There has never been a better moment for organizations to prioritize Schema Markup.
Why is that, you may wonder?
First of all, Schema Markup, also known as structured data, is not a new concept.
Google has been rewarding sites that implement structured data with rich results. If you haven’t been leveraging these rich results in search, it is time to increase your click-through rate with these visual features.
Secondly, as search is now primarily driven by AI, it is more crucial than ever to help search engines understand your content.
Schema Markup allows your organization to clearly express what your content means and how it relates to other elements on your website.
The final reason to adopt Schema Markup is that it enables you to build a content knowledge graph when implemented correctly, which is a critical asset in the era of generative AI.
Schema Markup For Rich Results
Schema.org, created in collaboration with Google, Bing, Yahoo, and Yandex, has existed since 2011 to help website owners translate their content for better understanding by search engines.
Since its creation, Google has incentivized the use of Schema Markup by providing rich results to sites with particular types of markup and eligible content. Websites that obtain these rich outcomes generally see higher click-through rates from search engine results pages.
Schema Markup remains one of the clearest and highly recommended SEO tactics that Google endorses. While many SEO practices need to be reverse-engineered, this one is straightforward.
You might have postponed implementing Schema Markup due to the lack of relevant rich results for your website. That was perhaps true before. Since 2013, the variety of rich results has increased significantly.
Even though Google phased out how-to rich results and adjusted the eligibility of FAQ rich results in August 2023, it introduced six new rich results shortly afterward – the most introduced in a single year!
These include vehicle listing, course information, profile pages, discussion forums, organization, vacation rental, and product variants.
Currently, there are 35 rich results available for use, spanning industries such as healthcare, finance, and technology.
Here are some widely applicable rich results worth considering:
- Breadcrumb
- Product
- Reviews
- JobPosting
- Video
- Profile Page
- Organization
Given so many ways to influence your appearance in search, it’s surprising more websites haven’t adopted it.
A report from Web Data Commons in October 2023 revealed that only 50% of pages incorporated structured data.
Of those utilizing JSON-LD markup, these were the predominant types of entities found:
- ListItem (2,341,592,788 Entities)
- ImageObject (1,429,942,067 Entities)
- Organization (907,701,098 Entities)
- BreadcrumbList (817,464,472 Entities)
- WebSite (712,198,821 Entities)
- WebPage (691,208,528 Entities)
- Offer (623,956,111 Entities)
- SearchAction (614,892,152 Entities)
- Person (582,460,344 Entities)
- EntryPoint (502,883,892 Entities)
(Source: October 2023 Web Data Commons Report)
Most types listed relate to the rich results mentioned previously. For example, ListItem and BreadcrumbList are needed for the Breadcrumb Rich Result, SearchAction is required for a Sitelink Search Box, and Offer is needed for the Product Rich Result.
This suggests that websites primarily use Schema Markup for rich results.
While these Schema.org types help your site stand out in search, they don’t necessarily tell search engines about each page in detail, enhancing your site’s semantic context.
Help AI Search Engines Understand Your Content
Have you noticed competitors using specific Schema.org Types not found in Google’s structured data documentation (e.g., MedicalClinic, IndividualPhysician, Service)?
The Schema.org vocabulary, boasting over 800 types and properties, helps websites specify what a page is about. However, Google’s structured data features only need a limited subset of these for rich result eligibility.
Websites seeking only to gain rich results often offer less detailed Schema Markup.
AI search engines today focus on the meaning and intent of content to provide more relevant search results. Thus, organizations aiming to stay ahead should use more specific Schema.org types and appropriate properties to guide search engines toward a more nuanced understanding and contextualization of their content. You can maintain descriptive content while still achieving rich results.
For example, each type (e.g., Article, Person) in the Schema.org vocabulary has 40+ properties to describe an entity.
These properties help you fully articulate what the page covers and how it connects to other components on your website and the internet, effectively requiring a semantic description of the page’s entity or topic.
The term ‘semantic’ involves understanding language meaning. Notably, the word “understanding” features prominently in its definition. Interestingly, in October 2023, John Mueller from Google released a Search Update video. In the six-minute video, he highlighted Schema Markup updates.
For the first time, Mueller described Schema Markup as “a code you can add to your web pages, which search engines can use to better understand the content.”
Historically, Mueller has spoken extensively about Schema Markup, often within the context of rich result eligibility, so why the updated perspective?
This new emphasis on improving search engine comprehension via Schema Markup aligns with AI’s growing role and influence in search. It is vital to render content easily consumable and understandable by search engines.
Take Control Of AI By Shaping Your Data With Schema Markup
Should being understood and standing out in search not be compelling reasons to implement Schema Markup, then facilitating enterprise control over content and preparing it for artificial intelligence should be.
In February 2024, Gartner released a report on “30 Emerging Technologies That Will Guide Your Business Decisions,” highlighting generative AI and knowledge graphs as pivotal emerging technologies companies must invest in within the next 0-1 years.
Knowledge graphs represent collections of relationship-related entities using a standardized vocabulary, enabling new knowledge through inference.
Good news! By using Schema Markup to define and link entities on your site, you create a content knowledge graph for your organization, becoming a vital enabler for generative AI adoption and benefitting SEO.
Learn more about building content knowledge graphs in my article, Extending Your Schema Markup From Rich Results to Knowledge Graphs.
We can also consider insights from other knowledge graph experts to recognize the urgency of implementing Schema Markup.
In a LinkedIn post, Tony Seale, Knowledge Graph Architect at UBS in the UK, noted,
“AI does not need to happen to you; organizations have the ability to shape AI by shaping their data."
“It is a choice: We can allow all data to be consumed by large ‘data gravity wells’ or create ‘networks of networks,’ each connecting and consolidating our data.”
Seale’s concept of “networks of networks” refers to the knowledge graphs that can be built using semantic Schema Markup.
The AI revolution is just beginning, and now is the time to shape your data, starting with web content through Schema Markup implementation.
Use Schema Markup As The Catalyst For AI
In the current digital landscape, organizations must embrace new technology to keep up with AI and search evolutions. Whether seeking to stand out on the SERP or ensuring content comprehension by Google and other search engines, now is the time to implement Schema Markup.
Schema Markup enables SEO professionals to become heroes, facilitating generative AI adoption through content knowledge graphs while delivering tangible benefits like increased click-through rates and improved search visibility.
More resources:
Featured Image by author
