Using Schema.org structured data to improve SEO

Search engine optimization has long been a cornerstone of the web, continually evolving as search engines and open‑web initiatives shape how information is discovered.

Today, the rise of AI tools and AI‑powered search is accelerating that evolution, making structured data more critical than ever. In this post, I’ll explore how adding schema.org markup can enrich your content, improve visibility across both traditional search and AI‑driven platforms, and ultimately create a better experience for users.

Schema.org is a set of extensible schemas that enables webmasters to embed structured data on their web pages for use by search engines and other applications. For more details, see the homepage.

Why Use Structured Data?

Adding structured data to your website provides several benefits:

• Rich Search Results: Your content can appear with enhanced visuals in search results, including star ratings, images, prices, and availability information
• Better Click-Through Rates: Rich snippets stand out in search results, leading to higher engagement
• Voice Search Optimization: Search assistants use structured data to provide spoken answers
• Knowledge Graph Integration: Your content can be featured in Google’s Knowledge Panel
• AI Agent Compatibility: Modern AI systems can better understand and utilise your content (more on this below)

How to Implement Structured Data

There are 3 main ways to include structured data in a website’s markup:

• Microdata
• JSON-LD
• RDFa

Microdata adds additional attributes to HTML elements to identify the data on the page. The data is embedded directly within your existing HTML.

<article itemscope itemtype="https://schema.org/BlogPosting">
  <h1 itemprop="headline">My Blog Post Title</h1>
  <span itemprop="author" itemscope itemtype="https://schema.org/Person">
    <span itemprop="name">Damian Karzon</span>
  </span>
  <time itemprop="datePublished" datetime="2025-12-04">December 4, 2025</time>
  <div itemprop="articleBody">
    <p>The content of the blog post goes here...</p>
  </div>
</article>

JSON-LD (JavaScript Object Notation for Linked Data) adds a JSON block to the page where the structured data is output in a single location. This is Google’s recommended format as it’s easier to implement and maintain.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "BlogPosting",
  "headline": "My Blog Post Title",
  "author": {
    "@type": "Person",
    "name": "Damian Karzon"
  },
  "datePublished": "2025-12-04",
  "dateModified": "2025-12-04",
  "image": "https://example.com/images/post-banner.jpg",
  "publisher": {
    "@type": "Organization",
    "name": "DK Development",
    "logo": {
      "@type": "ImageObject",
      "url": "https://example.com/logo.png"
    }
  }
}
</script>

RDFa (Resource Description Framework in Attributes) like Microdata, adds additional attributes to HTML elements to identify the data on the page. It’s more verbose but offers greater flexibility.

<article vocab="https://schema.org/" typeof="BlogPosting">
  <h1 property="headline">My Blog Post Title</h1>
  <span property="author" typeof="Person">
    <span property="name">Damian Karzon</span>
  </span>
  <time property="datePublished" datetime="2025-12-04">December 4, 2025</time>
  <div property="articleBody">
    <p>The content of the blog post goes here...</p>
  </div>
</article>

Which Format Should You Use?

JSON-LD is the recommended approach for most implementations because:

• It’s easier to add and maintain (no need to modify existing HTML)
• It keeps your markup cleaner
• It’s Google’s preferred format
• It can be dynamically generated server-side or via JavaScript

Popular Schema Types

A comprehensive list of schema types can be found at schema.org/docs/schemas.html.

The vocabulary currently consists of 792 Types, 1447 Properties, 15 Datatypes, 83 Enumerations and 445 Enumeration members.

Here are some of the most commonly used schema types:

AI Agents and Structured Data

With the rise of AI assistants like ChatGPT, Claude, Gemini, and others, structured data has taken on a new dimension of importance. Here’s how AI agents interact with schema.org markup:

Enhanced Content Understanding

AI agents parse structured data to better understand the context and meaning of web content. When an AI encounters a page with proper schema markup, it can:

• Accurately identify the type of content (article, product, recipe, etc.)
• Extract key information like authors, dates, prices, and ratings
• Understand relationships between entities on the page

AI-Powered Search and Assistants

Many AI systems now power search experiences and virtual assistants:

• Retrieval-Augmented Generation (RAG): AI systems that search and synthesise information benefit from structured data to provide accurate, well-attributed responses
• Voice Assistants: Siri, Alexa, and Google Assistant use structured data to answer questions directly
• AI Search Engines: Perplexity, Bing Copilot, and Google’s AI Overviews leverage schema markup to generate accurate summaries

Agentic Web Browsing

As AI agents become more autonomous in browsing and interacting with websites:

• Structured data helps agents understand page purpose and available actions
• Schema types like Action and EntryPoint can indicate how to interact with a service
• Well-marked content is more likely to be correctly interpreted and cited

Best Practices for AI Compatibility

To optimise your structured data for AI agents:

1. Be comprehensive: Include as many relevant properties as possible
2. Use accurate data: AI systems may cross-reference your claims
3. Include sameAs properties: Link to authoritative sources (Wikipedia, social profiles)
4. Add speakable schema: Indicates content suitable for text-to-speech
5. Implement WebPage and WebSite schemas: Helps AI understand your site structure

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "WebSite",
  "name": "DK Development",
  "url": "https://dkdev.au",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://dkdev.au/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>

Testing Your Structured Data

Before deploying structured data to production, validate it using these tools:

• Google Rich Results Test: Tests if your page is eligible for rich results
• Schema.org Validator: Validates your markup against the schema.org specification
• Google Structured Data Markup Helper: Helps generate markup for your pages

A Real-World Blog Example

Here’s how I’ve implemented structured data on this very blog using JSON-LD:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "BlogPosting",
  "mainEntityOfPage": {
    "@type": "WebPage",
    "@id": "https://dkdev.au/seo-structured-data-2025/"
  },
  "headline": "Using Schema.org structured data to improve SEO",
  "description": "How to add Schema.org markup to your websites to improve users search experience.",
  "image": "https://dkdev.au/img/Banners/book.jpg",
  "author": {
    "@type": "Person",
    "name": "Damian Karzon",
    "url": "https://dkdev.au"
  },
  "publisher": {
    "@type": "Organization",
    "name": "DK Development",
    "logo": {
      "@type": "ImageObject",
      "url": "https://dkdev.au/img/favicon.ico"
    }
  },
  "datePublished": "2025-12-04",
  "dateModified": "2025-12-04"
}
</script>

Recap

Structured data is no longer just about improving traditional search results—it’s becoming essential infrastructure for how AI systems understand and interact with web content. By implementing schema.org markup:

1. Choose JSON-LD as your primary format for ease of implementation
2. Start with the basics: Add Article/BlogPosting schema to your blog posts
3. Expand to business schemas: Organization, LocalBusiness, and Person for your about pages
4. Test thoroughly before deployment using Google’s validation tools
5. Think about AI: Your structured data helps AI agents accurately represent your content

As AI continues to transform how users discover and consume web content, well-structured data will become a competitive advantage—not just for SEO, but for ensuring your content is accurately understood and represented across an increasingly AI-mediated web.

Further Reading

• Schema.org Blog Type
• Google’s Article Structured Data Guide
• Schema Microdata Examples on GitHub