A dedicated FAQ page gives AI a structured bank of questions and answers about your accounting firm. Unlike FAQ nodes appended to other pages, a dedicated FAQ page uses FAQPage as the primary type, signaling to AI that this is the canonical source for common questions about your services, processes, and policies.
The FAQ page is where AI goes to find direct answers to the questions people actually ask about accounting firms. When someone asks "does this CPA firm handle small business taxes" or "what documents do I need for a tax consultation," a structured FAQ page gives AI a ready-made answer to surface. Without it, AI has to guess from paragraph copy.
FAQPage is the main schema type with its own @id, name, and url. This is different from the FAQ nodes used as supporting data on other blueprint pages.mainEntity array holds each Question and its acceptedAnswer. Each question should be written the way a real person would ask it, not as a marketing headline.about reference pointing to your AccountingService node tells AI these FAQs are specifically about your firm, not generic accounting questions.isPartOf linking to your website node places the FAQ page within your site hierarchy so AI understands this is an official page, not a standalone document.Each field in the template below serves a specific role in how AI systems discover, classify, and recommend your business.
Researched and tested by Minnesota AI
nameurlCopy 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 Accounting Service 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. Domain 3. Faq page title 4. Firm name 5. 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 Accounting Service 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 this template and replace every YOUR_* placeholder with your own data. Add or remove Question entries from mainEntity to match the number of FAQs on your page.
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "FAQPage",
"@id": "https://YOUR_DOMAIN.com/faq/#faqpage",
"name": "YOUR_FAQ_PAGE_TITLE",
"url": "https://YOUR_DOMAIN.com/faq/",
"isPartOf": {
"@id": "https://YOUR_DOMAIN.com/#website"
},
"about": {
"@id": "https://YOUR_DOMAIN.com/#organization"
},
"mainEntity": [
{
"@type": "Question",
"name": "YOUR_QUESTION_1",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_ANSWER_1"
}
},
{
"@type": "Question",
"name": "YOUR_QUESTION_2",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_ANSWER_2"
}
},
{
"@type": "Question",
"name": "YOUR_QUESTION_3",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_ANSWER_3"
}
},
{
"@type": "Question",
"name": "YOUR_QUESTION_4",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_ANSWER_4"
}
},
{
"@type": "Question",
"name": "YOUR_QUESTION_5",
"acceptedAnswer": {
"@type": "Answer",
"text": "YOUR_ANSWER_5"
}
}
]
},
{
"@type": "AccountingService",
"@id": "https://YOUR_DOMAIN.com/#organization",
"name": "YOUR_FIRM_NAME",
"url": "https://YOUR_DOMAIN.com"
},
{
"@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/"
}
]
}
]
}
On a dedicated FAQ page, FAQPage is the primary schema type with its own @id, name, url, and isPartOf. It represents the page itself. On other pages (like your services or contact page), a FAQPage node is a supporting element in the @graph that adds supplemental Q&A data. AI treats the dedicated version as the authoritative source for your firm's frequently asked questions.
Include every question that actually appears on your FAQ page. There is no strict upper limit, but every question in the schema must have a matching visible question on the page itself. If your page shows 12 questions, your schema should have 12 entries. Mismatches between visible content and structured data can hurt trust with both search engines and AI systems.
Keep FAQ answers in the text field as plain text. AI systems read the raw string value, so HTML tags inside the answer add noise without benefit. If your visible answer on the page includes links or bold text, that is fine for human readers, but the structured data version should be a clean, concise text summary of the answer.