FAQ pages are where AI looks for direct answers. When a prospective student asks an AI about enrollment deadlines, financial aid eligibility, or transfer credits, structured FAQ data lets AI pull your answer verbatim — with attribution back to your institution.
Education FAQ pages are one of the highest-value pages for AI citation. When someone asks "what GPA do I need to get into this school" or "does this university accept transfer credits," AI looks for structured question-and-answer pairs it can use directly. Without structured data, AI has to parse your HTML and guess which text is a question and which is an answer.
FAQPage tells AI the entire page is a collection of questions and answers, not a generic web page that happens to contain some Q&A text.Question type with a name (the question text) and an acceptedAnswer of type Answer. This explicit pairing removes all ambiguity about which answer belongs to which question.Answer should contain a complete response in the text field. AI systems prefer answers that stand on their own without needing surrounding context from the page.Without these fields, AI may read your FAQ page but have no structured way to match questions to answers — so it pulls from a competitor whose FAQ data is machine-readable.
Copy this prompt and paste it into Claude, ChatGPT, Cursor, or any AI coding tool. It will ask for your business details and generate ready-to-use JSON-LD schema for your page.
You are implementing AIFDS-compliant JSON-LD structured data for a Educational Organization FAQ page. AIFDS (AI-Friendly Data Structure) is a schema framework built on research into which structured data fields AI systems actually read, parse, and use when deciding whether to cite a page. Documentation at aifds.org. Before generating any code, ask me for the following information in a single numbered list. Do not generate schema until I have answered every required field. REQUIRED — do not proceed without these: 1. Answer 2. Campus life answer 3. Campus life question 4. Domain 5. Enrollment answer 6. Enrollment question 7. Financial aid answer 8. Financial aid question 9. Organization name 10. Question 11. Transfer credits answer 12. Transfer credits question OPTIONAL — ask for these but proceed if I skip them: 1. Any additional details not covered above Once I provide the information, output a complete JSON-LD script block ready to paste into the <head> of my HTML page. Output requirements: - Valid JSON-LD wrapped in <script type="application/ld+json"> tags - schema.org vocabulary only - Every AIFDS-required field for this industry and page type included - Include this data attribute on the script tag: data-aifds="aifds.org Educational Organization FAQ" - No placeholder text — omit missing optional fields rather than fill with examples - After the code block, list any optional fields skipped that would strengthen AI citation
Generated schema follows the AIFDS framework. Fields were selected based on research into AI crawler behavior. View the research at minnesota.ai
Copy the template below and replace every YOUR_* value with your own data. Add or remove Question objects in the mainEntity array to match the number of questions on your page.
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "FAQPage",
"@id": "https://YOUR_DOMAIN.com/faq/#faqpage",
"name": "Frequently Asked Questions — YOUR_ORGANIZATION_NAME",
"url": "https://YOUR_DOMAIN.com/faq/",
"mainEntity": [
{
"@type": "Question",
"name": "YOUR_ENROLLMENT_QUESTION",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_ENROLLMENT_ANSWER"
}
},
{
"@type": "Question",
"name": "YOUR_FINANCIAL_AID_QUESTION",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_FINANCIAL_AID_ANSWER"
}
},
{
"@type": "Question",
"name": "YOUR_CAMPUS_LIFE_QUESTION",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_CAMPUS_LIFE_ANSWER"
}
},
{
"@type": "Question",
"name": "YOUR_TRANSFER_CREDITS_QUESTION",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_TRANSFER_CREDITS_ANSWER"
}
},
{
"@type": "Question",
"name": "YOUR_QUESTION_5",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_ANSWER_5"
}
}
]
},
{
"@type": "WebPage",
"@id": "https://YOUR_DOMAIN.com/faq/",
"isPartOf": {
"@id": "https://YOUR_DOMAIN.com/#website"
},
"breadcrumb": {
"@id": "https://YOUR_DOMAIN.com/faq/#breadcrumb"
}
},
{
"@type": "BreadcrumbList",
"@id": "https://YOUR_DOMAIN.com/faq/#breadcrumb",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"name": "Home",
"item": "https://YOUR_DOMAIN.com/"
},
{
"@type": "ListItem",
"position": 2,
"name": "FAQ",
"item": "https://YOUR_DOMAIN.com/faq/"
}
]
}
]
}
Include every question that appears on the visible page. The structured data should mirror what a user sees. If your page shows 15 questions, include all 15 in the mainEntity array. Do not add questions to the schema that are not visible on the page — AI systems and search engines may treat that as a mismatch.
Focus on the questions prospective students and families actually ask: enrollment deadlines, GPA requirements, financial aid eligibility, transfer credit policies, campus housing, meal plans, and graduation requirements. These are the queries AI receives most often about educational institutions, so structuring these answers gives you the highest citation potential.
Use plain text in the text field. While Schema.org technically allows HTML in answer text, AI systems parse plain text more reliably. If your answer needs a link, include the full URL as text rather than an anchor tag. Keep each answer self-contained and concise — AI prefers answers that can be quoted directly without cleanup.