In 2019, Google introduced the BERT upgrade, which marked a significant change in search technology. This big shift signalled the end of conventional keyword-centric search engine optimisation strategies and the beginning of a more sophisticated strategy based on entity-based SEO and Natural Language Processing (NLP).

BERT, or Bidirectional Encoder Representations from Transformers, improved Google's comprehension of the intent and subtleties of language by helping it to recognise the context of words in search requests.

This was more than simply a technical improvement; it was a fundamental shift in the way SEOs viewed content, prioritising entities—unique, recognisable things and concepts—above simple keyword optimisation.

Thanks to advancements in search technology, Google is now able to interpret the relationships and qualities of entities embedded in content, resulting in more accurate and relevant search results.

This change established a new benchmark for marketers and content producers using entity SEO to boost search engine rankings, highlighting the growing significance of semantic search and entity recognition in the SEO landscape.

An Entity Vs Keyword: Entity Based SEO Strategy

Entity-Based SEO is based on the idea of "entities," as opposed to traditional keyword-focused SEO, which focusses on optimising for certain words or phrases that are likely to be typed into a search engine.

These are discrete, recognisable concepts or physical objects that exist in both realms. Instead of focussing just on a list of keywords, Google and other search engines are now trying to comprehend and organise information around these things.

This change is the result of the requirement to comprehend user queries' contextual meaning and search intent more thoroughly.

What are Entities in Entity SEO?

Entities are distinct, recognised objects or ideas that fall under a precise definition. This encompasses individuals, locations, businesses, brands, and intangible ideas.

Entities aid search engines in understanding the context of material, enhancing the precision of search results. In order to deliver more accurate information on search engine results pages, search engine algorithms increasingly place more weight on entities than keywords.

For example, when a person searches for "Apple," search engines have to figure out if they're looking for the fruit, the tech business, or something else completely.

Example of Entity SEO: Related Entities

Think of "The Beatles" as a single unit. This entity is linked to multiple characteristics, including albums that are noteworthy, band members, and the genre of music they play.

Search engines are now able to differentiate between the band, certain insect species, and even themed products when they identify these links and provide more relevant results for queries pertaining to the Beatles.

Relationships Amongst Entities

Because of their characteristics and connections to other entities, entities are interrelated. These linkages are used by Google to create a Knowledge Graph, which is an extensive network of entities, qualities, and the conceptual, cultural, or historical connections among them.

For instance, the terms "Central Park," "Empire State Building," and "Statue of Liberty" may be associated with the entity "New York City."

Comprehending Entity Linking: Linking Text to Information

One of the most important tasks in natural language processing (NLP) is entity linking, which is finding and connecting textual references to entities (names of individuals, groups, or places) in unstructured text to the relevant entries in a knowledge base or database.

By integrating textual data with structured knowledge resources, the ultimate objective is to improve textual data analysis and comprehension.

Entity linking functions practically in a few essential steps:

1. Mention Detection: The first step involves identifying potential entities within the text. This can include named entities like “Barack Obama” or “Apple Inc.”, which are typically proper nouns that refer to specific entities.

2. Candidate Generation: Once mentions are detected, a set of candidate entities from a knowledge base (such as Wikipedia or a custom database) is generated. This step aims to create a pool of potential matches for each detected entity mentioned.

3. Disambiguation: After generating candidate entities, the system needs to disambiguate which candidate best matches the context of the entity mentioned in the given text. This involves considering various features such as context clues, entity popularity, semantic relatedness, and entity descriptions.

4. Linking: Finally, the selected candidate entity is linked to the original entity mentioned in the text, creating a direct connection between the unstructured textual data and structured knowledge.

Applications for entity linking can be found in many areas, such as knowledge graph creation, information retrieval, semantic search, and question answering systems.

NLP systems can help with a richer semantic understanding of text, information extraction, and search accuracy by associating textual mentions with entities in a knowledge base.

Entity linking systems' precision and efficiency are largely dependent on the calibre of the underlying knowledge base, the complexity of the disambiguation algorithms, and their capacity to manage context and ambiguity in natural language.

These methods are still being refined through ongoing research, which aims to increase recall and precision in entity linking tasks across several languages and domains.

The Google Knowledge Graph and Entities

Google collects data from a range of sources to improve search engine results, which is the basis of Google's Knowledge Graph.

Users see this information in a box adjacent to the search results. The way that information is identified and ranked is greatly impacted by these outcomes, which are produced based on entities and their connections.

What Is Entity-Based SEO?

Entity-Based SEO focusses on optimising the content of your website around Google-recognised entities and organising data so that search engines can read and process it more easily.

This entails giving thorough information that connects these entities to one another in a meaningful way in addition to simply mentioning pertinent entities.

Why do Entities Matter for SEO

Search engines use entities to help them comprehend the semantics of the content. They facilitate better content classification and indexing, resulting in more focused and pertinent search results.

Websites can increase user engagement and satisfaction, as well as their relevance and authority, by concentrating on entities.

When done correctly, SEO links your website, business, and Google knowledge graph with search intent and improves Google's comprehension of your material.

Semantic Search vs Entity Search engines

Understanding a user's intent behind a search query, as opposed to just the words they type, is known as semantic search. On the other hand, entity search entails finding and locating content that makes reference to particular entities associated with a query.

While both strategies seek to increase the precision and applicability of search results, entity search offers a more organised way to explore data.

Unstructured Data References

Online content is frequently unstructured, meaning it is just plain text without any clear indicators indicating how different pieces of information relate to one another. This unstructured material is transformed by entities into a structured format that search engines can comprehend and use more efficiently.

