AI Visibility Methodology

AI visibility measures how often and how prominently AI engines recommend specific products and brands. GEO (Generative Engine Optimization) is the methodology for improving and tracking that visibility, just as SEO tracks search result rankings.

Every week, we query three AI engines — ChatGPT, Gemini, and Grok — using 8 category-specific prompts per engine. All data is collected via official APIs, not web interfaces.

Responses are processed by a separate LLM to extract brand mentions and their order of appearance. Extracted brands are matched against a canonical brand database with alias support.

Each brand receives an AI visibility score from 0 to 100:

• Appearance Rate — percentage of valid responses that mention the brand
• Avg Rank Score — exponential decay based on average position: 100 × e^{−0.15 × (avgRank − 1)}
• Model Coverage — fraction of engines that mention the brand (overall ranking only)

Individual engine rankings use a simplified formula without model coverage:

Rankings are not based on a fixed list. Each week, brands are dynamically discovered from AI responses. New brands are automatically added and scored. A human review process ensures brand names are properly normalized and deduplicated.

Rankings are updated weekly, every Monday. Data is labeled by the week's Monday date (e.g., "Week of 2026-07-27").