Entity SEO

Definition

Entity SEO treats content as a collection of named things (people, places, products, brands, frameworks, events) rather than as a bag of keywords. Search engines and large language models use entity recognition to build a map of who is related to what, and content that clearly names and links entities is easier to understand, verify, and cite.

At the technical level, Entity SEO combines Schema.org markup (Person, Organization, Product, Place, Event), Wikidata and Wikipedia alignment, consistent entity naming across a site, and explicit entity relationships using sameAs links. At the content level, it means writing with specific proper nouns instead of generic references.

Why It Matters

Google moved from a keyword index to an entity-aware index with the Knowledge Graph (2012) and Hummingbird (2013). Every major AI search engine now relies on entity extraction to decide which sources to trust and cite. If your brand is not a recognized entity, you are invisible to the citation layer even if your pages rank.

The practical effect is stark. A blog post that says "we work with top analytics platforms" is entity-poor. A blog post that says "we integrate with Google Analytics 4, Plausible, and PostHog" names three entities that AI models can parse, verify, and attach authority signals to.

How Acta AI Handles This

Examples

A Person entity marked up with Schema.org gives AI models an unambiguous identity:

{
  "@context": "https://schema.org",
  "@type": "Person",
  "name": "Jane Doe",
  "jobTitle": "Head of SEO",
  "worksFor": {
    "@type": "Organization",
    "name": "Acta AI"
  },
  "sameAs": [
    "https://www.linkedin.com/in/janedoe",
    "https://en.wikipedia.org/wiki/Jane_Doe"
  ]
}

The `sameAs` array links this entity to external authoritative sources (LinkedIn, Wikipedia, Wikidata) so search engines and LLMs can reconcile the identity across the web.