Generative engine optimization (GEO) is the practice of making your content and brand more likely to be found, quoted and cited in answers from AI engines such as ChatGPT, Gemini, Perplexity and Google AI Overviews. Where SEO aims for a ranking position, GEO aims for a mention or citation inside the generated answer itself.
The term comes from a 2023 research paper by researchers at Princeton University and IIT Delhi, which showed that specific content changes can raise a source’s visibility in AI answers. This guide explains what GEO is, how it differs from SEO and AEO, how AI engines pick sources, the tactics that hold up, and how to measure results.
Key takeaways
- GEO means optimising to be cited or mentioned in AI-generated answers, not only to rank in a list of links.
- The original GEO paper found that adding quotations, statistics and citations raised visibility, while keyword stuffing hurt it.
- Good SEO is the base layer: Google says there are no special requirements for AI Overviews beyond being indexed and eligible for a snippet.
- The tactics that work are extractable answers, clear entity information, cited facts, structured data, freshness and third-party mentions.
- Measure GEO with share of model across a fixed prompt set and with AI referral traffic in GA4’s AI Assistant channel.
Check your GEO readiness in 2 minutes
Answer six quick questions about how your brand shows up outside your own website and get a 0 to 100 score with a prioritised list of fixes. Try the free TechMachaw GEO readiness score checker, then use this guide to work through the gaps.
What is generative engine optimization?
Generative engine optimization is the work of making content easy for AI systems to find, understand, trust and quote. It covers how a page is written (clear, self-contained answers backed by sources), how your brand is described across the web, and whether AI crawlers can access your pages. Success is measured by how often AI answers mention or cite you.
A generative engine is any system that answers a question by writing a response, often with links to sources, instead of just returning ten blue links. ChatGPT with search, Perplexity, Gemini, Microsoft Copilot and Google’s AI Overviews and AI Mode all fit that description.
The shift for marketers is simple to state. In classic search, a user saw your title and chose to click. In an AI answer, the engine has already read your page and decided whether your words, facts or brand name deserve to appear. If they do not, you are invisible even when your page ranks well.
Where did GEO come from? The 2023 research paper
The term GEO was introduced in the paper “GEO: Generative Engine Optimization” by Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande, first posted in November 2023 and published at KDD 2024. It introduced GEO-bench and reported that GEO methods could boost visibility in generative engine responses by up to 40%.
The GEO paper on arXiv tested nine ways of rewriting a source page and measured how much of each source showed up in AI answers. The authors tested a simulated engine and the live Perplexity engine. Their results are the most cited evidence in the field, so it is worth knowing what they actually found:
| Method tested | What it means | Result in the paper |
|---|---|---|
| Quotation addition | Adding quotes from credible sources | Among the best performers |
| Statistics addition | Replacing vague claims with numbers | Among the best performers |
| Cite sources | Linking claims to relevant sources | Strong improvement |
| Fluency optimisation | Making text read more smoothly | Strong improvement |
| Keyword stuffing | Repeating query terms, old-style SEO | Performed worse than the unmodified page |
The paper also stressed that results vary by domain, so a tactic that works for history questions may not work for product comparisons. Treat it as direction, not a recipe. The core lesson holds up: engines reward content that is specific, sourced and easy to lift into an answer.
What is the difference between GEO, SEO and AEO?
SEO optimises pages to rank in search results and earn clicks. AEO, answer engine optimisation, focuses on being the direct answer in featured snippets, voice assistants and AI answers. GEO focuses on being cited or mentioned in AI-generated responses across chat and search engines. In practice they overlap heavily, and GEO builds on strong SEO rather than replacing it.
| SEO | AEO | GEO | |
|---|---|---|---|
| Goal | Rank and earn clicks | Be the direct answer | Be cited or mentioned in AI answers |
| Where it shows | Search results pages | Featured snippets, voice, AI answers | ChatGPT, Gemini, Perplexity, AI Overviews and AI Mode |
| Unit of success | Position, clicks | Answer box ownership | Mentions, citations, share of model |
| Main levers | Relevance, links, technical health | Question-led structure, concise answers | Extractable answers, entity clarity, sources, third-party mentions |
| Measurement | Search Console, rank trackers | Snippet tracking | Prompt tracking, GA4 AI Assistant channel |
| Time to impact | Weeks to months | Weeks | Varies by engine and how often it refreshes sources |
Some vendors say AEO and GEO are the same thing with different names. That is a fair view. The label matters less than the work, and the work starts with pages that already deserve to rank.
