The Power of Schema Markup: Building a Reusable Content Knowledge Graph for Your Organization
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You’re likely familiar with Schema Markup for enhancing pages to achieve rich results. However, did you know it can also be used to construct a reusable content knowledge graph for your organization’s web content?
Often, SEO professionals focus solely on attaining rich results with Schema Markup, thereby missing the opportunity to create semantic Schema Markup and develop a content knowledge graph.
Content knowledge graphs enable search engines to better contextualize your site’s content, making inferences more easily.
To illustrate the power of Schema Markup for inferencing, let me introduce myself. I’m Martha van Berkel, and here is my knowledge graph. It explains who I am and my relationship to various other things.
- I studied at MIT and hold a degree in Mathematics and Engineering.
- I’m Canadian, the co-founder and CEO of Schema App, and have extensive knowledge about Schema Markup.
- I spent 14 years working at Cisco.
- I once owned a 1965 Austin Healey Sprite, which appeared in the movie "Losing Chase," directed by Kevin Bacon. Kevin Bacon even drove my car.
What inferences can you draw from my knowledge graph? Perhaps you’re considering how you might win the "6 degrees of separation from Kevin Bacon" game? Or maybe you’re seeing the connection between my knowledge of Schema Markup and my role as CEO of Schema App?
These inferences are possible because of the insights developed from understanding the specific relationships outlined in my knowledge graph. I used properties applicable for a Person Schema.org type to articulate my relationship with these items—the same vocabulary we use to optimize web pages.
Without defining the relationships between myself and these other entities, you might incorrectly assume I work at Cisco, am simply a user of Schema App, and am related to Kevin Bacon. This highlights the importance of specificity and context!
Just as I’ve employed Schema Markup to bring clarity and context to who I am, it’s possible to use Schema Markup to add more context to website content, enabling search engines and AI to make accurate and powerful inferences.
This article will explore why it’s crucial to think of Schema Markup in terms of its semantic value and how you can use it to build a reusable content knowledge graph.
Why Is It Important To Start Thinking About Schema Markup For Its Semantic Value?
The search landscape is evolving rapidly. Search engines are striving to provide a new search experience utilizing inferencing and chat functionalities.
This evolution is evident in offerings like Google’s Gemini and Bing’s ChatGPT, as well as newer entities like Perplexity AI. In chat-based environments, search engines need the capability to offer users quick, accurate answers while adapting to changing contexts.
Consumers are increasingly using highly specific, long-tail queries in their searches. For instance, instead of querying [female doctor Nashville women’s health], users might look for [find me a female doctor who can help me with my cramps and has availability in the next 2 days].
Search engines and large language models (LLMs) cannot easily infer the answer to this kind of query by merely analyzing website data—without understanding how the information is interconnected. This requirement for contextual inference is part of why there’s a shift from lexical to semantic search.
So, how do you facilitate this understanding and inference from your content? By translating web content into a standardized vocabulary comprehensible to both humans and search engines—through Schema Markup.
By implementing Schema Markup, you can identify and describe entities on your site and use the Schema.org properties to detail how they relate to one another.
Entities refer to distinct, well-defined concepts or items, which might include people, places, or ideas, each carrying specific characteristics and attributes.
The content on your website features entities relevant to your organization (e.g., brand, products, services, people, locations), and Schema Markup allows you to articulate relationships between your site’s entities.
Entities serve as fundamental building blocks for crafting a content knowledge graph.
A content knowledge graph’s value extends beyond SEO. Gartner’s 2024 Emerging Tech Impact Radar highlights knowledge graphs as crucial tools and worthy of investment for embracing generative AI innovations.
Numerous AI projects are powered by large language models prone to inaccuracies. Research indicates that pairing them with knowledge graphs can provide factual grounding, yielding more accurate LLM-derived answers.
Creating content knowledge graphs through Schema Markup can empower search engine comprehension and help position organizations as innovators with AI.
Implementing Schema Markup To Build A Content Knowledge Graph Vs. Just Rich Results
You might ask: How is building a content knowledge graph different from using Schema Markup for rich results?
