ONPAGE · SEO GLOSSARY
Entity-Based SEO
An SEO approach that optimises for Google\'s Knowledge Graph — helping Google identify the people, organisations, places, and concepts your content is about, rather than just the keywords it contains.
Definition
Entity-based SEO treats the subject matter of content as **entities** (distinct, uniquely identifiable things) rather than as keyword strings. Google\'s Knowledge Graph maps entities and their relationships: "Python" is an entity that is a programming language, created by Guido van Rossum, with versions, related entities (Django, Flask, NumPy), and a canonical identifier (its Wikipedia/Wikidata entry). When Google understands that a page is authoritatively about the Python programming language (not the snake), it can rank the page for the full semantic cluster of Python-related queries, not just pages that include the exact string "Python". **Key entity SEO tactics**: Schema.org structured data — explicitly identifying entities with JSON-LD (`Organization`, `Person`, `Product`, `Place`) so Google can map them to Knowledge Graph nodes; `sameAs` properties linking to authoritative external references (Wikipedia, Wikidata, authoritative directories); Entity mentions — naturally using the full names of entities (tools, people, concepts) and their aliases; Internal linking — linking between pages that cover related entities creates a site-level entity graph; E-E-A-T signals — demonstrating genuine authorship and organisational identity through author pages, About pages, and external mentions, helping Google associate the site with its entity in the Knowledge Graph. Entity-based SEO is more durable than exact-keyword SEO because it aligns with how Google actually models meaning rather than surface-level string matching.
Why it matters for SEO
Google\'s language models and Knowledge Graph now assess content meaning, not just keyword presence. A page that accurately identifies its subject entities and demonstrates genuine expertise in those entities is more likely to rank for the full range of related queries — including natural language questions, voice search, and AI Overview citations — than a page optimised for exact keyword density.
How DeepSEOAnalysis checks this
The audit checks entity identification signals: `Organization`, `Person`, `Product` JSON-LD with `sameAs` properties pointing to authoritative external references; author attribution on blog/article pages (both visible byline and schema); and whether FAQ and How-To schema are used to surface entity-related questions. Structured data that identifies key entities but lacks `sameAs` linking to canonical external references is flagged as an entity clarity gap.
Useful tools and resources
GLOSSARY
Related terms
structured data
Structured Data
Machine-readable annotations added to HTML — usually JSON-LD — that explicitly describe what a page is about to search engines and AI systems.
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Knowledge Panel
A boxed sidebar in Google Search displaying structured information about a person, organisation, place, or thing — drawn from Google\'s Knowledge Graph and structured data on authoritative sources.
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E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness)
Google\'s quality framework for evaluating content — especially important for YMYL (Your Money, Your Life) topics like health, finance, and legal.
Read definition →structured data
Schema Markup
A shared vocabulary of types and properties from Schema.org used to annotate web content in machine-readable format — enabling search engines to understand what content means, not just what it says, and to generate rich results.
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Topical Relevance
The degree to which a page\'s content, internal link context, and surrounding site content signal subject-matter authority and deep coverage of a specific topic — a key factor in how Google evaluates whether a page is the best result for a query.
Read definition →See how your site scores on Entity-Based SEO.
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