Practical guidance for evaluating search visibility and its relationship to qualified demand. Each article identifies its evidence, method, and limitations so you can assess what the findings or recommendations support.
Start with the measurement guide
Methodology guide · Version 1.1 · Prepared September 7, 2026
How to Measure AI Search Visibility Without Confusing It With Demand
A step-by-step protocol for separating mentions, citations, recommendations, referrals, qualified inquiries, and business outcomes. Includes explicit denominators, sampling limitations, current platform documentation, and a blank measurement worksheet.
Draft prepared by OpenAI Codex for Chuck Price. Documentation reviewed September 7, 2026; Chuck’s editorial review is pending. This is a proposed methodology, not an original quantitative study.
How to read the evidence
Documentation describes platform behavior using dated primary sources. Observations require captured evidence and stated collection conditions. Recommendations explain a proposed course of action and its limits.
The guide currently available in this draft collection contains no original dataset or client results. A methodology should be assessed on whether its definitions, counting rules, and limitations are explicit; it should not be mistaken for evidence that an intervention improved performance.
About the work
Chuck Price is Founder of Measurable SEO and a senior SEO and AI search consultant. Read about his background and published work.
For the engagement context behind a measurement discussion, see AI search consulting. To discuss a specific question, discuss your measurement approach.