GEO Audit
A structured assessment of how well a brand is optimized for generative engines, spanning technical, content, off-site, and Share of Model signals.
A GEO Audit is a systematic evaluation of how prepared a brand is to be discovered and cited by generative AI engines. A thorough GEO audit covers four layers: technical GEO (crawler access, JavaScript rendering, server-rendered content, structured data, and discovery files), content and entity signals, off-site authority, and Share of Model measurement.
The technical layer is foundational because most LLM crawlers do not execute JavaScript. If critical content is injected client-side, AI crawlers see an empty page, so server-side rendering and SEO fundamentals are prerequisites. The audit then scores content quality, entity consistency, off-site citations, and finally how often the brand actually appears across AI models.
A repeatable GEO audit, run quarterly with lighter monthly checks and frequent Share of Model sampling, turns AI visibility from guesswork into a measurable, improvable process.
Related Terms
Generative Engine Optimization (GEO)
A framework for optimizing content specifically for AI-powered generative search engines that synthesize answers from multiple sources.
Share of Model
The percentage of AI-generated answers within a defined set of prompts where a brand appears, measured across one or more models.
JavaScript Rendering (AI Crawling)
Whether a crawler executes a page's JavaScript to see client-side content; most LLM crawlers do not, unlike Google Search.
AEO Vision Content Team
Insights on AI search visibility, answer engine optimization, and brand discovery across ChatGPT, Perplexity, Gemini, Claude, and Google AI Mode.
Track your GEO Audit performance
AEO Vision helps brands measure and improve their AI search visibility across every major platform.