Google's search engine has not thought in keywords for years. It thinks in entities — named concepts like people, places, businesses, products, and ideas, and the relationships between them. The Knowledge Graph, Google's massive database of entities and relationships, is the foundation on which both traditional search results and AI Overviews are built. For SEO, this means keyword optimization alone is no longer sufficient. You need to build your brand as a recognized entity in Google's understanding of the world. This guide provides a complete approach to entity SEO — from theory to practical implementation.
What entities are in Google's understanding
An entity is a concept that is uniquely identifiable and distinct from other concepts. It can be a person (Elon Musk), a place (Oslo), an organization (LeapJet), a product (iPhone 16), a concept (machine learning), or an event (2028 Olympics). Entities are not keywords — they are defined things with properties and relationships.
Google defines an entity as "a thing or concept that is singular, unique, well-defined, and distinguishable" (Google Patents, US8898152B1). This definition is the core of how Google understands content. When you write about "apple," Google understands from context whether you mean the fruit, the technology company, or the record label — because all three are separate entities with different properties and relationships.
For SEO, this means optimization is about helping Google understand which entities your content covers and how they relate to each other. It is a fundamentally different approach than focusing on keyword density and search volume.
How Google's Knowledge Graph works
Google's Knowledge Graph launched in 2012 and as of 2025 contains over 500 billion facts about more than 5 billion entities, according to Google (Google Blog, 2023). It is a graph-based database where entities are nodes and relationships are edges. Each entity has a unique ID (a "machine ID" or KGMID) and a set of properties and relationships.
The Knowledge Graph powers Knowledge Panels in search results, "People also ask" boxes, related searches, and increasingly AI Overviews. When Google presents information like "Oslo is the capital of Norway with 709,000 inhabitants," those facts come directly from the Knowledge Graph.
Sources for the Knowledge Graph include Wikipedia, Wikidata, CIA World Factbook, Freebase (now integrated), public databases, and information Google extracts from web pages using Natural Language Processing (NLP). For businesses, the most important sources are Google Business Profile, Wikipedia, Wikidata, and structured data on the website.
Trust levels in the Knowledge Graph vary. Information from Wikipedia and public databases has high trust. Information from structured data on websites has moderate trust. Information found only in a single source has low trust. The more independent sources confirming an entity and its properties, the stronger Google's understanding.
Why entity SEO matters more than ever
AI search engines think in entities, not keywords. When ChatGPT, Perplexity, or Google AI Overviews generate an answer, they first identify the entities in the query, then find sources that are authoritative for the relevant entities. This means brands that are recognized entities have a fundamental advantage.
According to a study by SEMrush (2024), websites with recognized Google Knowledge Panels have 35% higher probability of being cited in AI Overviews compared to websites without a Knowledge Panel. The reason is simple: Google has already established that these websites are authoritative sources for specific topics.
For a deeper understanding of how AI search engines select sources and how entity optimization fits into a broader GEO strategy, we recommend our complete GEO guide to generative engine optimization. You can also read our guide to AI search engine optimization for a practical overview of optimizing for ChatGPT, Perplexity, and Google AI Overviews.
Building your brand as a recognized entity
Building your brand as a recognized entity is the single most important action in entity SEO. It is about establishing a consistent, verifiable identity across all sources that Google and AI engines trust.
Start with Wikipedia and Wikidata. A Wikipedia article about your company is the strongest signal you can send to Google's Knowledge Graph. The article must meet Wikipedia's notability requirements, which means the company must have independent media coverage. A Wikidata entry can be created independently of Wikipedia and provides structured entity information directly to Google.
Crunchbase, LinkedIn Company Page, and Google Business Profile are the next priorities. These sources are actively used by AI engines to verify business information. Ensure that NAP data (name, address, phone), descriptions, and categorizations are consistent across all profiles.
