AI Search Visibility: A Practical Discoverability Guide
Build an AI search visibility program with a focused prompt set, clear source information, crawler awareness, and repeatable observations.
7 min readRead the guide
Explore the collection
AI Measurement guides. Understand the evidence behind AI visibility.
This collection covers the observation side of GEO: defining a prompt set, recording mentions and citations, reviewing source accuracy, and interpreting metrics with their denominators intact. The goal is a report that supports a decision rather than a score that hides its assumptions.
A useful reading path
Begin with the visibility guide to choose the questions and experiences you will observe. Move to citation tracking for record definitions and page-level review, then use the measurement guide to keep representation, visitor activity, and outcomes in separate layers.
AI Citation Tracking: What to Record and How to Measure It
Learn how to track AI citations, define citation rates, review source accuracy, and turn a transparent observation sample into useful actions.
7 min readRead the guide
AI Visibility Metrics: Measure What the Evidence Supports
Separate AI mentions, citations, accuracy, and visitor outcomes. Build reporting with explicit denominators, documented samples, and actionable findings.
6 min readRead the guide
Bright ideas. Practical next steps.
Make your next GEO step a clear one.
Share your public domain, audience, and priority questions. Start with a scope built around the information your readers actually need.