The TLDR on Entity-Based SEO
- “Entity SEO” is a concept that describes a transformative shift in Google’s search engine algorithm. Instead of relying solely on keywords, Google now places increased emphasis on entities, defined as uniquely identifiable objects or things. Entities are characterized by their names, types, attributes, and relationships between entities.
- The birth of Entity-based SEO can be traced back to Google’s pivotal blog post, “Things, not strings.” This post signified the evolution of Google’s algorithm from a straightforward keyword detection system to a sophisticated model capable of discerning the underlying meaning behind keywords, thanks to machine learning.
Since Google’s blog post in 2012, titled “Things, Not Strings”, a new type of SEO was developed, called Entity SEO.
Entity SEO is different to “Traditional SEO”, SEO that focuses on keywords and written content. Instead of this, entity SEO looks for context. Context in names, types, attributes, and relationships, helping boost the accuracy of search results.
The Basics of Entity-Based SEO
Entity SEO Definition
“Entity SEO” is a concept that describes a shift in Google’s search engine algorithm. Instead of relying solely on keywords, Google now places increased emphasis on entities, which are defined as uniquely identifiable objects or things. Entities are characterised by their names, types, attributes, and relationships between entities.
Examples of Entity SEO
A good example of entity SEO is the “Eiffel Tower”.
It has a unique name, “The Eiffel Tower”, a type (it’s a monument), attributes (like its height, location, and construction date), and relationships to other entities (like Paris, Gustave Eiffel, and France).
Reference: Entity SEO Eiffel Tower Example
This is just one example, however. An entity can be a lot of things. For example, it could also be a person, such as Gordon Ramsay.
Reference: Entity SEO Gordon Ramsay Example
The list goes on and on as well, it could be products, people, places, locations, it doesn’t matter. It could even be a company, big or small, like the following from Meta.
Reference: Entity SEO Meta Example
Wikipedia entries are also classic examples of entities, providing comprehensive information about a particular entity.
An entity gains recognition when it is catalogued in an entity catalogue such as Wikipedia, Wikidata, DBpedia, Freebase, or Yago, which assigns a unique ID to each entity
Understanding Entity SEO
The easiest way to understand entity SEO is that it’s all about context, not keywords like traditional SEO.
Instead of this keyword-centred “traditional SEO”, Entity SEO introduces a new approach. It leverages the semantic integrity of the content to understand what it is.
Entity SEO focuses on the core of your information, such as a business or service, unlike the old strategy of focusing purely on keywords.
An entity, for example, can be a person, place, or thing. Google’s knowledge graph utilises these entities to better understand the context and intent behind searches.
In SEO, entities can help refine search results and provide more accurate matches for user queries. Semantic SEO plays a great role in optimising entities and building authority.
Semantic SEO, also related to Entity-Based SEO, aims to improve the context within a given content. By maintaining relevance and consociation between the entity and corresponding content, the search engines find it easier to index and rank pages.
Knowing the intent behind searches is key
For instance, how is your entity related to other linked entities within your page? Is your website’s information answering the real intent of your customer’s searches? These are the questions that can guide us in creating great Entity SEO strategies.
Ultimately, taking an entity and an entity approach to SEO presents related opportunities to enhance your business’ online presence.
By understanding and implementing an Entity SEO strategy, your website’s content can surpass mere links and keywords, moving into the realm of Entities- a realm in which context, knowledge, and intent reign supreme.
Why are search results pivoting towards the Entity-based search model?
Understanding the importance of entities in Entity SEO isn’t just useful; it’s becoming essential.
We’re observing an apparent pivot in search results towards an Entity model. This approach, postulated by SEO gurus like Dave Davies and Sara Taher, believes that search engines are moving away from traditional keyword-based SEO, focusing more on the ‘entities’ associated with the keywords.
The primary goal is to contextualise content based on the entity related to it. Entity SEO is, thus, positioning itself as a revolutionary guide, placing a larger emphasis on users’ intent and the context of search queries.
Context is very important. A good way to explain this is by looking at the word apple. Apple means two things: the fruit or the company. Traditional SEO finds it hard to differentiate the two, but entity-based SEO does not, as it delivers more targeted search results.
Entity Catalog to the Knowledge Graph
Entity Catalogues (like Wikipedia) and Google’s Knowledge Graph go hand-in-hand for entity SEO.
Imagine the Knowledge Graph as a giant, interconnected web of information. It’s made up of three key layers:
- Entity Catalogue: Think of this as a vast library where every single ‘entity’ (like people, places, things) that’s been identified over time is stored. It’s like having a card for every book in a library, but for every piece of information on the internet.
