Entity-Based SEO
In one line
Entity-based SEO organises content around entities — people, brands, products, concepts — rather than keywords, and works on the relationship signals between them.
Going deeper
Entity-based SEO shifts the unit of analysis from words to entities — people, brands, products, concepts. Systems like Google's Knowledge Graph, MUM and RankBrain already read pages as 'this is content about entity X', and they layer in how X relates to other entities. The signal isn't really the string 'Villion' — it's 'Villion is a Korean GEO analytics platform = an AI-search visibility tool', and the relationships around that.
In practice this splits into two workstreams. First, make the entities on a page legible: Schema.org and JSON-LD markup, Wikipedia and Wikidata linkage, consistent brand information across pages. Second, grow a coherent information graph around your brand across the open web — corporate pages, press, directories, reviews all feed the same signal pool.
For GEO this is foundational. LLMs lean on entities and their attributes and relationships before they pick which sources to cite, so the more accurately and richly your brand entity sits in the graph, the more often you become a citation candidate. What Villion talks about as 'teaching AI who your brand is' is, mechanically, entity-based SEO.
Related terms
Semantic Search
Semantic search matches results by understanding the meaning and intent behind a query rather than matching exact keywords — the default mode of modern search engines and LLMs.
SEOKnowledge Graph
A knowledge graph is a database of entities — people, brands, products — and their relationships, used by search engines and LLMs as the factual backbone of their answers.
SEOSchema.org
Schema.org is the shared vocabulary co-sponsored by Google, Microsoft, Yahoo and Yandex that lets you label what each page means so search engines and AI can understand it.
GEO·AEOGEO
GEO (Generative Engine Optimization) is the practice of optimizing content and data so that a brand gets cited and recommended inside generative AI search answers like ChatGPT, Perplexity and Google AI Overviews.
GEO·AEOLLMO
LLMO (Large Language Model Optimization) is the work of shaping content, data and context signals so that LLMs understand and cite your brand correctly.
How does your brand show up in AI answers?
Villion measures how your brand appears across ChatGPT, Perplexity and AI Overviews, then automates the work that lifts citation rate and share of voice.
Get a free audit