Entity SEO: The Future of Optimizing for Search Engines

Things, not strings. If you haven’t heard this before, it comes from a famous Google blog post that announced the Knowledge Graph. 

This quote indicates that Google now understands things and is no longer just matching keywords.

Entities in the context of SEO refer to distinct and identifiable objects, concepts, or things that exist independently. They can be anything from people, places, and organizations to abstract concepts like dates, ideas, or emotions. In the digital world, entities are often represented through unique identifiers, allowing search engines to understand and categorize them.

For something to be determined to be an entity, it must exist inside an entity catalog, or knowledge base. Wikipedia is a well-known example of such an entity catalog.

Some examples of entity catalogs include:

  • Wikipedia
  • Wikidata
  • DBpedia
  • Freebase
  • Golden

The knowledge base entry of an entity summarizes what is known about that entity. 

As the world is constantly changing, new facts are continuing to emerge. Keeping up with these changes requires a constant effort from editors and content managers. This is a demanding task at scale. 

By analyzing the contents of documents in which entities are mentioned, the process of finding new facts or facts that need updating may be supported or even fully automated. 

Scientists refer to this as the problem of knowledge base population, which is why entity linking is important.

Why are entities important?

Entities allow for a better understanding of the meaning of text, both for humans and for machines (like Google’s algorithm). 

Entities are vital in the realm of SEO for several reasons, and their importance extends beyond mere keyword optimization. Here’s why entities are considered essential:

Enhanced Search Relevance

Entities enable search engines to understand the context and relationships within content, leading to more relevant search results. By recognizing the specific entities involved in a query, search engines can provide answers that align more closely with the user’s intent.

Improved User Experience

By focusing on entities, content creators can deliver information that resonates with the user’s needs and questions. This approach fosters a more engaging and satisfying user experience, as the content is tailored to the user’s understanding and interest in specific subjects or concepts.

Connection to Knowledge Graphs

Search engines often use knowledge graphs to represent the relationships between different entities. These graphs enable search engines to create a more comprehensive understanding of the world and how various entities are interconnected. By optimizing for entities, content can become part of this vast network of information, enhancing its visibility and relevance.

Voice Search Optimization

With the rise of voice-activated devices, understanding and optimizing for entities has become even more critical. Voice searches often involve more natural and conversational language, requiring a deeper understanding of the context and relationships between entities. By focusing on entities, content can be more easily accessed and understood through voice search.

Building Authority and Trust

Entities are closely tied to Google’s E-A-T (Expertise, Authority, Trustworthiness) algorithm. By accurately representing and connecting entities within content, websites can demonstrate their expertise and authority in a particular field. This alignment with recognized entities can lead to increased trust and higher rankings in search results.

What is Google’s history with entities?

After investing in Freebase, Google realized that Wikidata had a better solution. Google then worked to merge Freebase into Wikidata, a task that was far more difficult than expected. 

Five Google scientists wrote a paper titled “From Freebase to Wikidata: The Great Migration.” Key takeaways include:

“Freebase is built on the notions of objects, facts, types, and properties. Each Freebase object has a stable identifier called a “mid” (for Machine ID).”

“Wikidata’s data model relies on the notions of item and statement. An item represents an entity, has a stable identifier called “qid”, and may have labels, descriptions, and aliases in multiple languages; further statements and links to pages about the entity in other Wikimedia projects –  most prominently Wikipedia. Contrary to Freebase, Wikidata statements do not aim to encode true facts, but claims from different sources, which can also contradict each other…”

How does Google handle unstructured entities like blogs?

Entities are defined in these knowledge bases, but Google still had to build its entity knowledge for unstructured data (i.e., blogs). 

Google partnered with Bing and Yahoo and created Schema.org to accomplish this task.

Google provides schema directions so website managers can have tools that help Google understand the content. Remember, Google wants to focus on things, not strings.

In Google’s words:

“You can help us by providing explicit clues about the meaning of a page to Google by including structured data on the page. Structured data is a standardized format for providing information about a page and classifying the page content; for example, on a recipe page, what are the ingredients, the cooking time and temperature, the calories, and so on.”

Google continues by saying:

“You must include all the required properties for an object to be eligible for appearance in Google Search with enhanced display. In general, defining more recommended features can make it more likely that your information can appear in Search results with enhanced display. However, it is more important to supply fewer but complete and accurate recommended properties rather than trying to provide every possible recommended property with less complete, badly-formed, or inaccurate data.”