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FAQs Page Blueprint — Ecommerce

FAQ pages structure your shipping, returns, and ordering answers so AI can quote them directly to shoppers. When someone asks "does this store offer free returns?" AI needs a structured answer it can cite with confidence. This blueprint makes your FAQ page the definitive source for those answers.

View Prompt View JSON

What this page needs

The FAQ page is one of the highest-value pages for AI discoverability. Every question-answer pair becomes a discrete fact that AI can extract and serve. The page must declare itself as a FAQPage with a structured array of questions and answers.

FAQPage as primary type. The FAQPage node is the primary entity on this page, not a supplementary addition. Its mainEntity array contains every question-answer pair AI can extract.
Question and Answer pairs. Each entry in mainEntity is a Question with an acceptedAnswer of type Answer. Keep answers clear, specific, and self-contained — AI will quote them verbatim.
Connection to store Organization. Linking the FAQ page to your Organization tells AI these answers are official store policy, not user-generated content or third-party opinions.
Clear, specific answers. Avoid vague language. Instead of "we have a great return policy," say "we accept returns within 30 days of delivery for a full refund." AI needs concrete facts to cite.

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

WebSite

@id: All other schema nodes reference this ID. Without it the graph is disconnected.

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 Ecommerce 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. 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 Ecommerce 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. This block belongs in a <script type="application/ld+json"> tag in the <head> of your FAQ page.

{
  "@context": "https://schema.org",
  "@graph": [
    {
      "@type": "FAQPage",
      "@id": "https://YOUR_DOMAIN.com/faq/#faqpage",
      "url": "https://YOUR_DOMAIN.com/faq/",
      "name": "Frequently Asked Questions",
      "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"
          }
        }
      ],
      "about": {
        "@id": "https://YOUR_DOMAIN.com/#organization"
      }
    },
    {
      "@type": "WebPage",
      "@id": "https://YOUR_DOMAIN.com/faq/#webpage",
      "url": "https://YOUR_DOMAIN.com/faq/",
      "name": "Frequently Asked Questions",
      "isPartOf": {
        "@type": "WebSite",
        "@id": "https://YOUR_DOMAIN.com/#website"
      }
    },
    {
      "@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": "FAQs",
          "item": "https://YOUR_DOMAIN.com/faq/"
        }
      ]
    }
  ]
}

Frequently asked questions

How many question-answer pairs should I include?

Include every question that customers actually ask. There is no upper limit, but aim for at least five to ten pairs covering shipping, returns, payment methods, and order tracking. Each pair is a discrete fact AI can extract, so more well-written pairs means more opportunities for your store to appear in AI responses.

How often should I update my FAQ structured data?

Update it whenever your policies change. If you extend your return window for the holidays, update the answer. If you add a new payment method, add a new Q&A pair. Stale FAQ data is worse than no data — AI systems may cite outdated information, which erodes customer trust in both the AI and your store.

What is the difference between an FAQ page and product-level FAQs?

The FAQ page covers store-wide policies — shipping, returns, payment, ordering. Product-level FAQs answer questions specific to a single product, like sizing, materials, or compatibility. Both are valuable, but they serve different purposes. The store FAQ page handles "does this store ship internationally?" while the product FAQ handles "does this lamp come with a bulb?"