Entity SEO

Modern search systems do not just match words; they resolve them to entities. When Google or an LLM processes the word Apple, it must decide whether you mean the company or the fruit, based on context and known relationships. Entity SEO works with this machinery: it makes your brand, products, and people unambiguous, well-described, and consistently connected across the web.

Core tactics include defining entities with schema markup (Organization, Person, Product), maintaining consistent names and descriptions everywhere your brand appears, securing presence in authoritative knowledge bases, and building topical associations through content and third-party mentions.

LLMs represent knowledge as relationships between entities learned from training data. When ChatGPT recommends software for a use case, it is traversing entity associations: this brand is connected to this category, these features, this audience. If your brand entity is weakly defined or inconsistently described, models either omit you or, worse, describe you inaccurately — a form of AI hallucination driven by sparse data.

Strong entity signals also help retrieval: engines grounding answers in live search resolve queries to entities before fetching documents, so a well-established entity surfaces in more retrieval paths and gets cited more reliably.

Start by stating clearly who you are: a definitive about page, Organization schema with sameAs links to your social and knowledge base profiles, and consistent boilerplate descriptions used in press, directories, and partner pages. Then build associations — publish authoritative content on your core topics and earn mentions linking your brand to your category, since the knowledge graph and LLM training pipelines both learn from repetition across independent sources. Geonimo's AI visibility monitoring shows how models actually describe your brand entity today, revealing gaps between the identity you publish and the one AI engines have learned.