Structured Data & Schema Markup Guide

Structured data (schema markup) is machine-readable code that tells search engines and AI models exactly what your content means. It's the single most impactful technical change you can make for both SEO rich results AND AI citation readiness.

Why Structured Data is Critical in 2025

Structured data serves two audiences simultaneously: search engines (for rich results) and AI models (for entity understanding and citation). Pages with proper schema markup rank 4 positions higher on average AND are 3x more likely to be cited by AI models.

Essential Schema Types

JSON-LD Implementation Example

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "LocalBusiness",
  "name": "Your Business Name",
  "url": "https://yourbusiness.com",
  "telephone": "+1-555-123-4567",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "123 Main St",
    "addressLocality": "Austin",
    "addressRegion": "TX",
    "postalCode": "78701"
  },
  "openingHoursSpecification": {...},
  "aggregateRating": {...}
}
</script>

Common Schema Mistakes

• Missing required properties — Schema without required fields won't generate rich results
• Incorrect nesting — Improper @type hierarchy confuses parsers
• Duplicate schema — Multiple conflicting Organization schemas on one page
• Stale data — Schema with outdated hours, prices, or descriptions
• No FAQ schema — The easiest quick-win most sites miss entirely

SAGIScan's schema validator uses AI to check not just syntax but appropriateness — whether your schema types match your content and whether you're missing opportunities. Validate your schema free.