How Schema Markup Drives Success in AI-Powered Search

The Gist

• Content strategy shift. Schema markup is transforming from an SEO tool to a key element in AI-driven search strategies.
• AI-powered search. Structured data enhances knowledge graphs, which are essential for AI models to interpret and present information effectively.
• Bing’s schema importance. Schema markup is now critical for both Google and Bing search engines, with AI-enabled search making it essential for marketers to adapt.

Until today, Google has dominated search results. This means that for the last two decades, content has been the star of the digital world, while context has been largely overlooked and given little attention.

This paradigm is changing, and it’s changing very quickly. Soon, it will not matter what position you rank for a keyword. What will matter more is whether AI can understand the intent of your content and find it valuable for consumers searching via AI interfaces.

This means the way you build your content strategy needs to change. This change does not lie in new tech investment but in something that Google, Bing and Yahoo have been working on for the past 13 years. The solution is Schema.org.

The Evolution of Schema Markup

Schema.org is the markup standard founded by Google, Bing and Yahoo in June 2011 with 297 classes (content types). Today, this has grown to 811 classes. Google still actively works to bring more content types into the mix, and this is evidenced by the time earlier this year where Google tried to bring shipping information into schema markup.

As of 2024, out of approximately 193 million active sites, more than 45 million use schema, which is an impressive number at first glance. This has led to good results, too. More than 72% of sites on Google’s first page search results use schema.

However, the devil is in the details. Most of the schema markup implemented consists of basic types like FAQ, organization, product and article. With 811 classes available, most content strategy teams have barely scratched the surface. This was acceptable when schema was seen as an SEO tool rather than an integral part of content strategy. But now Schema.org markup has transformed from a mere SEO enhancement tool to a crucial component for success in AI-driven search environments. As search engines become increasingly sophisticated with AI capabilities, the role of structured data has become more vital to guarantee accurate content interpretation and visibility.

Google has never stated that schema markup affects rankings. However, in 2017, it explained how Schema.org helps it understand content better. Here’s what Google’s Gary Illyes said about schema markups: “It will help us understand your pages better, and indirectly, it leads to better ranks in some sense, because we can rank easier.”

For years, the industry focused on the “rank easier” part. Now it’s time to focus on the “understand your pages better” part.

Related Article: Are Marketers Prepared for AI Search Disruption?

Why Schema Markup Is More Important Today

Schema markup has undergone a significant transformation in recent years. While it traditionally served to generate rich snippets in search results, its purpose has expanded dramatically with the advent of AI-powered search experiences. The structured data framework now allows more precise interpretation and presentation of web content.

Schema markup plays a vital role in building knowledge graphs, which are foundational for large language models (LLMs). By representing information in a structured and standardized way, knowledge graphs allow algorithms to extract insights and make predictions more effectively. Without structured information, we’re at the mercy of algorithms to make sense of content and understand all explicit and implicit context.

Another important reason why Schema.org is more important today than a few years ago is the rise of Bing. Google has traditionally dominated search traffic, but with ChatGPT’s rise and its recent launch of search with Bing as its backbone, Bing search as part of the marketing operations roadmap has now become crucial. A low-hanging fruit is schema, which is a common factor in both Bing and Google.

Fabrice Canel, principal program manager for Bing, stated the importance of schema very clearly in his 2023 PubCon keynote: “One of the ways SEOs can prepare for this new AI-enabled search is by writing great content and annotating with Schema Markup.”

One of my favorite examples of a fundamental change in thinking about content strategy is the Georgia.gov case study of building Ask GeorgiaGov, an Alexa skill. The story highlights how content was rearchitected to make sure it would be viable for users consuming content via voice instead of visual interfaces.

That’s the crux of the challenge. We write, think and consume content like humans, and we are woefully unprepared for a scenario where machines become the primary consumers that are tasked with understanding, interpreting and presenting information to end users.

Related Article: Assessing the Impact of AI-Driven Web Browsing on SEO and Marketing

Key Steps to Take for CMOs and Product Owners

First and foremost, work on the basics. Make sure your digital experience platform can support schemas. Most platforms cover basic schema types (usually 20-30 schema markups), but the important consideration is whether they can accommodate custom schemas that aren’t supported out of the box.

Once you’ve made sure that the technical challenges are covered, the grunt work begins. Have your content team map each content type they’re considering to the pool of 811 schema types available. You’ll be surprised how enlightening this exercise can be and how amazed the team will be at the diversity of content types at their disposal.

Once you have that list, start comparing your content types to the available schema markup. This laborious exercise will reveal how unstructured your content truly is.