geo-fundamentals

To audit content for AI-citation readiness, analyze public web pages for structured data like JSON-LD, H1/H2 headings, author and date metadata, and FAQ sections. This generates per-page scores and actionable recommendations to improve machine-readable signals.

GEO optimization improves AI citations by adding machine-readable signals like JSON-LD and entity schemas to web content. Auditing semantic cues and metadata ensures AI models can reliably extract, understand, and cite your public-facing pages.

Check JSON-LD and H1/H2 structure by running an automated audit across your project's public-facing pages. The audit identifies missing structured data and heading hierarchy issues, then outputs a per-page score to guide deterministic improvements.

FAQ sections and author metadata are needed for better AI search extraction because they provide clear semantic cues. Including these signals alongside dates and structured data helps AI models reliably parse and cite your content.

The best way to score structured data across a website is to run an automated audit that evaluates JSON-LD, headings, and metadata. This generates an average GEO score and per-page recommendations to drive deterministic content improvements.

Content fails to get cited by AI models when it lacks machine-readable signals like JSON-LD, proper H1/H2 structure, and author metadata. Without these structured data elements, AI models struggle to reliably extract and verify the content.