- Wikipedia — the strongest entity signal, requires notability and independent sources
- Wikidata — structured entity data that Google reads directly, can be created without Wikipedia
- Google Business Profile — the foundation for local entity recognition
- Crunchbase — important for technology and service companies
- LinkedIn Company Page — verifies organizational data and employee profile connections
- Industry-specific directories — strengthen entity relevance within the field
- Consistent NAP data and descriptions across all profiles
Entity-first content strategy: From keywords to topic graphs
An entity-first content strategy replaces keyword lists with topic graphs — visual maps of entities and the relationships between them. Instead of writing articles based on search volume, you write articles that cover entities and their relationships within your domain.
Start by identifying the core entities for your business. For a digital marketing agency like LeapJet, core entities might be: SEO, GEO, content marketing, Google Ads, conversion optimization. Around each core entity are related entities: for SEO it could be technical SEO, link building, local SEO, entity optimization.
Then build content that covers the relationships between entities. An article about "how entity SEO improves local visibility" connects two entities and strengthens your authority on both. The more relationships you cover, the stronger your topical authority becomes in Google's eyes. Read more about building topic clusters in our SEO content strategy guide at /blog/seo-content-strategy-topic-cluster.
Entity gap analysis: Finding holes in your entity coverage
An entity gap analysis reveals which entities your competitors are associated with that you are not. This gives you a concrete roadmap for content production and authority building.
Conduct the analysis in three steps. First: map which entities your competitors' content covers by analyzing their top-ranking pages with Google's NLP API or TextRazor. These tools identify the entities in the text and categorize them. Then: do the same for your own content. Finally: compare and identify entities your competitors cover that you are missing.
Prioritize entities based on two criteria: relevance to your business and frequency in AI citations within the field. Entities that competitors are consistently cited for in AI answers should be prioritized highly. Use tools like InLinks to visualize entity graphs and identify the most important relationships.
Schema markup for entity disambiguation
Schema markup is your primary mechanism for communicating entity information directly to search engines and AI systems. For entity SEO, the most important schemas are Organization, Person, SameAs, and knowsAbout.
Organization schema with sameAs links to Wikipedia, Wikidata, LinkedIn, Crunchbase, and other profiles is the most fundamental step. It tells Google explicitly which profiles belong to your entity. The knowsAbout property lets you declare which topics the organization has expertise in.
Person schema for authors and subject matter experts strengthens E-E-A-T signals (Experience, Expertise, Authoritativeness, Trustworthiness). Connect author profiles with sameAs to LinkedIn, Google Scholar, industry profiles, and other authoritative sources. For a complete guide to schema implementation, see our guide to schema markup and structured data. Also read our guide to E-E-A-T and authority building to understand how Google evaluates expertise and trustworthiness.
- Organization — with name, url, logo, sameAs, knowsAbout, foundingDate
- Person — for authors, with sameAs to LinkedIn, Google Scholar, industry sites
- SameAs — links to all official profiles for entity disambiguation
- knowsAbout — declares expertise areas for organization and individuals
- Article with author reference — connects content to author entity
- LocalBusiness — for businesses with physical locations, connects to place entities
Topical authority through entity clusters
Topical authority means becoming the preferred source within a defined subject area. AI engines and Google assess topical authority based on depth, consistency, and quality of content production over time.
Build entity clusters — groups of content covering a core entity and all related sub-entities. For example: a pillar page on "entity SEO" linked to supporting articles on "Knowledge Graph," "schema markup," "Wikidata optimization," "NER analysis," and "topical authority." Each supporting article strengthens the authority of the pillar page.
Consistency in publishing matters. Google and AI engines evaluate not just the volume of content but also the frequency and recency. A site publishing weekly within a subject area over 12 months builds stronger topical authority than a site publishing 50 articles at once and then stopping.
Entity optimization for local businesses
For local businesses, entity SEO is particularly powerful because it connects the business entity to local place entities. Google understands that "LeapJet is a digital agency in Fredrikstad" by linking two entities — the organization and the place.
Google Business Profile is the most important tool for local entity optimization. Ensure the profile is complete with correct categories, business hours, photos, and regular posts. Consistent NAP data across all local directories strengthens entity trust.
