In brief
Entity SEO is making sure search engines and AI models recognise your business, people and products as distinct, well described things. It means one consistent name, a stable @id in your structured data, sameAs links to trusted profiles, authors marked up as people, and matching details across the web. Clear entities are easier to recommend and harder to confuse.
Key points
- An entity is a distinct thing, such as a business, person or product, that machines can identify and describe.
- AI engines need to know which business you are before they can recommend you, especially if your name is shared.
- A stable @id and connected schema nodes turn your site into one clear description of the business.
- sameAs links should point to profiles and records that confirm your identity, not to pages that merely mention you.
- Consistent names and details across your site, Business Profile and directories do as much as markup.
- Wikidata can help established organisations and people, but only where they meet its notability rules.
The steps at a glance
- 1
Fix your name
Choose one trading name and one legal name and use them exactly the same way on your site, profiles and listings.
- 2
Set a stable @id
Give your Organization a fixed @id, such as your home page plus #organization, and never change it.
- 3
Connect the graph
Make every page's markup point to the same Organization and Person @id values rather than restating them.
- 4
Add sameAs and identifiers
Link to profiles you control and records that confirm who you are, and add identifiers such as a company number.
- 5
Mark up your people
Give each author a bio page and a Person entity linked to the Organization and to their own profiles.
- 6
Align the rest of the web
Update your Business Profile, directories and social profiles so names and details match, and consider Wikidata only if notable.
What is entity SEO?
Entity SEO is making sure machines recognise your business as one distinct, well described thing. An entity is anything that can be clearly identified, such as a company, a person, a product or a place.
Search engines and AI models store what they know about entities and how they connect. Google calls its version the Knowledge Graph. AI models hold a similar, looser picture learnt in training. When someone asks for a recommendation, the engine has to match the words in the question to entities it knows.
Entity SEO is about making that match easy and certain. It covers your name, your structured data, your links to other profiles, your people, and the details other sites hold about you.
Why do entities matter for AI search?
Because an engine cannot recommend a business it cannot identify. If it is unsure which firm you are, it will either leave you out or mix you up with someone else.
This is a bigger problem than many people think. Plenty of businesses share names, or have names close to others. A firm called Example Kitchens in Leeds may share its name with a firm in Kent. If both have thin, inconsistent details, an engine can blend them. That is how you end up with the wrong address, the wrong founder or a competitor's reviews in an answer about you.
Clear entities also help the model describe you. An engine that knows who you are, what you do, where you work and who leads you can give a precise answer. The guide on when AI gets your business wrong shows what happens when it cannot.
How does Google build its Knowledge Graph?
From many sources, automatically. Google's help page on how the Knowledge Graph works says facts come from a variety of sources that compile factual information. It also says knowledge panels are created automatically when there is enough information on the open web.
There is no form to apply. What you can do is make sure the information about you is clear, consistent and easy to confirm. Your own site is one source. Your profiles, directory listings, press coverage and public records are others. When they agree, the picture is strong.
How do stable @id values help?
An @id gives each entity a fixed identifier that every page can point to. The JSON-LD specification describes @id as the way to uniquely identify the things a document describes.
Without it, each page describes the business from scratch. One page might say "Example Windows", another "Example Windows Ltd" and a third "Example Windows and Doors". A machine sees three descriptions that may or may not be the same firm. With a shared @id, every page adds to one description.
The usual pattern is your home page address plus a hash, such as #organization for the business and #website for the site. Authors get their bio page address plus #person. Once set, never change them.
Here is a small connected graph for a made-up firm. Notice how the article points to the person and the organisation rather than repeating them.
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "Organization",
"@id": "https://www.example.co.uk/#organization",
"name": "Example Windows",
"legalName": "Example Windows Ltd",
"url": "https://www.example.co.uk/",
"identifier": "SC000000",
"sameAs": [
"https://find-and-update.company-information.service.gov.uk/company/SC000000",
"https://www.linkedin.com/company/example-windows"
]
},
{
"@type": "WebSite",
"@id": "https://www.example.co.uk/#website",
"url": "https://www.example.co.uk/",
"publisher": { "@id": "https://www.example.co.uk/#organization" }
},
{
"@type": "Person",
"@id": "https://www.example.co.uk/team/jane-smith/#person",
"name": "Jane Smith",
"jobTitle": "Technical Director",
"worksFor": { "@id": "https://www.example.co.uk/#organization" },
"sameAs": ["https://www.linkedin.com/in/jane-smith-example"]
},
{
"@type": "Article",
"headline": "How to stop condensation on new windows",
"author": { "@id": "https://www.example.co.uk/team/jane-smith/#person" },
"publisher": { "@id": "https://www.example.co.uk/#organization" }
}
]
}
What should sameAs point to?