- Knowledge Repository: This is where things get organised. Here, all the entities from the Entity Catalog are brought together. It’s like putting all those library cards into neat categories and adding detailed descriptions to each. Google has something called the Knowledge Vault, which is their version of this repository.
- Knowledge Graph: Now, imagine adding strings to connect all those categorised cards, showing how they relate to each other. In the Knowledge Graph, we add attributes (like details and characteristics) to each entity and establish relationships between them. This creates a massive, interconnected web of information.
What are Entity Attributes?
Think of an ‘entity’ in a knowledge database like the main character in a story. This entity could be anything – a person, a place, an event, or even a concept. Now, around this main character, they gather all sorts of information, much like details in a story.
- Attributes: These are the characteristics or properties of the entity. Imagine describing a person; attributes could include their name, age, occupation, etc. For a place, it might be the location, population, and climate.
- Entity Types: This is like assigning a genre to our main character. Is the entity a person, a place, a business, a product? Classifying entities helps in organising the data better and makes it easier to find in a search.
- Social Media Profiles: For entities that are people or organisations, linking their social media profiles is like adding a modern twist to their story. It provides real-time, dynamic information about them.
- Media: Just like illustrations in a book, media (like documents, videos, audios) add depth to the entity’s profile. They provide a richer, more engaging way to understand the entity.
- Related Entities: Finally, think of related entities as supporting characters in our main character’s story. They show connections and relationships, like family members, colleagues, historical events, etc.
Entity Attribute Example
Think of an entity attribute as a specific detail or fact about something or someone. In the world of SEO and knowledge databases like Wikidata, these attributes help to paint a complete and detailed picture of an entity.
The following attributes are for Gordon Ramsey:
- Gender: Male
- Country of citizenship: United Kingdom
- First name: Gordon
- Last name: Ramsay
- Date of birth: November 8, 1966
- Birthplace: Johnstone, Scotland
- Spouse: Tana Ramsay
- Number of children: 5
- Language spoken or published: English
- Occupation: Chef, Television presenter, Restaurateur, Writer
- Known for: Multiple Michelin star restaurants, television shows like Hell’s Kitchen and MasterChef
- Awards received: Several culinary and television awards
- Residence: London
These attributes on Wikidata create a comprehensive profile of Gordon Ramsay, giving a clear understanding of who he is, his background, career, and personal life. The Wikidata record for Gordon Ramsay would present these attributes in a structured format.
Common Terminology for Entity SEO
We often come across terms like ‘entity types’ and ‘domains’ or ‘classes’. These terms help us group together entities (like people, places, or things) that share similar characteristics. It’s like sorting different items into boxes based on their features.
- Entity Types and Domains: Imagine you have a box labelled “Person” or “Human.” In this box, you would place entities that are people. All these people would have common attributes like place of birth, place of residence, date of birth, etc. These common attributes define the domain and associated entity types. It’s like having categories and subcategories.
- Example of Gordon: In the case of Gordon Ramsay, his entity type could be “Chef” or “Television Presenter.” This indicates that he belongs to a group of entities sharing characteristics common to chefs or television presenters, such as the names of the restaurants they run, the culinary styles they are known for, or the television programs they host.
- Entity Types – Similar to Object-Oriented Programming: To make it even simpler, think of it like object-oriented programming in computers. In this analogy, an entity type is like a class, and each entity (like Gordon Ramsey) is an instance of that class. They all share the properties defined by the class but also have their own unique attributes.
Sources for Entity Data
Let’s talk about the different sources Google uses to gather information for the attributes of entities in its Knowledge Graph.
Understanding these sources can really help grasp how SEO works and how to find SEO entities.
Sources for Unstructured Data:
- Normal Web Pages: Google ‘crawls’ through regular websites, collecting information. Using Natural Language Processing (NLP), it understands and extracts entity information from the content.
- Search Queries: Google also analyses the search queries people type in. Again, using NLP, it extracts information about entities and their relationships.
- Unstructured Databases and Datasets: These are databases that don’t have a fixed format. Google can pull entity information from these as well.
- The Knowledge Vault: This is a special case. Google uses it to identify and interpret entities from unstructured content. It’s a large-scale database that combines extracted information from the web with existing databases.
Sources for Semi-Structured Data:
- Encyclopaedias like Wikipedia: These sites have a systematic structure that makes it easier for Google to extract information. Wikipedia is a rich source for entity attributes.
Sources for Structured Data:
- Semantic Databases and Datasets: This includes databases like Wikidata (formerly Freebase), Google My Business, CIA World Factbook, DBpedia, and YAGO. These databases are already organised in a structured manner, making it easy for Google to use their data.
