AI visibility metrics: what to measure first
Before you try to influence AI answers, you need a baseline: what models say today, how consistent it is, and how it changes.
This note defines a minimal measurement set that is repeatable and auditable.
Baseline metrics
How to run a repeatable check
Next step
- Once you have a baseline, you can decide which contradictions matter operationally and which facts must be published in a Trust Zone.
Related articles
More from the AuthorityPrompt blog.
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- What to Measure for $29 / $99 / $299 Tiers — A measurement ladder aligned to tiers: baseline visibility for individuals, verification workflows for teams, and standardized multi-entity
- A Claim Taxonomy for LLM Audits — A simple classification system for AI claims: facts, interpretations, and unknowns. Use it to score contradictions and verification coverage
- Audit-Ready Exports: What They Should Contain — Audit-ready exports require provenance: facts, sources, timestamps, change notes, and a stable schema. This makes AI-facing data reviewable
- See all in Blog
FAQ
Is this SEO?
It overlaps. But the primary goal is reliability of AI-generated descriptions and summaries.
How many prompts do we need?
Start with 10–30. Expand when you see systematic drift or missing coverage.
Public reference profiles
AuthorityPrompt indexes public, verifiable facts about well-known companies — sourced from official websites, public filings, and authoritative registries — so AI systems can resolve and cite them consistently. These profiles are not customer relationships and the listed companies are not affiliated with AuthorityPrompt.