Entity-Based SEO: When SEO is taken to the next level

Why is Entity SEO Replacing Keyword-Based SEO?

Keyword SEO: An Outdated Approach?

For years, SEO revolved almost entirely around keywords. You'd identify popular search terms, incorporate them into your content, and voilà! You hoped to climb the SERPs (search engine results pages). But Google changed the game. Now, it's no longer just about isolated words but comprehensive understanding.

This evolution prioritizes deep content comprehension over simple lexical matching. SEO professionals and marketers must now create content rich in relevant information, structured around interconnected entities.

Modern optimization requires a holistic approach, integrating:

• Content semantics

• Relationships between concepts

• Overall thematic consistency of the site

This new era of SEO demands increased expertise and fine understanding of the topics covered to meet the expectations of both users and search engines. That's why you can't really do proper SEO without having a broader content strategy aligned with your brand positioning.

From Semantics to Entities

Today, Google strives to understand the context of your content, not just simple keyword repetition. For example, if you write about "Elon Musk," Google knows he's connected to concepts like SpaceX, Tesla, and even interplanetary travel. This is where Entity SEO comes into play: semantic relationships.

Semantic relationships between entities form the foundation of Entity SEO. Instead of focusing on isolated keywords, this approach aims to create a network of interconnected concepts. Google analyzes these connections to better understand context and content relevance.

Entity-based optimization involves identifying key concepts related to your topic and integrating them naturally into your texts. This method allows you to build a rich semantic structure that reflects the complexity of the subject addressed.

By adopting this strategy, your site gains thematic authority in the eyes of search engines. Semantic consistency between your pages reinforces their overall relevance, potentially improving their ranking for various queries related to your area of expertise.

Relevance Above All

By emphasizing relationships between entities, Google seeks to offer more relevant and nuanced results to users. This means that even if you don't use exactly the same keywords, your content can still be considered relevant thanks to its entity connections. Gone are the days of keyword stuffing—hello, quality!

For example, a search for "apples" might include information about nutrition, fruit cultivation, and cooking recipes, even if these pages don't use the word "apple" repetitively.

To leverage this evolution:

• Create content rich in related information

• Use varied vocabulary around your main topic

• Establish connections between related concepts

This strategy not only improves your visibility in search results but also enriches your visitors' experience.

The Role of the Knowledge Graph in Entity SEO

What is the Knowledge Graph?

You've surely noticed those enriched information boxes that appear to the right of Google results. They're part of the Google Knowledge Graph, a gigantic database that connects entities and concepts. The Knowledge Graph enables Google to understand not only what things are, but also how they're connected.

This interconnected structure facilitates deep contextual understanding of user queries. The integration of diverse data sources continuously enriches this network, improving the precision and relevance of search results. This approach allows Google to provide more nuanced and contextualized answers to users' questions.

How Does It Work?

Let's take an example. If you search for "Marie Curie," Google knows she's a scientist, that she worked on radioactivity, and that she's linked to entities like Pierre Curie, the Nobel Prize, and radioactive isotopes. Thanks to this understanding of relationships, the search engine can offer richer and more precise results.

The Knowledge Graph analyzes and interconnects millions of data points from various sources. For example, a search for "radioactivity" might include links to Curie's work, even if her name isn't explicitly mentioned in the query.

The Knowledge Graph also adapts to search intent. A query for "Marie Curie biography" will generate different results than a search for "Marie Curie scientific contributions," highlighting the most relevant aspects of her life or work.

Concrete Examples of Knowledge Graph Applications

The Knowledge Graph manifests in several forms: the knowledge panel (which groups all key information about an entity), rich results (like reviews, hours, events), or dynamic FAQs. Each search then becomes a much more contextualized experience.

The Importance of Well-Structured Content and Semantic Entities

Keywords Out, Entities In

As you've understood, Entity SEO isn't just about optimizing a few keywords. It's about structuring your content around important entities so Google can understand their relationships. In other words, you need to think about the overall consistency of your pages.

The Power of Content Clusters

To get the most out of Entity SEO, it's essential to create content clusters. These clusters involve organizing your pages around main topics (key entities) and linking these pages together. This reinforces semantic context and helps Google better understand the relationships between your content.

Content clusters constitute a major asset for improving a website's natural referencing. By grouping thematically related content, they strengthen the site's authority on specific subjects.

This approach promotes better context understanding by search engines, thus increasing visibility for varied queries. For example, a cluster on "sustainable nutrition" could include articles on organic agriculture, locavorism, and reducing food waste.

Content clusters also optimize user experience by facilitating navigation between related content. This logical structure encourages visitors to explore the site further, reducing bounce rate and increasing time spent on the site—two factors appreciated by Google.