How do AI engines choose which sources to cite?
Most AI engines with web access retrieve pages from a search index, then the model reads them, writes an answer and cites its sources. Pages get picked when they are indexed, open to the engine’s crawler, relevant, and contain a precise passage worth quoting. Brand mentions also come from what the model learned in training.
Two separate paths put your brand in an answer:
- Retrieval (live search). The engine searches, reads a handful of pages and cites them. Here classic SEO signals, crawl access and clear passages matter most. OpenAI says sites that opt out of its search crawler will not be shown in ChatGPT search answers, so check your robots.txt allows OAI-SearchBot if you want to appear.
- Training memory. When an engine answers without searching, it relies on patterns learned from training data. Brands mentioned often, consistently and in trusted places are more likely to come up.
For Google specifically, its guidance on AI features and your website says there are no additional requirements or special optimisations to appear in AI Overviews or AI Mode. A page must be indexed and eligible to show with a snippet. That is the clearest statement that GEO sits on top of SEO.
What are the most effective GEO tactics?
The most reliable GEO tactics are writing self-contained answers under question-style headings, adding sourced statistics and quotations, making your brand facts consistent everywhere, using structured data that matches visible content, keeping pages fresh with dated updates, and earning mentions on third-party sites that engines already trust, such as reviews, forums and comparison pages.
1. Write extractable answers
Put a 40 to 60 word answer directly under each question heading, written so it makes sense if lifted out alone. Start with the direct answer, then add the condition or number. This page uses that pattern in every boxed answer.
2. Make your entity clear
An entity is a thing the engine can identify: your brand, product or founder. Use the same brand name, description, category and key facts on your site, social profiles, directories and review sites. Add Organization structured data on your home page. Conflicting descriptions make engines less confident about what you are.
3. Cite sources and add real numbers
Replace “many marketers” with a sourced figure and a link. This is the tactic with the strongest evidence from the GEO paper. Never invent numbers: an AI engine repeating a made-up statistic under your name is a reputation risk.
4. Use structured data honestly
FAQ, HowTo, Product, Review and Organization markup help machines parse a page. Google notes structured data must match the visible text on the page. Markup is not a shortcut to citations, but it removes ambiguity.
5. Keep content fresh
Add a visible “last updated” date and actually update facts, prices and platform details. Engines answering “best X in 2026” favour pages that clearly cover 2026.
6. Earn third-party mentions
AI answers about “best”, “top” and “vs” questions often draw from reviews, forums, videos and comparison articles, not brand sites. Being listed, reviewed and discussed in those places is often the biggest lever. Our follow-up guide on how to get your brand mentioned in ChatGPT, Gemini and Perplexity turns this into a step-by-step playbook.
How do you measure GEO? Share of model and AI referral traffic
Measure GEO with two numbers. Share of model is the percentage of AI answers, across a fixed set of prompts and engines, that mention your brand. AI referral traffic is the visits and conversions that arrive from AI assistants, which GA4 now reports in an AI Assistant default channel. Track both monthly against competitors.
Formula: Share of model = (Answers that mention your brand ÷ Total answers checked) × 100
It is the AI version of share of voice, which we cover in our guide to share of voice in advertising.
Example (illustrative numbers): Say a project management software brand tracks 30 buyer prompts, such as “best project management tool for agencies in India”, in four engines. That gives 120 answers a month.
| Brand | Answers mentioning brand | Share of model | Answers citing brand’s own site |
|---|---|---|---|
| Your brand | 18 of 120 | 15% | 6 |
| Competitor A | 54 of 120 | 45% | 21 |
| Competitor B | 33 of 120 | 27.5% | 9 |
The gap to Competitor A is 30 points. If Competitor A is mentioned mostly through review sites and Reddit threads where you are absent, your fix is off-site presence, not more blog posts.
For traffic, Google Analytics added an AI Assistant channel to its default channel groups in 2026, covering visits from assistants such as ChatGPT, Gemini and Claude. Two limits: AI Overviews and AI Mode clicks count as Google organic search, not AI Assistant, and visits that arrive without a referrer land in Direct. If your property predates the change or you need custom rules, build a custom channel group, and tag any links you control with consistent UTM parameters.
