Guides
How to Audit a Website for AI Search Readiness
AI search visibility starts with the same useful, crawlable and trustworthy content foundations as search—not a secret GEO tag.
Make the page accessible, distinctive, clearly owned and easy to verify. Allow the search crawler you want, then measure real referrals and citations over time.
Start with search eligibility and crawler access
AI-assisted discovery systems rely on accessible, crawlable web content. A page returning 4xx/5xx status, blocked by robots.txt, or carrying a noindex directive in meta tags or X-Robots-Tag has a basic discovery barrier. Ensure search crawlers like OAI-SearchBot and Googlebot can fetch the page reliably while controlling AI training bots like GPTBot separately in robots.txt.
Provide structured, extractable answers
Use one descriptive H1, specific H2 subsections, and concise answer paragraphs (between 80 and 320 characters) placed directly next to the questions they resolve. Retrieval-augmented generation (RAG) and answer synthesis engines extract well-defined passages far more reliably than vague marketing copy or deeply nested JavaScript widgets.
Establish entity clarity and authorship
Explicitly identify the responsible author, expert reviewer, or organization behind the content. Display honest publication and update dates (<time datetime='YYYY-MM-DD'>), and back entity claims with structured Schema.org markup (such as Organization or Person). Clear ownership signals allow AI systems and users to evaluate source authority and trustworthiness.
Cite primary sources and verifiable evidence
Place direct reference links and citations next to factual claims, statistics, and industry definitions. Linking to authoritative, primary documentation demonstrates rigor and allows AI systems to corroborate facts against trusted knowledge graphs.
Measure actual referrals instead of chasing guarantees
A single page audit cannot guarantee future AI citations or search placements. Monitor Search Console performance, track referral traffic with UTM parameters from AI search engines, and evaluate repeatable prompt samples over time while recognizing that AI responses remain dynamic and probabilistic.