But this is only part of an entity-based strategy since entity-based SEO doesn't happen only on your site. And I'm not talking here about traditional link building—what ultimately matters is that people talk about you, with or without links, in a context aligned with your objective.

Semantic Links and Relevance

By creating well-organized clusters, you allow Google to navigate more easily through your pages and understand semantic relationships. For example, an article on "project management" should be connected to pages about requirements documents, PERT methodology, or risk management.

This internal linking is just as important for your users as for search engines. Understand that we all function this way when we're interested in a topic. For a more detailed view of this subject, we've made a great video:

Practical Optimization: How to Optimize a Site for Entity SEO?

Structuring Content with Entities

To properly optimize your site for Entity SEO, start by identifying the most relevant entities for your topic. Use tools like Google NLP to discover how Google interprets your content and which entities are highlighted.

Naturally integrate key entities into your titles, subtitles, and opening paragraphs. Create contextual links between these entities by mentioning them together in relevant sentences.

For example, a photography article could link the entities "camera," "exposure," and "composition" in a paragraph about basic techniques.

Use bullet lists or tables to clearly present relationships between entities. Enrich your content with concise definitions and examples illustrating connections between concepts.

Don't forget to include secondary entities related to your main topic to broaden semantic context. A text about coffee could thus mention roasting methods, bean varieties, and producing countries.

The Importance of Structured Data

Structured data, like those provided by Schema.org, are crucial for Google to better understand relationships between your entities. For example, by adding specific tags to your articles (like Person, Organization, or Article), you help Google connect your content to broader entities.

We have a great tool, completely free, that can help you write your structured data: Schema markup generator

It's our gift to you!

Co-occurrence and SEO

Finally, think about co-occurrence: the more related entities appear simultaneously in your texts, the more Google understands they're important in the same context. This technique improves your content's semantic relevance and makes it more accessible to search engines.

The Future of Entity SEO: Artificial Intelligence and Semantic Search

Google Becomes More Intelligent

Entity-Based SEO is just the beginning. With the rise of artificial intelligence and machine learning, search engines will become increasingly adept at understanding complex relationships between entities. Tools like Google BERT already allow grasping context and nuance in queries, making search ever more precise.

The Role of AI in Entity SEO

AI enables analyzing tons of data and detecting entities even more precisely. This means that in the near future, Entity SEO will be inseparable from advances in artificial intelligence. Sites that adapt to this new reality will have a clear advantage.

Entity SEO vs Semantic Cocooning: Understanding the Differences

While Entity-Based SEO and semantic cocooning are both advanced natural referencing strategies, they rest on different concepts. Here's a comparison to better understand these two approaches.

Semantic Cocooning or Clustering

Semantic cocooning is a content structuring technique based on organizing pages around related topics, thus creating a very strong internal link network between different pages of a site. This model aims to guide users (and Google) through a logical path, reinforcing page relevance based on their context and targeted main keyword. The main characteristics of semantic cocooning are:

• Content organization in clusters: Content is grouped into sub-themes that logically nest within each other, creating a very coherent tree structure.

• Optimized internal links: Pages in the same cluster are intensively linked to reinforce their relevance in search engines' eyes.

• Focus on keywords: Although the cocooning strategy aims to cover topics in depth, it relies heavily on creating content based on specific target keywords.

Entity-Based SEO

Unlike semantic cocooning, Entity-Based SEO doesn't focus on organizing pages around keywords, but rather on recognizing and highlighting entities (people, places, objects, concepts) that are important for a given topic. The emphasis is on how search engines understand semantic relationships between entities. Key elements of this strategy are:

• Relationships between entities: Google seeks to understand the relationship between mentioned entities (for example, how a company is connected to a technology or business sector).

• Content contextualization: Entity SEO seeks to optimize Google's overall understanding of a topic through the presence and clarity of entities rather than through repeated keyword use.

• Relevance development through entities: Instead of focusing solely on content clusters linked by keywords, Entity SEO focuses on entities and their connections to optimize SERP positioning.

Comparison of Both Approaches

How to Choose Between These Two Approaches?

The choice between Entity-Based SEO and semantic cocooning depends on your SEO objectives and the type of site you manage:

• For an information site or blog: Semantic cocooning may be more relevant if you want to structure a large quantity of content around different topics and sub-topics, while optimizing internal links to maximize SEO relevance.

• For a site focused on information quality and relationships between concepts: Entity-Based SEO can offer better results if you want to maximize Google's semantic understanding and its ability to connect entities in your domain (for example, for technical or B2B content).

In reality, both approaches are complementary and overlap in certain aspects. But the nature of linking and the optimization method for each article differ.