Example: if the AI Assistant channel brings 900 sessions a month with 36 sign-ups (4%), and organic search brings 30,000 sessions with 600 sign-ups (2%), AI referrals are small but convert at twice the rate. That is a reason to invest, even before volume grows.
What this means for marketers and creators
For marketers: Start with a baseline: list 20 to 40 prompts your buyers actually ask, check them in ChatGPT, Gemini, Perplexity and Google, and record who gets mentioned. Fix the basics first (crawl access, indexing, consistent brand facts, extractable answers), then put effort into reviews and comparison pages where competitors appear and you do not. Report share of model next to organic search, not instead of it.
For creators: AI engines already cite YouTube videos, podcasts and forum answers. Give each video or post a clear, searchable title, a transcript or description that answers the question in plain words, and consistent naming across platforms. Being the quoted expert in a niche is a real advantage: brands will pay creators whose content AI engines already surface.
Common GEO mistakes to avoid
The biggest GEO mistakes are treating it as separate from SEO, blocking AI crawlers by accident, stuffing keywords, publishing unsourced or invented statistics, describing your brand differently on every platform, and measuring with a handful of random prompts. Each makes you harder to cite or makes your results impossible to trust.
| Mistake | Why it hurts | Fix |
|---|---|---|
| Blocking OAI-SearchBot or other search crawlers | Not eligible for those engines’ live answers | Review robots.txt and CDN bot rules |
| Keyword stuffing | The GEO paper found it lowered visibility | Write for the question, not the keyword count |
| Invented statistics | Engines may repeat them, and trust drops | Link every number to its source |
| Inconsistent brand descriptions | Engine is unsure what you are | One boilerplate used everywhere |
| Random prompt checks | Answers vary run to run | Fixed prompt set, same engines, monthly |
| Ignoring off-site sources | Competitors win “best” and “vs” answers | Reviews, forums, videos and comparison pages |
Prompt wording affects what engines return, so write your tracking prompts the way customers actually ask. Our guide to prompt engineering for marketers helps you build a realistic prompt set. For the media planning terms used across this series, see the digital media planning glossary.
Frequently asked questions
What is generative engine optimization in simple terms?
Generative engine optimization, or GEO, is making your content and brand easy for AI tools like ChatGPT, Gemini, Perplexity and Google AI Overviews to find, trust and quote. Instead of only chasing a ranking, you aim to be mentioned or cited inside the AI-written answer that people read.
Is GEO replacing SEO?
No. GEO builds on SEO. AI engines that search the web still need your pages to be crawlable, indexed and relevant, and Google says there are no special requirements for AI Overviews beyond normal Search eligibility. GEO adds extra focus on extractable answers, entity clarity, sources and third-party mentions.
What is the difference between GEO and AEO?
AEO, answer engine optimisation, focuses on becoming the direct answer in snippets, voice assistants and AI results. GEO focuses on being cited or mentioned in generated AI responses. The two overlap so much that many marketers treat them as the same discipline with different names. The practical work is largely identical.
Who coined the term generative engine optimization?
The term comes from the paper GEO: Generative Engine Optimization by Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande, with authors from Princeton University and IIT Delhi. It was first posted in November 2023 and published at KDD 2024.
How do you measure GEO success?
Track share of model, the percentage of AI answers across a fixed prompt set and set of engines that mention your brand, and compare it with competitors monthly. Also track AI referral sessions and conversions in GA4, which now has an AI Assistant default channel for visits from assistants such as ChatGPT and Gemini.
Does structured data help with AI search?
Structured data helps machines understand what a page is about, such as a product, an FAQ or an organisation, which reduces ambiguity. It does not guarantee citations. Google says structured data must match the visible text on the page, so use it to describe content that is really there.
How long does GEO take to work?
It depends on the engine. Changes to pages that engines retrieve live can show up once the page is recrawled, sometimes within weeks. Changes that depend on training data, such as how often your brand is mentioned across the web, take longer. Track a fixed prompt set monthly to see the trend.
Next steps: Get your baseline with the free GEO readiness score checker. It takes about two minutes and gives you a prioritised list of fixes to start this week. Then list your 20 to 40 buyer prompts and record who AI engines mention today.
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