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FAQ Page Blueprint — Bar & Pub

FAQ pages are where AI looks for direct answers. When someone asks "Does this bar allow dogs?" or "Do they have happy hour on Wednesdays?" structured FAQ data lets AI pull your answer verbatim — with attribution back to your bar.

View Prompt View JSON

What this page needs

FAQ pages are one of the highest-value pages for AI citation. When someone asks an AI "what time does this bar close on Sundays" or "can I bring a group of 20," 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 as primary type. Declaring the page as 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.
mainEntity with Question/Answer pairs. Each question uses the 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.
Clear, self-contained answers. Each 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.
Bar-specific questions. Cover the questions people actually ask about bars: capacity, dress code, age policy, pet policy, happy hour times, private event availability, and parking.

Why these fields matter to AI

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

BarOrPub

name: Non-negotiable. AI cannot cite or recommend an unnamed entity.
url: AI needs a stable URL to route users and attribute recommendations.

Use This Prompt to Implement Your Schema

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 Bar or Pub 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. Bar name
3. Domain
4. 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 Bar or Pub 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

Template — fill in your values

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_BAR_NAME",
      "url": "https://YOUR_DOMAIN.com/faq/",
      "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": "BarOrPub",
      "@id": "https://YOUR_DOMAIN.com/#business",
      "name": "YOUR_BAR_NAME",
      "url": "https://YOUR_DOMAIN.com"
    },
    {
      "@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/"
        }
      ]
    }
  ]
}

Frequently asked questions

How many questions should I include in the FAQPage schema?

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 may treat that as a mismatch.

What types of questions work best for a bar FAQ?

Focus on the questions people actually ask before visiting: "Do you have happy hour?" "Is there a dress code?" "Can I reserve space for a party?" "Do you allow dogs on the patio?" "What time does the kitchen close?" These are the queries AI receives most often about bars, and structured answers let AI respond with your exact policies.

Should answers include HTML formatting or just plain text?

Use plain text in the text field. While Schema.org technically allows HTML in answer text, AI systems parse plain text more reliably. Keep each answer self-contained and concise — AI prefers answers that can be quoted directly without cleanup.