- Websites with Structured Data: Websites can structure their data using Microdata, RDFa, and JSON-LD. This structured format is easily readable by Google for use in the Knowledge Graph.
- Licensed Data and Datasets: These are data sources that Google has permission to use. Examples include ClueWeb09 to ClueWeb12, Common Crawl, and KBA Stream Corpus.
Entity SEO vs Traditional SEO
| Aspect | Entity SEO | Traditional SEO |
| Focus | Centres on entities (people, places, things, concepts) and their relationships | Centres on keywords and phrases to target search terms |
| Understanding | Uses meaning and context to determine relevance | Uses keyword matching to determine relevance |
| Content Structuring | Organises content around entities and related topics, focusing on context and connections | Organises content around specific keywords and their variations |
| Search Result Accuracy | Improves accuracy by distinguishing between entities with the same name (e.g., Apple company vs. fruit) | Can struggle to differentiate ambiguous terms without additional keywords |
| Optimisation Techniques | Relies on structured data, schema markup, and semantic content clusters | Relies on keyword density, meta tags, and backlinks |
| Search Features | Prominently uses Knowledge Panels, answer boxes, and rich snippets | Primarily uses standard search result listings |
| Role of Google’s Knowledge Graph | Utilises the Knowledge Graph to establish entity relationships and boost visibility | Not directly connected to the Knowledge Graph, relies more on links and keywords |
| Relevance for User Intent | Highly relevant for complex or ambiguous searches, as it understands entity context | Primarily relevant for straightforward, keyword-driven searches |
| Optimisation Goal | Focuses on defining entities and their relationships to improve authority and context | Focuses on matching search queries with exact or similar keyword phrases |
| Impact on Search Ranking | Builds authority and relevance by establishing connections between entities | Builds authority and relevance primarily through keyword targeting and link-building strategies |
How to Optimise for Entity SEO
Step 1: Identify Important Elements
Start with an Entity Audit by looking at your website and determining the key things you’re discussing. This could be your products, services, or events you’re hosting in a specific location.
Afterwards, determine the “type” of entity (e.g. a person, place, product, or concept) and how these elements relate to one another.
When performing this step, think of it as a bit of organising. You’re organising your content around unique identifiers that make your website valuable.
Step 2: Use Structured Data
Once you know what’s important on your site from the entity audit, you’ll want to describe these things in a way that search engines understand.
This is where structured data comes in. It’s like giving search engines a clear roadmap of your site. You can create a schema by following the documentation of Schema.org. They also have a schema validation so you can test your schema before putting it on your website.
For example, if your website includes a product listing, Product Schema can help describe the name, price, and reviews to search engines in a language they understand. Scheme (or structured data) is what allows search engines to display rich, informative snippets on the SERPs.
Step 3: Create Quality Content
Content is central to Entity SEO, but it goes beyond what people call “traditional” SEO.
You need to create rich, informative content that doesn’t only allow search engines to understand your website but content that also benefits the reader.
One thing you can do, other than creating quality content, is grouping related topics together to form “content clusters”. This will improve site navigation as well as help search engines build connections between your different services, products, locations, etc.
For example, if you own a furniture website, creating content clusters for chairs, tables, sofas, etc., would help both search engines and your target audience.
When creating content, standard on-page SEO strategies should always be considered. These will help improve everyone’s overall experience.
Step 4: Internally Link Pages Up
You should also be internally linking pages on your website to reinforce relationships between topics. For example, if you have an article about “Best SEO Practice”, you can link to other related articles like “Structured Data”, “Semantic Search”, etc. This will help build topical relevance.
Step 5: Keep an Eye on Performance
Always keep track of your entity’s SEO efforts. Use tools like Google Analytics and Google Search Console to see whether these efforts are bringing in results. Monitor what’s working and what isn’t. Double down on what works and get a better understanding of why some pages aren’t working.
Tools for Finding and Optimising Entities
Here are ways to find entities using tools:
- Google Image Search
- Google Trends for related queries and topics
- Wikipedia for main entity research and related topics
- Google Knowledge Graph Search API
- InLinks – a company specialising in semantic SEO
Google collects information about entities and their relationships from a variety of sources, ranging from unstructured web content and search queries to structured and semi-structured databases
Final Word
By embracing the entities approach in SEO, you’re not just hopping on the latest bandwagon, you’re revolutionising the way you conquer the search engine realm. Say goodbye to outdated strategies and hello to a whole new level of online success.
With this cutting-edge entity-based approach, your website will soar above the competition, delivering mindblowingly relevant entities and mind-expanding search results to users. Don’t just stay ahead of the SEO curve, leapfrog over it with confidence and creativity.
