What is generative engine optimization (GEO)?

By the Variask team · Updated

In short

Generative engine optimization (GEO) is the practice of making your brand and content more likely to be mentioned, cited and recommended in answers written by AI assistants such as ChatGPT, Gemini, Claude, Perplexity and Google AI Overviews.

Key facts

  • GEO targets answers written by AI, while classic SEO targets ranked lists of links.
  • The term comes from a 2023 research paper by Princeton, Georgia Tech, the Allen Institute for AI and IIT Delhi.
  • Success is measured by how often AI names you, where it ranks you and which pages it cites.
  • AI answers vary from one ask to the next, so GEO results are best read as ranges over many answers.

How GEO works

When someone asks an AI assistant a question, it writes one answer instead of showing ten links. That answer draws on what the model learned in training and, for most assistants today, on pages it fetches live from the web. GEO improves your odds at both stages: being well represented in what models already know, and being the page an assistant finds and quotes when it searches.

Because the assistant picks a handful of brands to name, the gap between being mentioned and being left out is large. A brand that ranks fifth on Google can still be the first name in an AI answer, and the reverse is common too.

GEO vs SEO

  • Output: SEO competes for positions in a list of links. GEO competes for a mention inside one written answer.
  • Signals: SEO leans on links, relevance and page experience. GEO also rewards clear facts, quotable passages, third party mentions and consistent information about you across the web.
  • Measurement: SEO tracks rankings and clicks. GEO tracks visibility, position in the answer, share of voice, sentiment and cited sources.
  • Overlap: a crawlable, fast, well structured site helps both. GEO builds on good SEO rather than replacing it.

What improves GEO results

  1. 1Let AI crawlers in. Check that robots.txt and your firewall allow search crawlers like OAI-SearchBot, Claude-SearchBot and PerplexityBot.
  2. 2Answer the question in the first lines. Put a direct, self contained answer at the top of each page, then the detail.
  3. 3Add facts AI can quote: prices, specs, comparisons, dates and named sources, written plainly.
  4. 4Mark up your pages with structured data such as Organization, Product, FAQPage and Article.
  5. 5Earn mentions on the sites AI cites for your topic: reviews, forums, news and comparison pages.
  6. 6Fix wrong facts. If an assistant repeats an old price or feature, update the pages it is likely reading.
  7. 7Measure across engines and markets, and act only on changes that are bigger than normal answer to answer noise.

How to measure GEO

Track a fixed set of the questions your customers ask, in their country and language, across every major assistant. For each answer, record whether you were named, your position, the sentiment of the sentence and the sources cited. Ask each question more than once: the spread between answers tells you how confident to be in any single score.

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Questions

Generative engine optimization (GEO):
common questions

They overlap. Answer engine optimization (AEO) is the broader idea of optimizing for any system that returns a direct answer, including featured snippets and voice assistants. GEO focuses on answers written by generative AI models.

No. Most AI assistants search the web before answering, so a crawlable, well ranked, well structured site is still the base. GEO adds work on quotable content, third party mentions and measuring AI answers directly.

Answers that rely on live web search can change within days of a page being published and crawled. Changes to what a model knows from training take much longer, often until its next update.

University

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