Entity SEO: What Businesses Need to Get Right
Search engines and AI-powered systems process online information differently from a human visitor. One part of that process is identifying the people, organisations, places, and other entities that information refers to, and understanding how they relate. Entity SEO is the term commonly used for the work involved in making that identification as clear as possible.
What is an entity?
In search terminology, an "entity" is a distinct, identifiable thing: a business, a person, a place, a product, or another defined concept. Google's Knowledge Graph is built around entities like these and the relationships between them, rather than simply pages and keywords.
A business can be treated as an entity, as can people, places, products, and other distinctly identifiable things associated with it. Those entities can also have relationships: a founder associated with an organisation, for example, or a business operating at a particular location. Entity SEO is the term commonly used for work that helps search engines more clearly identify a business, person, place, product, or other defined concept, and understand those relationships. Echeva applies the same underlying principle when considering AI-search visibility, though it's worth being clear that no AI platform publishes a formal "entity SEO" mechanism of its own.
Entities and keywords
Keywords remain an important part of search, because they express what users are actually looking for. Entity-based understanding adds another layer: identifying the real-world people, organisations, places, and concepts those words refer to, and understanding the relationships between them. Entity SEO complements keyword-focused SEO rather than replacing it; the two work alongside each other.
A page can contain all the expected keywords and still describe a poorly defined entity. A page can also be written in plain, everyday language and still represent a very clearly defined entity, if the underlying facts about that business are consistent and well-supported elsewhere.
Where entity information comes from
Google doesn't build entity understanding from a single source. Google states that Knowledge Graph information can come from public information across the web, open and licensed databases, and information supplied by verified entities. For an individual business, its own website, its Google Business Profile, and credible third-party references can therefore all form part of a wider online identity, though Google doesn't publish a universal weighting for how much any one source contributes.
This is part of why entity SEO can't be solved by editing a single "About Us" page. It's a property of how a business is represented across many different places, not just one.
Identity clarity is not identity uniformity
A common misconception is that entity clarity means every reference to a business has to use identical wording. It doesn't. A company may legitimately have a trading name, a registered legal name, and a recognised abbreviation, all at once. Google's own Organisation structured data explicitly supports separate name, alternateName, and legalName properties for exactly this reason.
The issue isn't variation itself. It's unexplained or contradictory variation. A clear relationship between "Smith & Co" and its registered name "Smith and Company Limited" is very different from an outdated address, an unrelated name, or a conflicting description that leaves it unclear whether two sources are even referring to the same organisation. Entity SEO isn't about mechanically making every mention identical. It's about making legitimate differences understandable.
A note on sameAs
One specific technique worth understanding is the sameAs property in structured data, which allows a business to reference another webpage that unambiguously identifies the same entity. Google supports sameAs within Organisation structured data, and Schema.org gives examples including official websites, Wikipedia pages, and Wikidata entries. This can provide search systems with an explicit, machine-readable relationship between different references to the same entity. See our guide on schema for search and AI for more on structured data generally.
It shouldn't be treated as an AI-ranking technique, and there's no evidence that adding a particular sameAs link guarantees inclusion in an AI-generated answer. It's also worth noting that a Wikidata entry should only be referenced where an appropriate, legitimate entry already exists; it isn't something to create purely for SEO purposes.
The Knowledge Graph, briefly
We cover Google's Knowledge Graph in more detail in our AI Search Knowledge Base, but it's worth mentioning here specifically. It's Google's database of facts about entities and their relationships, built from information gathered across the web and other data sources. Businesses can't simply submit an application to be added to it. Where a Knowledge Panel already exists for a business, eligible representatives may be able to claim it and suggest corrections, while local businesses generally manage their Google presence through their Business Profile instead.
An example
A firm of solicitors operates publicly as "Harris & Cole," while the underlying legal entity is Harris & Cole Legal Services Limited. That difference is perfectly legitimate on its own, as long as the relationship is clearly stated somewhere. Ambiguity arises if older directories still use a former trading name, one office listing shows a previous address, third-party profiles attribute partners to the wrong organisation, and nothing on the website ever clearly establishes how these different identities relate to one another.
Common mistakes
Treating the "About Us" page as the whole solution. Entity clarity depends on consistency across many sources, not just one page.
Unexplained identity differences. Different legal, trading, or abbreviated names aren't automatically a problem. The problem is when sources contain outdated, contradictory, or unexplained identities that make it unclear whether they refer to the same organisation.
Structured data that doesn't match visible content. Google requires structured data to accurately represent the content it describes. Incorrect or misleading markup can make a page ineligible for certain search features and, in serious cases, breach Google's structured data guidelines.
Ignoring third-party profiles. A business's own website is only one part of its wider online identity. Relevant directories, review sites, social profiles, and other credible third-party references can provide additional information about the organisation, although the importance of individual sources varies.
Assuming entity clarity is a one-off task. Business details change (new locations, new services, rebrands), and entity information needs to be kept consistent as they do.
What businesses should aim for
A clearly defined business should have an identifiable primary name, clearly explained legal or trading identities where relevant, accurate location and contact information where applicable, structured data that accurately reflects visible content, and official online profiles that can be confidently associated with the same organisation.
These principles describe the outcome businesses should be working toward, not a complete audit methodology. Determining exactly where ambiguity exists for a specific business, which sources matter most, and what should be corrected first requires a broader assessment of that business's actual search and AI-search footprint.