Field Guide
What is Generative Engine Optimization (GEO)?
Generative Engine Optimization (GEO) is the practice of improving how AI assistants — ChatGPT, Claude, Gemini, and others — cite, describe, and recommend your brand. As people increasingly ask AI for product recommendations instead of scrolling search results, being named inside the answer is becoming as important as ranking #1 ever was.
GEO vs SEO: what changed
Search engine optimization (SEO) earns you a link in a ranked list — the user still clicks through and decides. Generative Engine Optimization earns you a mention inside a synthesized answer, where the AI has already done the choosing. The underlying fundamentals overlap: clear, well-structured content and genuine authority help in both. But GEO adds a layer of AI-specific signals, and it shifts the goal from ranking to being referenced.
How AI engines decide what to cite
Generative models draw on their training data and, increasingly, real-time retrieval. When someone asks “what’s the best tool for X?”, the model assembles an answer from the brands it has seen described clearly and repeatedly across sources it trusts — documentation, review platforms (G2, Capterra), communities (Reddit, Stack Overflow), comparison articles, and your own site. Brands that are ambiguous, thinly documented, or absent from those sources simply don’t make the cut.
The building blocks of GEO
- llms.txt — A structured file at your site root that tells AI models what you do, who you serve, and how you compare — like robots.txt, but for language models.
- Structured data — Schema.org / JSON-LD markup so models can unambiguously parse your category, features, and pricing.
- FAQ content — Natural-language question-and-answer pairs that mirror how people actually prompt AI — the format models love to quote.
- Comparison pages — “You vs Competitor” content that AI references directly when users ask comparison questions.
- Third-party presence — Listings and reviews on the platforms models trust (G2, Capterra, TrustRadius) and active, helpful participation in relevant communities.
Why GEO matters now
AI assistants are becoming the default starting point for product research. If a model doesn’t mention you, you’re invisible to that buyer — and unlike search, there’s no second page to scroll to. GEO is how you make sure the answer includes you.
Measure your AI visibility first
You can’t improve what you can’t see. A free meraGEO scan shows exactly how often ChatGPT, Claude, and Gemini mention your brand — and where competitors are named instead.
Run a free scanThen read The AI Visibility Guide for the step-by-step playbook.
GEO FAQ
What does GEO stand for?
GEO stands for Generative Engine Optimization — the practice of improving how generative AI assistants (ChatGPT, Claude, Gemini, and others) cite, describe, and recommend your brand when users ask questions.
Is GEO the same as SEO?
No. SEO optimizes for search engine result rankings — getting links to appear in a list. GEO optimizes for being mentioned inside an AI assistant's generated answer. They share fundamentals (clear content, structured data, authority) but GEO adds AI-specific signals like llms.txt, FAQ content, comparison pages, and presence on the third-party sources AI models trust.
How do AI assistants decide which brands to mention?
Generative engines draw on their training data and, increasingly, live retrieval. They favor brands that are clearly described, frequently referenced across reputable third-party sites (review platforms, communities, comparison content), and easy to parse via structured data and llms.txt.
How do I measure my GEO performance?
Run an AI visibility scan: query the major models with real-world prompts in your category and measure how often, and how prominently, your brand is mentioned versus competitors. meraGEO does this automatically across ChatGPT, Claude, and Gemini.