Schema markup for SEO: What it is and how it works

Implementing schema markup for SEO is a great way to improve your chances of being featured in a rich result on Google. As a system of labels, it’s surprisingly simple to create with a few pointers (and the right tools).

There are a few specific schema markup types you can use to fill in details about your web pages. In this article, you’ll learn about those types and how to use schema markup for SEO (and how it benefits your brand’s AEO as well).

What’s schema markup?

Schema markup, also known as structured data, is code you write into web pages to help search algorithms identify what’s on your page. There are around 1,500 properties you can use to do things like identify the price of a product or the title of a movie playing in a theater. (You won’t need to know all the properties — just the ones relevant to your website.)

All of these properties are detailed on Schema.org, a joint project from Google, Microsoft, Yahoo, and Yandex that created the vocabulary for all the schema types used for search results. This standardization means everyone can use the same labels (e.g., “openingHours,” “reviewRating,” or “priceRange”) for more visibility and better SEO and AEO performance.

Key aspects of schema markup in SEO

Schema markups are useful, but applying one isn’t a cheat code for better search rankings. It gives your content a chance to show up as a rich snippet (like the one shown above) — an enhanced search result with more information than your standard search listing.

Here’s what makes schema markup important for SEO:

• Stronger click-through rates: Rich results get users to click through at 17% higher rates, and search results with better CTRs rank higher because it signals a stronger link between the query and your page.
• Improved SERP real estate: With their extra information, rich results take up a larger space in the search engine results page (SERP), including the knowledge panel on the right side of Google results. That means more visibility and perceived credibility. 
• Better UX: Searchers get more information from the SERP, so they can see if your site will answer their search intent. Users who click through are then more likely to stay on your site for longer with a lower bounce rate.
• AI visibility: Structured data labels content in a way that large language models can discover and use in AI search results.
• Competitive advantage: You’ll be more likely to outrank competitors in SERPs if they don’t have a schema markup.

Common schema markup types

All of the schema markup properties are organized into categories called “types.” You can tell them apart from properties by their capitalization. A category starts with a capital letter, and a property starts in lowercase (for example, “LocalBusiness” is a type, and “openingHours” is a property within that type). 

When you create schema markup, you reference a type and the property within it that you want to use. Here are some of the most common schema markup types and examples of their typical uses:

• Article. Blogs and news websites use properties from the “Article” type to give search engines context about their written content, including “datePublished” and “breadcrumbs.”
• Product. Ecommerce sites use the “Product” type to clarify information about each item they’re selling, like “size” and “review.”
• FAQPage. Service websites label their FAQ page with properties from the “FAQPage” type, such as “relatedLink” and “primaryImageOfPage.”
• LocalBusiness. Businesses that serve an in-person population, like gas stations and restaurants, use “LocalBusiness” properties to answer searcher’s questions about how their business is run (e.g., “openingHours,” “paymentAccepted,” and “priceRange”).
• Event. Event organizers use properties from the “Event” type, such as “eventSchedule” and “typicalAgeRange,” to highlight details for rich results.

Common schema markup formats

There are three accepted ways to add schema markup to your pages. JSON-LD is the most commonly recommended, but here’s how all three formats work in practice.

JSON-LD

JSON-LD is a script you add to your page’s HTML that organizes structured data properties into ‘name: value’ pairs. Those pairs create a long list you can easily update as your site grows.

Here’s an SEO schema markup example that uses JSON-LD:

<script type="application/ld+json">

{

  "@context": "https://schema.org",

  "@type": "LocalBusiness",

  "name": "Ricardo’s Deli",

  "image": "https://RicardosDeli.com/logo.png",

  "telephone": "+15551234",

  "openingHours": "Mo,Tu,We,Th 09:00-12:00",

  "priceRange": "$$",

  "address": {

    "@type": "PostalAddress",

    "streetAddress": "123 Elm St",

    "addressLocality": "Lincoln",

    "addressRegion": "CA",

    "postalCode": "95648",

    "addressCountry": "US"

  }

 }

</script>

Microdata

With Microdata, individual HTML elements are labeled with schema markup attributes like <itemtype> and <itemprop>. For example, you might label a title heading as the name of your business:

<div itemscope itemtype="https://schema.org/LocalBusiness">

  <h1><span itemprop="name">Ricardo’s Deli</span></h1> 

</div>

Note: Not every HTML element can take schema markup attributes like <itemprop> and <itemtype>. Use <div>s and <span>s as needed to insert compatible elements that can use those attributes.

Resource description framework in attributes (RDFa)

RDFa is the predecessor to Microdata, so it looks very similar. However, the attributes are different (such as <span>), and types are identified with their property rather than a URL:

<div vocab="https://schema.org/" typeof="LocalBusiness">

  <h1><span property="name">Ricardo’s Deli<span></h1> 

</div>