Discover How Many Websites Use Each Schema Type with Schema.org

Have you ever been curious about how many sites use a specific type of structured data? Now, you have the chance to find out.

I recently discovered that Schema.org is now sharing aggregated usage statistics for its terms across the public web. This means you can see exactly how many domains are using a particular schema or structured data element.

According to a Schema.org announcement, they are excited to offer a new dataset providing these statistics. Updated monthly, the data is aggregated at the domain level and categorized into popularity range buckets, which helps to filter daily noise while emphasizing meaningful adoption trends for researchers and tool developers.

What’s the appearance like? Take a look at a snapshot of two Schema.org pages, featuring author schema and event schema, displaying the usage statistics prominently at the top:

Delving deeper into the data. Schema.org has further detailed the usage statistics. Here’s a brief overview:

• Schema.org term frequencies are evaluated within Google’s public web crawling infrastructure. The aggregation occurs at the domain level (e.g., example.com), not page by page. If you use the same term on 100 pages, it still only counts as one domain using it.
• Rather than displaying exact numbers, which can fluctuate daily, websites are categorized into range buckets (e.g., “10K – 100K” domains). This approach stabilizes the data and respects website privacy.
• The raw data files can be accessed on GitHub under the Google Public Stats dataset. Both JSON and CSV formats are available, alongside a JSON summary format offering aggregated bucket distributions, all updated monthly.
• Term Type: Specifies whether the term is a Type (e.g., “Person” or “Event”) or a Property (e.g., “price” or “telephone”).
• URI: Shows the official URI of the term, such as http://schema.org/Person.
• Domain Count Bucket: The range of unique domains utilizing the term, for instance, 100K - 1M domains.

If you’re interested, here’s a peek at GitHub:

Why is this important? Well, besides my love for data, understanding the popularity of a specific schema element might just convince your development team to incorporate that schema code on your site.

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Inspired by this post on Search Engine Land.

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