What Role Do Entities Play in Schema Markup and Structured Data?

Website owners can clearly specify which portions of their material represent entities by using schema markup and structured data.

This markup improves the accuracy of entity identification by directly communicating to search engines the details of entities seen on a webpage, such as a person's name, a product's price, or the date and location of an event.

Entities and NLP Words

Search engines are better able to detect entities and their relationships within the material Thanks to Natural Language Processing (NLP) technologies, which allow search engines to comprehend the context in which words and phrases are employed. For human language to be parsed in a form that makes sense to humans, natural language processing (NLP) is essential.

Importance of NLP in SEO

NLP improves search engines' ability to understand the relevance and meaning of content for given search queries. It is essential to content ranking, particularly when evaluating how well a piece of information corresponds with related entities and satisfies user intent.

How to Use Entities on Your Website

Determine which entities are pertinent to your sector, business, or content.

Conduct an entity audit of your competitors and market.

For your pages, use schema markup to make the entities more clear.

Provide comprehensive explanations and connections between these entities in your content so that search engines can comprehend and index it.

Start with an Entity Audit

Make sure your website appropriately represents the entities associated with your brand in order to maximise the benefits of entity-based SEO.

You start by performing an entity audit.

The goal of this audit is to make sure you have the best entities for your website by going over yours and comparing it to those of your competitors.

Are you having trouble locating the proper entities for your website? Researching entities is becoming easier due to AI developments.

Head of SEO John Butterworth describes how he uses AI to collect pertinent entities:

Since ChatGPT's release, it has completely changed the way I find and include pertinent elements in my writing. Although NLP phrase identification tools like SurferSEO are excellent, they only provide terms that are already utilised by pages that score highly. This implies that they could lose out on significant entities that rivals haven't yet employed.

Herein lies the value of ChatGPT. It can reveal hidden entities, which could greatly improve your content. For instance, utilising this unique prompt he created:

Boost Your Knowledge Graph Card

In May 2012, Google debuted their knowledge graph and advertised it under the slogan "Things, not strings."

With the help of the knowledge graph, a sizeable database, Google is able to respond to questions regarding actual entities in real time. Semantic SEO has become even more important because it improves search engine rankings, user experience, and visibility for your website.Use Structured Data to improve your knowledge graph:

Organising content on your page in a structured data format makes it easier for search engines to classify and display it in search results. Schema markup is a useful tool for applying organised data. It improves the description of the data on your website, making it simpler to find in search results.

On schema.org, you can find a variety of entities to include on your website, such as:

Creative works like books, movies, and music

• Embedded objects such as audio, images, and videos

• Events

• Health and medical types

• Logos

• Names

• Organisations

• Local Business

• People

• Places, local businesses, restaurants

• Website

• Products and offers

• Reviews and ratings

• Actions, and more

Structured data helps you rank higher in search engine results pages and improves your knowledge graph card.

Gunmade.com founder Brady Kirkpatrick talks about his experience:

"We had trouble ranking high at GunMade.com before utilising structured data. However, Google was able to comprehend our content more fully after using structured data to emphasise costs and optimise information around organisations like gun manufacturers. As a result, we rose from constantly ranking on pages two or three to page one for numerous keywords.

It's important to review Google's requirements for required features for structured data and to verify your markup using the Markup Testing Tool.

Think about using free and open data sources such as DBpedia and Wikipedia as well. Google frequently uses these platforms, which can greatly increase the dependability and exposure of your website. It can be advantageous to create a Wikipedia page for your company if you don't already have one.

Keeping Track of Entity-Based SEO Results

Using tools like Google Analytics and Search Console, monitor the effectiveness of your entity-based SEO approach by keeping an eye on key performance indicators like page views, bounce rate, and conversions. Based on these insights, modify your approach to more effectively target and interact with your audience.

Tools to Help Find Entities

There are a number of specific tools that can greatly assist you in your efforts to efficiently identify and assess entities for SEO purposes:

1. Topically – This tool leverages data from Google Images and search modifiers to help understand entity relationships and user intent. It offers a hierarchical view of these relationships, providing insights into how entities are connected and how they can be utilised in content for better SEO performance.

2. InLinks – This tool focuses on content optimisation through entity, keyword, intent, and gap analysis. InLinks generates detailed content briefs that include topic maps and suggested content structures based on the entities and concepts surrounding your target keywords.

3. Entity Analyser – Provides a suite of tools designed to enhance your SEO strategy by helping you explore entities related to your content and industry. Features include the ability to generate structured entity schemas for your web pages, which can improve how well search engines understand and rank your content.

4. WordLift – Offers a free tool for extracting entities using AI. It analyses content to identify all relevant entities and links them to their corresponding Wikidata descriptions, enhancing SEO benefits through better content understanding and AI-enriched schema markup.

5. Zizta’s Entity Explorer – This tool excels in researching and identifying the best entities and phrases that align with user intent and topical relevance. It provides features such as keyword and entity density analysis, optimising your content visibility and relevance in search engine results.

These tools are an essential resource for anyone wishing to optimise their online presence through a deeper understanding of entities and their impact on search rankings. They cover a wide range of entity-based SEO factors, from content generation to technical SEO optimisations.

Helping Your Google Presence

You may increase your website's search engine exposure and give users a more interesting, engaging experience by incorporating Entity-Based SEO.

Using your brand (company name) and linking entities to it to create an online relationship between the two is something to think about.

I have been using this SEO technique at RedKite SEO for the past three years to assist businesses establish their presence in their industry and secure digital marketing opportunities as well as appropriate website traffic derived from organic search results.