How-to guide · ai-search
How to make your business a clear entity that AI engines can identify
AI engines do not rank pages about you; they build a model of who you are from everything they can find. If your name, description and facts differ from place to place, that model is fuzzy and you get skipped or misdescribed. This is how to fix it in a fortnight.
Ask ChatGPT what your company does. If it hesitates, gets it wrong, or confuses you with a business of a similar name in another county, you have an entity problem. AI engines assemble their understanding of a business from every source they can read: your site, LinkedIn, Google Business Profile, Companies House, directories, press, reviews. When those sources agree, the engine is confident and will name you. When they disagree, it is not, and confidence is what decides who gets recommended.
Most of this is unglamorous consistency work. It takes about two weeks of part-time effort and it underpins everything else on this site.
Step 1: Write one canonical description and use it everywhere
Twenty-five words. Who you are, what you do, for whom, where. "Emerging Digital Partners is a digital marketing agency in Eastbourne, East Sussex, building websites and AI search visibility for small and mid-sized UK businesses." Agree the exact wording internally and treat it like a logo: it does not get rewritten per platform.
Step 2: Build an About page that answers the entity questions
Most About pages are a mission statement. Yours needs to state, in plain text near the top: legal name and trading name, what you do, who founded it and when, who runs it now (names, roles, short bios, photos), where you are based (full address), the areas or sectors you serve, company registration number, and memberships or accreditations. Then the story, if you want one. This page is the primary source the engine will use to resolve you.
Step 3: Add Organization schema with sameAs
On the homepage, one Organization (or LocalBusiness subtype) block with a stable @id, the canonical description, address, phone, founding date, founders, and sameAs links to every official profile: LinkedIn company page, Google Business Profile, Companies House record, Crunchbase, X, Facebook, Instagram, YouTube. sameAs is the explicit statement "these are all me". Our structured data guide has the full example.
Step 4: Align the facts on every platform you control
Open each profile and make them match the canonical version exactly: name (including "Ltd" or not, consistently), address format, phone number, description, founding year, category. Priority order: Google Business Profile, LinkedIn company page, Bing Places, Apple Business Connect, Facebook, Companies House (name and registered office), Trustpilot or your main review site, trade directories. Log each one in a spreadsheet with the date checked.
Step 5: Give your people entity pages too
Founders and senior staff should have author or team pages on your site with a photo, role, credentials and a Person schema block whose sameAs points to their LinkedIn profile and whose worksFor points to the Organization @id. Their LinkedIn headlines should name the company identically. Engines connect people to companies, and a founder with a clear public footprint lends the company credibility.
Step 6: Consider Wikidata, honestly
Wikidata's notability bar is lower than Wikipedia's: an item can be justified by serious and publicly available references. If you have coverage in independent publications, a Companies House record and industry listings, an item with your official website, founding date, headquarters and LinkedIn ID is achievable and gives engines a structured anchor. If you have none of that yet, skip it and come back later. Do not pay someone to create a Wikipedia page; it will be deleted.
Step 7: Get third parties to describe you the same way
When you are quoted in the press, sponsor an event, join a trade body or appear on a partner's site, supply the canonical description and ask them to use it. Every independent page that describes you consistently strengthens the entity. Every one that calls you "a Sussex marketing company" or spells the name differently weakens it a little.
Step 8: Test, fix, repeat quarterly
Ask the four main engines "What is [company] and what does it do?", "Who founded [company]?", "Where is [company] based?" and "What does [company] charge for [service]?" Record the answers. Anything wrong traces back to a source that disagrees with you; find it and correct it. Repeat every quarter. The answers improve as the sources align.
How to know it worked
Every engine describes you accurately and consistently, names your founders and location correctly, and does not confuse you with anyone else. Your third-party mentions start to appear in answers about you, which means the engine has connected them.
Common mistakes
- A different description on every platform because "each audience is different".
- An About page with no names, no address and no founding date.
- Organization schema with no
sameAs. - Founders with LinkedIn headlines that do not mention the company, or that mention an old one.
Frequently asked questions
What does 'entity' mean in AI search?
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An entity is a thing the engine can identify and hold facts about: a company, a person, a product, a place. AI engines connect mentions of your business across the web into one entity when the facts line up. When they do not, the engine either fails to connect them (so your third-party mentions do not count towards you) or describes you wrongly.
Do I need a Wikipedia page?
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No, and most small and mid-sized businesses will never meet Wikipedia's notability rules. A Wikidata item is sometimes achievable and useful, but the bigger wins are a clear About page, Organization schema with sameAs links, and consistent facts on LinkedIn, Google Business Profile and directories.
How do I check what AI thinks my business is?
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Ask ChatGPT, Perplexity, Gemini and Claude: 'What is [company name] and what does it do?' and 'Who runs [company name] and where is it based?' Compare the answers to the truth. Wrong or vague answers show you exactly what to fix.
Sources
- Google Search Central: Organization structured data · developers.google.com
- Maria Dykstra: Why identity fragmentation blocks AI citations · mariadykstra.com
- Wikidata: Notability policy · wikidata.org
George McKenna
Co-founder, Emerging Digital Partners
George co-founded Emerging Digital Partners in Eastbourne and built the AI Search & SEO Audit you are on now. He spent around twenty years in the UK IT channel before that, most recently running solution sales teams, and now splits his time between building websites and search tooling for EDP clients and taking AI products to regulated industries through the ETT Group, where he is Chairman and CTO. He writes about answer engine optimisation the way he practises it: test it, measure it, fix what is actually broken.
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