For local businesses serving multiple areas, build location-specific content that connects service entities to place entities. A page about "SEO services in Oslo" connects three entities (SEO, services, Oslo) and strengthens visibility for local searches. For more on local SEO strategy, see our guide at /blog/local-seo-guide-businesses.
Named Entity Recognition (NER): How AI identifies entities in your content
Named Entity Recognition (NER) is the technology AI systems use to identify and categorize entities in text. When Google crawls a page, it runs NER analysis to understand which entities the content covers and how they relate to each other.
NER categorizes entities into types: people, organizations, places, products, events, concepts, and more. The more clearly you name entities in your content, the easier it is for NER systems to identify them. Use full names ("Google Knowledge Graph" instead of "the graph") and be consistent throughout the article.
You can test how Google understands the entities in your content using the Google Cloud Natural Language API. The tool shows which entities are identified, their categories, and Google's confidence level. Use this as a diagnostic tool to ensure your content communicates the right entities.
Practical entity SEO audit checklist
This checklist covers the most important steps for implementing entity SEO. Use it as a starting point for auditing your current entity strategy.
- Does your company have a Wikipedia article or Wikidata entry?
- Is Organization schema implemented with sameAs to all official profiles?
- Are authors identified with Person schema and sameAs links?
- Is NAP data (name, address, phone) consistent across all profiles?
- Does your company have a Google Knowledge Panel?
- Is the content strategy based on entities and relationships, not just keywords?
- Do you use NER analysis to verify that content communicates the correct entities?
- Have entity clusters been built with pillar pages and supporting articles?
- Do you publish consistently within your core entities?
- Do you monitor Knowledge Panel and entity visibility regularly?
Tools for entity analysis
Several tools can help with entity analysis and optimization. Here are the most important, ranked by usefulness for entity SEO.
Google Cloud Natural Language API is the most direct tool for understanding how Google interprets your content. It analyzes text and identifies entities with category, salience score, and Wikipedia link. Use it to verify that your content communicates the entities you intend.
InLinks is a dedicated entity SEO tool that builds entity graphs, identifies internal linking opportunities based on entity relationships, and generates schema markup. WordLift does something similar with focus on structured data and knowledge graphs for websites. TextRazor is a powerful NLP API that identifies entities, categories, and relationships in text.
- Google Cloud Natural Language API — entity identification with Google's own technology
- InLinks — entity graphs, internal link optimization, and schema generation
- WordLift — knowledge graph for websites and structured data
- TextRazor — advanced NLP with entity extraction and categorization
- Wikidata SPARQL — querying Wikidata to understand entity relationships
- Google Search Console — monitor Knowledge Panel and rich results
Entity SEO and the future: How entity graphs power AI answers
The future of search is entity-driven. Both Google and AI search engines are moving toward a model where understanding of topics and relationships replaces keyword matching. Brands that invest in entity SEO now are building a foundation that becomes increasingly valuable.
Google's Gemini models actively use the Knowledge Graph to verify facts and select sources. ChatGPT and Perplexity are developing similar entity understanding. This means investment in entity profiles, structured data, and topical authority has cumulative effect — it becomes more valuable over time, not less.
At LeapJet, we see entity SEO as the bridge between traditional SEO and GEO. Businesses with a strong entity profile rank better in traditional search, get cited more often in AI answers, and have more robust visibility that withstands algorithm updates. It is the most future-proof SEO investment you can make in 2026.
Sources and further reading
This article draws on the following sources and industry reports:
- Google Patents — US8898152B1: Providing search results based on sorted properties (Entity Definition)
- Google Blog — Knowledge Graph: Things, Not Strings (2023 Update)
- SEMrush — Entity-Based SEO Study (2024)
- Google Cloud — Natural Language API Documentation (2025)
- InLinks — Entity SEO Research Reports (2024)
- WordLift — Knowledge Graph SEO White Paper (2024)
- For terms like entity, Knowledge Graph, schema markup, and topical authority, see our glossary of SEO and GEO terms
- LeapJet GEO services — professional generative engine optimization
- LeapJet SEO services — complete search engine optimization