To pages that confirm who you are. Schema.org defines sameAs as a reference page that unambiguously indicates the item's identity, giving a Wikipedia page, a Wikidata entry or an official website as examples.
Good sameAs links usually include these.
- Your official social profiles, such as LinkedIn, Facebook, Instagram and YouTube.
- Your entry on a public company register.
- Your Wikidata item or Wikipedia article, if you genuinely have one.
- Profiles on major industry bodies or registers you belong to.
Leave out news stories, review pages and directory pages that only mention you. They do not identify you, and a long list of weak links adds noise. Check every sameAs link works and belongs to you, and review the list when profiles change.
Why do consistent names matter so much?
Because names are the first thing an engine uses to match a mention to an entity. Small differences add doubt.
Pick one trading name and one legal name. Use the trading name the same way everywhere, including the website, Business Profile, social profiles, directories and press releases. Put the legal name in legalName in your markup and in your site footer.
If you have old names, list them as alternateName in your markup rather than leaving them scattered across the web. After a rebrand, update every profile you control and ask the main directories to update theirs. Old names left behind are a common source of confused AI answers.
Should your business be on Wikidata?
Only where it is appropriate. Wikidata is a free, community-run knowledge base. It is widely used, and schema.org names it as a good sameAs target.
Wikidata has notability rules. Broadly, an item should link to a Wikimedia page, or be a clearly identifiable entity described in serious, publicly available references, or be needed to support other items. Many small businesses do not meet that. Items made purely to promote a business can be deleted.
If your organisation or founder is well covered by independent sources, a Wikidata item can be a sound part of your entity work. Add only facts you can reference, and cite the sources. If you are not sure you qualify, leave it and focus on the steps you control.
How do author entities fit in?
Authors are entities too. Content written or checked by named, identifiable people carries more weight than anonymous pages.
Give each author a bio page with their role, experience and qualifications. Mark them up as a Person with an @id, a worksFor link to your organisation and sameAs links to their profiles. Point every article they write to that @id. Google's Article markup guide asks for the Person type and a url that uniquely identifies the author.
This ties into trust, which Google calls the most important part of E-E-A-T. The E-E-A-T for AI search guide covers the wider picture.
Do branches and products need entity work too?
Yes, where they matter to buyers. A business with several branches should describe each one as its own LocalBusiness, linked back to the parent brand. That lets an engine see one firm with eight showrooms, rather than eight firms with similar names.
Products and named services work the same way. If buyers ask for a product by name, give it a clear page, a consistent name and markup that links it to your organisation. A B2B software company with three named products should make it obvious which company makes each one. Otherwise an engine may credit a product to a reseller or a competitor.
How do you check your entity setup?
Look at your site the way a machine does. Pull the structured data from your key pages and ask a few questions.
- Is there exactly one Organization, with the same @id everywhere?
- Do all pages point to it rather than describing it again?
- Are the name, address and phone the same as your Business Profile?
- Do the sameAs links work and belong to you?
- Are authors Person entities linked to the organisation?
- Is there at least one verifiable identifier, such as a company number?
Then check outside your site. Search your business name and look at what comes up. Where details differ from your site, fix them at the source. The schema markup guide has more on the markup itself.
How Axiom GEO helps
The entity audit crawls your key pages and rebuilds the entity graph your site publishes. It checks for stable @ids, connected schema nodes, name variants, verifiable identifiers and authors as Person entities. It returns scored findings, each with what was found, why it matters and the fix. You can run it free at the public entity audit. The schema generator then builds copy and paste JSON-LD for any types a page is missing.
Sources
These are the external pages this guide relies on.