How to add FAQ schema to boost AI citations
Implement FAQPage JSON-LD markup that AI models use as a direct source when answering questions about your brand.
- 1
Identify your most-asked questions
Collect questions from customer support tickets, sales calls, Google Search Console queries, and AI model responses about your brand. Focus on questions users would ask an AI assistant about you.
- 2
Write concise, factual answers
Each answer should be 50-150 words. Start with a direct one-sentence response, then provide supporting details. Avoid marketing language - AI models prefer factual, neutral answers they can cite directly.
- 3
Build the FAQPage JSON-LD
Create a JSON-LD script with @type FAQPage containing an array of Question entities. Each Question needs a name (the question text) and an acceptedAnswer with @type Answer and a text property containing your answer.
- 4
Add the schema to your pages
Place FAQPage schema on your dedicated FAQ page, product pages, pricing page, and any page where FAQ sections appear. Each page should only have questions relevant to that page's topic.
- 5
Validate with testing tools
Run every page through Google Rich Results Test and Schema.org Validator. Fix all errors. Warnings about recommended fields should also be addressed for maximum AI model coverage.
- 6
Update questions based on AI model feedback
Run a RankSignal scan after implementing FAQ schema. If AI models still get specific facts wrong, add targeted FAQ entries that directly answer those questions with correct information. Re-scan to verify.
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RankSignal.ai scans ChatGPT, Claude, Gemini, Perplexity, and Grok to show how AI models perceive your brand. Try a free scan.
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