Living benchmark
AI Visibility Benchmark 2026
A reproducible scoring framework for measuring whether a brand is named, cited, recommended, and accurately understood across ChatGPT, Claude, Gemini, Perplexity, Copilot, and Grok.
8
weighted dimensions
6
AI answer engines
100
point visibility score
What this benchmark measures
AI visibility is not a single ranking. A brand can be visible without being cited, cited without being recommended, or recommended with inaccurate positioning. This benchmark separates those outcomes so teams can diagnose the exact failure point.
| Dimension | Weight | What it means |
|---|---|---|
| Direct brand mention | 20% | Whether the engine names the brand as an answer, option, or recommendation. |
| Citation or source link | 18% | Whether a Georion-owned URL is linked or clearly used as source material. |
| First-answer position | 14% | Whether the brand appears early enough to influence the user's decision. |
| Sentiment and fit | 12% | Whether the answer describes the brand accurately and in a positive, relevant context. |
| Competitor displacement | 12% | How often competitors appear instead of or above the tracked brand. |
| Entity confidence | 10% | Whether the engine understands what the brand is, who it serves, and what category it belongs to. |
| Third-party corroboration | 8% | Whether external pages, forums, directories, and mentions reinforce the answer. |
| Freshness | 6% | Whether recent pages, discussions, and changelog signals are visible in the answer corpus. |
Engine coverage
Each engine has a different citation surface and failure mode. The benchmark is engine-specific first, then rolled into a blended score so teams can see where they are strong or invisible.
ChatGPT
OpenAI
Surface: Search, browsing answers, memory-influenced recommendations
Common risk: Brand absent in comparison prompts
Claude
Anthropic
Surface: Research answers and document-grounded recommendations
Common risk: Weak source clarity and shallow evidence
Gemini
Surface: Google-connected answers and AI Overviews adjacent behavior
Common risk: Entity ambiguity and weak Google indexation
Perplexity
Perplexity
Surface: Citation-heavy answer pages
Common risk: Competitors own listicles and third-party mentions
Copilot
Microsoft
Surface: Bing-connected answers
Common risk: Missing Bing index and weak exact-match pages
Grok
xAI
Surface: Real-time social/contextual answers
Common risk: Low social proof and sparse public discussion
Prompt set design
The benchmark uses five prompt classes because users do not only ask “what is this brand?” They ask for alternatives, recommendations, comparisons, category leaders, and fixes to real problems.
- Brand awareness prompts
- Category recommendation prompts
- Competitor comparison prompts
- Problem-solution prompts
- Commercial investigation prompts
- Implementation and technical prompts