Schema markup implementation

This guide covers the technical implementation of JSON-LD schema markup for the types that have the highest impact on AI discoverability.

JSON-LD Basics

JSON-LD (JavaScript Object Notation for Linked Data) is embedded in a script tag in the page head. It describes entities and their properties in a format both humans and machines can read.

A basic Organization schema looks like this:

json{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Point11",
  "url": "https://www.point11.com",
  "logo": "https://www.point11.com/logo.png",
  "description": "AI infrastructure for enterprise customer acquisition.",
  "foundingDate": "2024",
  "founders": [
    { "@type": "Person", "name": "Adam Fish" },
    { "@type": "Person", "name": "Robert Bernton" }
  ],
  "sameAs": [
    "https://www.linkedin.com/company/point11",
    "https://twitter.com/point11"
  ]
}

Product Schema

For each product page, implement Product schema with as many properties as applicable:

• name: Product name.
• description: Product description (match the visible page content).
• brand: Your organization.
• offers: Pricing information with priceCurrency, price, and availability.
• aggregateRating: Review scores if available.
• image: Product images.
• sku: Stock keeping unit identifier.
• category: Product category within your taxonomy.

Google requires that all content in your structured data markup is also visible on the web page. Do not include data in schema that is not present in the page content.

Service Schema

For service-based businesses, use the Service type:

• name: Service name.
• description: What the service does.
• provider: Your Organization entity.
• serviceType: Category of service.
• areaServed: Geographic coverage.
• serviceOutput: What the customer receives.

FAQPage Schema

FAQ content is one of the most extractable formats for AI systems. Implement FAQPage with Question and Answer pairs:

• Each Question must have an acceptedAnswer with text content.
• The questions and answers must be visible on the page.
• Google may display FAQ rich results in search, and AI systems frequently extract and cite FAQ content.

BreadcrumbList Schema

Implement on every page to communicate site hierarchy:

• Include the full path from homepage to the current page.
• Each item needs a name and URL.
• Helps AI systems understand the relationship between pages and product categories.

Validation

Use these tools to validate your implementation:

• Google Rich Results Test for checking Google eligibility.
• Schema.org Validator for general schema compliance.
• Run validation on every page template, not just individual pages.

Common Mistakes

• Including schema data that is not visible on the page (Google penalizes this).
• Using the wrong schema type (e.g., LocalBusiness when the business has no public physical location).
• Missing required properties for rich results eligibility.
• Duplicate schema on the same page from multiple plugins or scripts.
• Not updating schema when page content changes.

Sources

• Schema.org Product Type: https://schema.org/Product
• Schema.org Service Type: https://schema.org/Service
• Schema.org FAQPage Type: https://schema.org/FAQPage
• Google Structured Data Guidelines: https://developers.google.com/search/docs/appearance/structured-data/sd-policies
• Google Rich Results Test: https://search.google.com/test/rich-results