When SEO professionals aim solely for rich results, they typically apply Schema Markup only to pages eligible for those results, imparting limited parts of the organization’s narrative to search engines.
This approach fails to offer detailed insights or context about site entities and their interconnections.
This leaves search engines guessing content intent and meaning—much like assuming my association with Kevin Bacon and Cisco in absence of established relationships noted earlier.
By pivoting toward building a content knowledge graph, SEO experts use Schema Markup to pinpoint, describe, and elaborate on site entities, granting search engines a deeper understanding and context of the organization’s website.
How To Implement Schema Markup To Build Your Content Knowledge Graph
- Identify Key Entity Pages On Your Website
Your site likely features numerous entities (such as specific products, individuals, services). However, some entities are crucial for meeting business goals. This content often needs to be communicated to both audiences and search engines to drive engagement or awareness.
Common key entities typically include the organization, services, products, people, and brand—though alignment with business objectives varies.
For instance, a healthcare provider aiming to establish trust and facilitate bookings may focus on entities like their organization, facilities, physicians, and services.
Upon recognizing key entities, locate site pages effectively representing them. Ideally, each page should detail one entity and its relationship with others on the site.
- Employ Schema.org Vocabulary For Entity Descriptions
Applying Schema Markup involves utilizing Schema.org vocabulary for creating descriptive statements about an entity. The Schema.org type classifies the entity, whereas properties detail it.
For example, a physician’s detail page might encompass the physician’s name, specialty, associated network, facility affiliations, services, and served regions.
Schema Markup can elaborate on these aspects while presenting a graph with precise links.
This helps search engines clarify details. Think of a query like [find a local cardiologist who performs EKGs and has appointments available in the next 2 days].
Each website page conveys information about your business.
Deploying Schema Markup on every page concisely informs search engines about its focus and interrelations with other site content. Therefore, search engines and large language models can utilize this data for confident inferences and answering specific queries.
- Link Entities Throughout Your Website
Each web page hosts unique entities, but may also reference other defined site entities.
Building a content knowledge graph involves displaying inter-entity connections and providing context using apt schema.org properties.
This step extends beyond hyperlinking with anchor text. Schema Markup uses properties best describing inter-entity relations.
For instance, if a Physician belongs to HealthNetwork, the memberOf property can assert this membership to the HealthNetwork Organization.
If page URLs guide user journeys, these entities should also be linked within Schema Markup. For physicians, this might relate to service line pages, practice locations, and so on.
Such connections furnish search engines with richer context regarding the physician, enabling them to respond to intricate queries.
With these steps, you’ve initiated the construction of your content knowledge graph. This goes hand in hand with striving for rich results. However, the chosen properties for inter-entity connections may differ from Google’s requirements for rich results.
- Connect Entities With Established Authoritative Knowledge Bases For Clarity
Apart from interlinking site entities, further define entities using links to recognized external authoritative knowledge bases such as Wikipedia, Wikidata, and Google’s Knowledge Graph.
This technique is known as entity linking.
Entity linking can clarify entities mentioned in your text, allowing search engines to differentiate them more assuredly and thus feature your page for more pertinent queries.
Schema App’s experimentation has unveiled the SEO impacts of entity linking. It showed that disambiguating entities, like places, enhanced page performance for "[near me]" and other location-focused queries.
The experiments also demonstrated that entity linking improved pages’ visibility for relevant non-branded queries, boosting click-through rates.
Here’s an entity linking scenario: Mentioning “Paris” in your content might confuse search engines given its global presence.
To specify Paris, Ontario in Canada on your site, employ the sameAs property to link this entity to its known counterparts in resources like Wikipedia, Wikidata, and Google’s Knowledge Graph.
Content Knowledge Graph Brings Context To Your Content
If your Schema Markup strategy focuses on select pages aimed at achieving rich results, it’s time to revise your approach.
While rich results may vary, the content knowledge graph established via Schema Markup aids search engines in comprehending your organization and preparing it to spearhead AI advancements.
Regardless of personal opinion, knowledge graphs are essential. Start building yours by implementing semantic Schema Markup on your site.
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