GlossaryAI search
What is generative engine optimization (GEO)?
Also called: GEO, AI SEO, LLM SEO, AI search optimization
Definition
Generative engine optimization (GEO) is the practice of making your content more likely to be found, used and cited in answers from AI systems like ChatGPT, Perplexity, Claude, Gemini and Google's AI Overviews.
Generative engine optimization (GEO), explained
The term comes from a 2023 research paper, "GEO: Generative Engine Optimization" by Aggarwal and colleagues, later published at KDD 2024. It described generative engines as systems that gather and summarize information to answer queries using large language models, and tested which content changes made sources more visible in those answers. In their experiments, adding citations to sources, quotations and statistics made content noticeably more visible, while keyword stuffing offered little to no improvement. Results varied by domain.
In practice, GEO sits on top of SEO rather than replacing it. Most AI assistants that answer with links run a web search first, then read and cite some of the results. OpenAI uses OAI-SearchBot to surface websites in ChatGPT's search features. Google's AI Overviews and AI Mode draw from pages in Google's index that are eligible for a snippet. Perplexity uses its own crawler, PerplexityBot. If you're not crawlable and indexed, you can't be cited.
What helps beyond ranking: pages that answer a question clearly near the top, in a sentence that can be quoted on its own; specific facts with sources; original data others can't copy; consistent descriptions of your product across your site, directories and reviews; and robots.txt rules that let AI search crawlers in. Google says no special markup or files are needed for its AI features.
What doesn't help much: invented statistics, walls of keywords, and files promising to "rank you in ChatGPT". Assistants tend to prefer sources that other sources agree with, so the same fundamentals that earn links and trust also earn citations.
Measuring GEO is still rough. Answers vary between runs, users and models, and most assistants don't report impressions. The usual approach is tracking a fixed set of prompts over time and counting mentions and citations.
Why it matters for founders
More buyers now ask an assistant before they search. If your product isn't in those answers, you miss people who never reach a results page. The good news: most of the work is the same work that makes you rank.
Example
Someone asks ChatGPT for "launch platforms that give a followed link without a badge". It searches, finds a comparison page that states this clearly with sources, and cites it in the answer.
Common mistakes
- Treating GEO as a separate discipline and neglecting basic SEO.
- Blocking AI search crawlers while wanting to be cited by AI search.
- Adding made-up statistics because the paper said statistics help.
- Measuring from one-off manual prompts instead of a tracked prompt set.
Sources
- Aggarwal et al., GEO: Generative Engine Optimization (arXiv, KDD 2024)
- Google Search Central: AI features and your website
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Related terms
- Answer engine optimization (AEO)Answer engine optimization (AEO) is structuring content so that systems which answer questions directly, such as featured snippets, voice assistants and AI chatbots, can pick it up and present it as the answer.
- LLM citationAn LLM citation is a link or named source that an AI assistant shows alongside its answer to say where information came from. Being cited sends referral traffic and signals that your page was trusted.
- AI OverviewsAI Overviews are AI-generated summaries Google shows at the top of some search results, with links to supporting pages. AI Mode is Google's separate, conversational search experience built on the same idea.
- AI share of voiceAI share of voice is how often your brand is mentioned or cited in AI assistants' answers to a fixed set of relevant prompts, compared with competitors. It's the AI-search version of share of search.