AI Visibility Diagnosis
A multi-channel diagnostic process that measures how well a brand or website is discovered, cited, and accurately described by AI systems — covering SEO, AEO, GEO, and AAO
What is AI Visibility Diagnosis?
AI visibility diagnosis is the process of measuring how readily a brand, website, or piece of content is discovered, cited, or accurately described by AI systems such as ChatGPT, Claude, Gemini, and Perplexity — across four distinct channels: SEO, AEO, GEO, and AAO.
Strong traditional SEO does not guarantee presence in AI responses. Search engine ranking and AI citation follow different mechanics and respond to different signals. AI visibility diagnosis quantifies that gap and provides a prioritized improvement roadmap.
The Four Diagnostic Channels
SEO (Search Engine Optimization)
Classic search engine visibility: domain authority, backlinks, page speed, and mobile optimization. This is the foundational layer on which AI visibility is built.
AEO (Answer Engine Optimization)
Measures whether content is structured so AI can extract and cite it directly when answering questions. Evaluated signals include FAQPage schema, question-form headings, direct-answer paragraphs, and HowTo markup.
GEO (Generative Engine Optimization)
Tests whether a brand actually appears when live queries are sent to ChatGPT, Claude, and Gemini. Covers brand mention rate, per-LLM breakdown, competitor share-of-voice, and sentiment framing.
AAO (AI Agent Optimization)
Measures the probability that AI agents select a brand's API, service, or plugin when choosing tools for a task. An emerging discipline that grows in importance as AI agent ecosystems expand.
Full Diagnostic Signal Map
| Diagnostic Area | Signals Measured | Weight |
|---|---|---|
| Crawlability | AI bot access (GPTBot, ClaudeBot, PerplexityBot), llms.txt presence | Medium |
| Structured data | JSON-LD schema types and implementation quality | High |
| AEO readiness | Direct-answer paragraphs, FAQ coverage, HowTo structure | High |
| Citation signals | Authoritative outbound links, updatedAt freshness, author attribution | Medium |
| Page speed | Core Web Vitals: LCP, CLS, INP | Medium |
| LLM brand mention | Whether the brand appears in actual LLM responses | Very High |
AIVS Grade Scale
trensee's AI visibility diagnostic (AIVS) converts the composite score into five letter grades:
| Grade | Score | Meaning |
|---|---|---|
| A | 90+ | High likelihood of AI citation |
| B | 75–89 | Key signals met; minor gaps to address |
| C | 60–74 | Structural improvements needed |
| D | 45–59 | Foundational signals missing |
| F | ≤44 | Very unlikely to appear in AI responses |
→ Free AI visibility diagnostic at trensee GEO Check
Frequently Asked Questions
Q. Can a site with excellent SEO score poorly on AI visibility?
Yes. A site that ranks number one in Google can still score D on AI visibility if it lacks AEO structure (FAQ schema, direct-answer paragraphs, HowTo markup). The two sets of signals overlap partially but are not equivalent.
Q. How often should AI visibility be diagnosed?
A minimum of once per quarter is recommended, because LLMs are continuously updated. Re-diagnose immediately after publishing a large batch of new content or making structural changes to the site.
Q. What if AI is describing the brand incorrectly?
Run a GEO Probe diagnosis first to see exactly how each LLM currently describes the brand. Then strengthen accurate brand descriptions on owned channels — the website, press releases, and authoritative third-party sources — to correct the AI's framing over time.
Q. How is AI visibility diagnosis different from brand monitoring?
Brand monitoring tracks mentions in social media and news. AI visibility diagnosis measures how brands are cited and described specifically inside LLM-generated answers — different tools, different signals, different improvement strategies.