Putting together an actionable strategy to keep your organization relevant in the ever-changing search marketing landscape is harder than ever.
To help support your organization through this journey, this guide provides insights into why schema markup is essential and how you can implement a structured data markup strategy to support your organization’s goals this year.
What Is Schema (A.k.a. Structured Data)?
Schema, also used interchangeably with the term structured data, refers to machine-readable data that you can add to your website to describe your content.
Schema is actually the industry standard vocabulary that is used to markup structured data. This helps search engines understand the content on your website in the context of your brand, making your content more visible to your target audience.
Optimizing your website is like translating your content into the language of search engines and machines.
Enable Higher Visibility In Search
By implementing structured data markup, you unlock the potential for your content to appear as rich results in Google search listings.
These rich results – which showcase additional information such as product pricing, star ratings, job posting details, and video thumbnails – take up more real estate in search results, drawing more attention and leading to higher click-through rates (CTR) and more traffic to your website.
Image created by author, February 2025Schema markup helps ensure your website can achieve rich results, supporting increased visibility and conversion from search engine results pages (SERPs), resulting in more traffic and leads.
Tip #1: Maximize Rich Results On Your Site
When implementing a structured data strategy, focus on maximizing the number of rich results you can achieve. These results can significantly improve your website’s visibility and conversion rate on the search engine result page
Top-performing rich results include Products, Reviews, Questions and Answers, and Job Postings.
Have your team review your current content to identify existing opportunities for rich results.
Google’s Guide provides examples to get your team started. Also, look for opportunities to update content to unlock new rich result opportunities.
For example, if you have a product page with pricing information, consider expanding it with additional recommended properties like availability, shipping details, ratings, and reviews. This could help you achieve a more detailed Merchant Listing in search results.
We recommend marking up more than just the minimum required fields.
Include Google’s recommended properties to increase your chances of achieving rich results, as well as other properties that showcase the uniqueness of your content or products. This helps inform search engines about your content and match them to specific queries.
While rich results have been around for some time, they remain a powerful tool in the age of zero-click searches to drive traffic to your site. Accelerating the optimization of your content with schema markup to achieve these rich results should be a priority.
Manage Your Brand With A Semantic Data Layer
With the introduction of AI Overviews in Google, as well as the rise of generative AI platforms such as ChatGPT, Perplexity, and Gemini, your target audience is increasingly interacting with your website data before they even visit a webpage on your site.
The data these AI models interact with is derived from the content on your site. While you have control over the content on your website, you have little control over how AI platforms interpret and understand the data.
When AI “hallucinates,” it can result in incorrect information showing up in search experiences, and these inaccuracies could harm your brand’s reputation.
While it’s not clear if these AI platforms are currently being trained on schema markup, adding semantic schema markup, which results in a semantic data layer, provides a resource to machines for how you want your content understood. This semantic data layer gives you a control point in how your brand is presented to these machines.
Large language models (LLMs) and AI tools are advancing and changing every day.
As the experiences powered by these models evolve, your web content will remain constant. You want to be sure your data is ready to be crawled and consumed – and structured data markup allows you to do that.
Tip #2: Shift Your Team From Keywords To Entities Using Structured Data Markup
To create a semantic data layer, your team needs to shift from thinking about keywords to thinking about entities. There is value in describing “things” on your website in context.
In this world of advanced search engines, think of keywords as being one-dimensional and entities being multi-dimensional.
For example, I, Martha van Berkel, am a person, and I can be defined as an entity on my author page.
The words on the page talk about things that people might want to know about me, and the schema markup structures this data to be understood by machines.
The schema markup on my author page explains who I am, my relationship to my organization, and information about my area of expertise.
Image created by author, February 2025Doing so will translate your unstructured content into machine-readable data, enhancing your semantic data layer.
So, in addition to trying to achieve rich results, you should leverage the Schema.org vocabulary to its fullest to explain what your website content is about and create a semantic data layer.
Add schema markup to your entire site to identify and describe your entities – the key topics or “things” within your content.
Tip #3: Connect The Things On Your Website With Schema Markup
Identifying and describing the entities on your site is only the first step. Many entities on your site can also be defined by their relationship to other things on your site and across the web.
Therefore, it is important that your team uses structured data markup to define the entities and topics on your site and explain their relationships.
For example, I, Martha van Berkel, am the founder of the organization Schema App. I am also the author of a few blog articles on the Schema App website.
Schema App and these blog articles are all unique entities. We can use schema markup to articulate my relationship with these entities.
Image created by author, February 2025Moreover, markup enables you to link entities across the web, providing greater context to search engines and AI.
This process, known as entity linking, helps to not only further define your entities, but also clarify their meaning.
Continuing our example: I, Martha van Berkel, know about knowledge graphs. One could easily mistake the knowledge graph we’re talking about as Google’s knowledge graph.
To clarify what “knowledge graph” we’re referring to, we could link the term “knowledge graphs” to the corresponding entity in authoritative knowledge bases like Wikidata, where the term structured data is already defined and understood by the machines consuming the content.
Image created by author, February 2025In addition to building the semantic data layer, at Schema App, we’ve seen an increase in related queries after adding entity linking.
For example, “near me” queries increased after we implemented place-based entity linking for location pages.
By connecting entities both within your site and across the web with structured data markup, you are effectively building a content knowledge graph.
This semantic data layer ensures that search engines, AI, and other data consumers understand the entities on your site and their relationships – far beyond just keywords.
Preparing For AI Within Your Organization
Many organizations have been tasked with developing AI strategies to prepare for the future. The good news is that the content knowledge graph you’ve built for search is equally valuable in enabling your internal AI innovations.
In February 2024, Gartner assessed 30 emerging technologies that companies need to invest in to stay relevant in this new AI world.
They named “knowledge graphs” as a critical enabler for generative AI. Knowledge graphs can support generative AI adoption by grounding the LLM in factual information, reducing hallucinations.
Furthermore, another research by Data.World showed that using knowledge graphs for responses in enterprises improves GPT-4’s accuracy from 16% to 54%.
The digital landscape is changing rapidly, and there are now many ways consumers and businesses can “search.” At the heart of these new experiences is your brand’s website content or your website data.
By investing in optimizing your website with schema markup and building a dynamic content knowledge graph, you are preparing your organization’s web data for internal AI initiatives.
When you do semantic schema markup, your web data is reusable and adaptable to future technologies.
Tip #4: Challenge SEO Professionals To Shift From Optimizing Pages To Optimizing Your Web Data
Just like content teams need to shift from thinking about keywords, SEO teams need to think about optimizing their web data vs. their webpages.
Challenge your SEO specialists to think about your entities and their relationships across your website using schema markup. This shift will require teams to think about how structured their web data is and how they can make it easily accessible to crawl and understand.
SEO professionals need to think like data architects to ensure your brand’s website data is future-proofed for what’s coming next in search and AI within and outside your organization.
Managing Your Web Data To Prepare For The Future
Implementing a structured data markup strategy is not just about optimizing for visibility in search. It is also about defining and connecting entities to build your brand’s semantic data layer.
The search landscape is ever-evolving, and AI technologies will come and go.
Therefore, SEO teams should take this opportunity to leverage schema markup for its semantic value and develop a content knowledge graph that prepares your brand for whatever comes next.
More Resources:
- Why Now’s The Time To Adopt Schema Markup
- Local SEO Schema: A Complete Guide To Local Markup & Rich Results
- SEO In The Age Of AI
Featured Image: PeopleImages.com – Yuri A/Shutterstock
