Structured Data and Schema Markup

What Is Structured Data?

Structured data is machine-readable code added to your pages that explicitly communicates information to search engines and AI systems. Rather than letting Google guess what your content means, structured data using the Schema.org vocabulary defines it precisely: this is a business, this is a service, this is a frequently asked question, this is a review. It is one of the most underutilized technical SEO levers available, and one of the most consequential for appearing in AI-generated answers.

Why Schema Markup Matters for AI Search

Structured data has always helped with traditional search results. In the AI search era it has become even more important. AI systems like Google AI Overviews, ChatGPT, and Perplexity need to understand not just what your content says but what type of entity you are and what you do. Schema markup makes that explicit.

Schema Code Examples

All structured data on this site is implemented as JSON-LD, Google's recommended format. JSON-LD lives in a script tag in the page head, completely separate from the visible HTML. Here are real examples of the three schema types we implement most frequently for service businesses.

FAQPage Schema

Marks up question-and-answer content so Google can display it as expandable FAQ rich results in search. Each question and answer must be visible on the page.

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is structured data?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Structured data is machine-readable code added to a webpage that explicitly communicates its content to search engines. It uses the Schema.org vocabulary and is most commonly implemented as JSON-LD in the page head."
      }
    },
    {
      "@type": "Question",
      "name": "Does schema markup improve rankings?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Schema does not directly change organic rankings, but it enables rich results like FAQ dropdowns and review stars that improve click-through rate. It also feeds AI answer systems that increasingly drive zero-click visibility."
      }
    }
  ]
}

ProfessionalService Schema

Tells search engines and AI systems exactly what your business is, what you offer, and how to contact you. Aligns with your Google Business Profile for consistent entity signals.

{
  "@context": "https://schema.org",
  "@type": "ProfessionalService",
  "name": "Your Business Name",
  "url": "https://example.com",
  "description": "Clear, specific description of what you do and who you serve.",
  "telephone": "+1-555-000-0000",
  "areaServed": "Dallas, TX",
  "serviceType": "SEO Services",
  "address": {
    "@type": "PostalAddress",
    "addressLocality": "Dallas",
    "addressRegion": "TX",
    "addressCountry": "US"
  },
  "openingHoursSpecification": {
    "@type": "OpeningHoursSpecification",
    "dayOfWeek": ["Monday","Tuesday","Wednesday","Thursday","Friday"],
    "opens": "09:00",
    "closes": "17:00"
  }
}

BreadcrumbList Schema

Communicates your site hierarchy so Google shows readable breadcrumb paths in search results instead of raw URLs. Every page deeper than the homepage benefits from this.

{
  "@context": "https://schema.org",
  "@type": "BreadcrumbList",
  "itemListElement": [
    {
      "@type": "ListItem",
      "position": 1,
      "name": "Home",
      "item": "https://example.com/"
    },
    {
      "@type": "ListItem",
      "position": 2,
      "name": "SEO Services",
      "item": "https://example.com/seo-services/"
    },
    {
      "@type": "ListItem",
      "position": 3,
      "name": "SEO for Law Firms",
      "item": "https://example.com/seo-services/law-firms/"
    }
  ]
}

All three of these schema types are validated against Google's Rich Results Test before deployment. Every page we build gets the schema types appropriate to its content, never generic boilerplate that misfires or misrepresents the page.