Schema.org in Practice

3.1 What is Schema.org

Schema.org is a structured data standard created jointly by Google, Microsoft, Yahoo, and Yandex. It defines a unified vocabulary that turns web page content into machine-readable data. Plain-language explanation: Your product page displays “Nike Air Max 90, $129.99, In Stock.” A human reads that instantly, but a machine sees only a string of text. Schema.org markup tells the machine: this is a Product, the name is “Nike Air Max 90,” the price is “129.99 USD,” and the availability is InStock. Impact on AI agents: AI agents (ChatGPT, Claude, Gemini, etc.) prioritize pages with structured data when making product recommendations, because they can extract product information accurately and reduce hallucination.

3.2 Three Implementation Formats

Format	Recommendation	Description
JSON-LD	Recommended	Officially recommended by Google. A standalone `script` tag that does not affect HTML structure
Microdata	Acceptable	Embedded in HTML tag attributes (`itemprop`, `itemscope`)
RDFa	Not recommended	Older format with low adoption

Why JSON-LD is recommended:

Completely decoupled from HTML, easy to maintain
Can be dynamically generated on the server side
Parsed most efficiently by AI agents
Explicitly recommended by Google

3.3 E-Commerce Essential: Product Markup

A complete Product markup example:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Classic Canvas Sneakers",
  "description": "Comfortable, breathable classic canvas shoes for everyday wear.",
  "image": [
    "https://example.com/photos/shoe-1.jpg",
    "https://example.com/photos/shoe-2.jpg"
  ],
  "brand": {
    "@type": "Brand",
    "name": "ExampleBrand"
  },
  "sku": "SHOE-001",
  "gtin13": "1234567890123",
  "offers": {
    "@type": "Offer",
    "url": "https://example.com/shoe-001",
    "priceCurrency": "USD",
    "price": "49.99",
    "availability": "https://schema.org/InStock",
    "seller": {
      "@type": "Organization",
      "name": "Example Store"
    },
    "shippingDetails": {
      "@type": "OfferShippingDetails",
      "shippingDestination": {
        "@type": "DefinedRegion",
        "addressCountry": "US"
      },
      "deliveryTime": {
        "@type": "ShippingDeliveryTime",
        "businessDays": {
          "@type": "QuantitativeValue",
          "minValue": 1,
          "maxValue": 5
        }
      }
    },
    "hasMerchantReturnPolicy": {
      "@type": "MerchantReturnPolicy",
      "returnPolicyCategory": "https://schema.org/MerchantReturnFiniteReturnWindow",
      "merchantReturnDays": 30
    }
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.6",
    "reviewCount": "128"
  }
}
</script>

Required fields checklist:

Field	Importance	Description
`name`	Required	Product name
`description`	Required	Product description
`image`	Required	At least one high-quality image URL
`offers.price`	Required	Price
`offers.priceCurrency`	Required	Currency code (USD/EUR/GBP, etc.)
`offers.availability`	Required	Stock status
`brand`	Strongly recommended	Brand name
`sku`	Recommended	Unique product identifier
`gtin13` / `gtin14`	Recommended	International barcode
`aggregateRating`	Recommended	Rating summary
`shippingDetails`	Recommended	Shipping information
`hasMerchantReturnPolicy`	Recommended	Return policy

3.4 Company Information: Organization Markup

In addition to products, your company information needs to be structured. Place this on your homepage or “About Us” page:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Company Name",
  "url": "https://example.com",
  "logo": "https://example.com/logo.png",
  "description": "A one-line description of your business",
  "foundingDate": "2020-01-01",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "123 Main Street",
    "addressLocality": "San Francisco",
    "addressRegion": "CA",
    "postalCode": "94105",
    "addressCountry": "US"
  },
  "contactPoint": {
    "@type": "ContactPoint",
    "contactType": "customer service",
    "email": "support@example.com",
    "telephone": "+1-555-123-4567"
  },
  "sameAs": [
    "https://twitter.com/example",
    "https://www.linkedin.com/company/example"
  ]
}
</script>

Helps AI agents understand your site’s hierarchical structure:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "BreadcrumbList",
  "itemListElement": [
    {
      "@type": "ListItem",
      "position": 1,
      "name": "Home",
      "item": "https://example.com"
    },
    {
      "@type": "ListItem",
      "position": 2,
      "name": "Sneakers",
      "item": "https://example.com/category/sneakers"
    },
    {
      "@type": "ListItem",
      "position": 3,
      "name": "Classic Canvas Sneakers"
    }
  ]
}
</script>

3.6 Common Mistakes

Mistake	Consequence	Fix
Price missing currency code	AI cannot compare prices	Always include `priceCurrency`
Missing availability status	AI does not know if the product is purchasable	Dynamically update `availability`
Relative image paths	AI fails to fetch images	Use full `https://` URLs
Markup inconsistent with visible content	Penalized by search engines	Keep markup data aligned with on-page content
Malformed nested JSON	Parse failure	Validate with testing tools

3.7 Validation Tools

After configuring Schema.org markup, validate with these tools:

Google Rich Results Test — Checks if markup is correct and eligible for rich results
Schema.org Validator — The official validation tool
Browser DevTools — Inspect the page source for script type="application/ld+json" content

3.8 Self-Assessment Checklist

Every product page has a Product JSON-LD block
Product markup includes name, description, image, price, and availability
Homepage or About page has an Organization JSON-LD block
Category pages have BreadcrumbList markup
At least 3 pages validated with Google Rich Results Test
Markup data is consistent with visible page content

Next chapter: JSON-LD vs Microdata — Technical comparison and migration guide

Technical infrastructure for AI trust signals JSON-LD vs Microdata: format comparison

Start

Learning Paths

Getting Started with AI Commerce

OTR Open Trust Registry

UCP Universal Commerce Protocol

ACP Agentic Commerce Protocol

MCP Model Context Protocol

SEO for the AI Era

ORBEXA Integrated Solution

Templates & Prompts

Glossary

Schema.org structured data for AI agents

Schema.org in Practice

3.1 What is Schema.org

3.2 Three Implementation Formats

3.3 E-Commerce Essential: Product Markup

3.4 Company Information: Organization Markup

3.6 Common Mistakes

3.7 Validation Tools

3.8 Self-Assessment Checklist

​Schema.org in Practice

​3.1 What is Schema.org

​3.2 Three Implementation Formats

​3.3 E-Commerce Essential: Product Markup

​3.4 Company Information: Organization Markup

​3.5 Breadcrumb Navigation: BreadcrumbList

​3.6 Common Mistakes

​3.7 Validation Tools

​3.8 Self-Assessment Checklist

Schema.org in Practice

3.1 What is Schema.org

3.2 Three Implementation Formats

3.3 E-Commerce Essential: Product Markup

3.4 Company Information: Organization Markup

3.5 Breadcrumb Navigation: BreadcrumbList

3.6 Common Mistakes

3.7 Validation Tools

3.8 Self-Assessment Checklist