the checks, Book a Discovery Call.
Frequently asked questions
Is generative engine optimization the same as SEO?
They overlap heavily. GEO uses the same foundations as SEO, such as indexing, crawlability and useful content, and adds a focus on being cited and described accurately inside AI answers. Google says existing SEO fundamentals stay worthwhile for its AI features.
Do I need llms.txt or special schema for AI Overviews?
No. Google says a page needs to be indexed and eligible for a snippet, with no additional technical requirements, and the Search generative AI features setting in Search Console must be left on (it is the default). Google also says llms.txt files aren't needed for Google Search and won't negatively or positively impact your visibility or rankings, because Google Search doesn't use them. Standard structured data such as Organization and Article markup still helps machines read your page.
How long does GEO take to show results?
Google says crawling can take from a few days to a few weeks after you ask it to recrawl a changed page. AI answers then vary from run to run, so judge progress on the trend across two or three months of checks.
What is the difference between GEO and AEO?
Answer engine optimization (AEO) and GEO are two names for overlapping work: making content easy for AI tools to use in their answers. Google's own guide notes both terms are common and warns that many suggested hacks aren't effective. The label matters less than the substance.
Can I see AI Overviews traffic separately in Search Console?
Partly. Search Console still counts AI Overviews and AI Mode within its Web figures in the Performance report. Since 31/08/2026, every property also has a separate Generative AI performance report, which shows impressions but no clicks. Pair it with a regular set of manual or automated checks to see where you're named and linked.