AI Visibility Methodology

How WREMF measures AI visibility. Prompt sampling, answer snapshots, citation extraction, scoring methodology, and data freshness explained.

WREMF measures AI visibility by sending prompts to 10 AI engines, capturing answer snapshots, extracting brand mentions, citations, and recommendations, and computing visibility scores.

How It Works

1. Prompt sampling: curated and user-defined prompts sent to AI engines
2. Answer snapshots: full responses captured and versioned
3. Citation extraction: URLs and sources identified in responses
4. Brand detection: mentions, recommendations, and sentiment analyzed
5. Scoring: visibility index computed across engines and prompts