"This approach mirrors a fundamental shift in how search systems work. Google no longer simply matches text; it maps how concepts relate to one another and evaluates whether content meaningfully contributes to a subject's broader ecosystem. As large language models like ChatGPT and Gemini increasingly shape how information surfaces, the strength of entity signals determines which sources get cited, referenced, and ranked."
"Entities are distinct concepts, people, places, or things that search engines identify and connect within the Knowledge Graph. These relationships help systems interpret meaning instead of relying on exact-match phrases. Search engines use entities to understand how topics connect. When content makes those connections clear, visibility improves across multiple related queries - not just one primary term. An entity represents far more than a word or phrase on a page - it encompasses the full context surrounding a concept."
Entity-based SEO focuses on concepts, relationships, and context rather than isolated keyword phrases. Search engines identify entities — distinct concepts, people, places, or things — and link them within a Knowledge Graph to interpret meaning and assess topical authority. Mapping how entities relate allows systems to evaluate relevance across multiple related queries instead of relying on exact-match terms. Large language models influence how information surfaces, making strong entity signals more likely to cause sources to be cited, referenced, and ranked. Effective implementation requires finding relevant entities, structuring content around relationships, and measuring entity-signal impact.
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