An entity is a thing a search or answer engine can be sure about: your business as a name, a location, a category, a set of attributes and relationships to other entities. Entity foundations are the work of making those facts identical wherever a machine reads them, and this chapter covers the four to get right and why they degrade.
What is an entity, and why does an engine need to be sure which one you are?
To a search or answer engine, your business is an entity: a thing with a name, a location, a category, a set of attributes, and relationships to other entities. The engine's job is to be sure it knows which entity you are.
Everything else depends on that certainty. Content from a business the engine cannot confidently identify is content it will hesitate to cite, because citing the wrong business is a worse outcome for the engine than citing nobody.
Which four things do you have to get right?
Four things carry the entity layer: one exact name, address and phone everywhere, a hardened Google Business Profile, schema that agrees with the visible page, and conflicting records hunted down. Each one is a statement about your business that a machine can check against another copy of it.
| Foundation | What it takes |
|---|---|
| One exact name, address and phone, everywhere. | Written identically across your site, Google Business Profile, every directory, every social profile. Not approximately the same, identically. “Suite 200” and “Ste 200” are two different facts to a machine reading at scale. |
| A hardened Google Business Profile. | Correct primary category, honest secondary categories, service areas matching where you actually work, real hours, and the fields most businesses leave empty filled in. |
| Schema that agrees with the visible page. | Organization and LocalBusiness markup stating the same facts the profile states, with sameAs pointing only at properties you control. Markup that contradicts the page is worse than none — it is a machine-readable assertion that you are inconsistent. |
| Conflicting records hunted down. | Old addresses, a previous phone number, a pre-rebrand trading name, duplicate profiles created by an aggregator. Found and corrected one at a time. There is no tool that finishes this. |
Why does entity accuracy degrade after you have fixed it?
Entity accuracy is not a one-time cleanup. An aggregator republishes a stale record, a staff member updates a profile with a slightly different name, a new directory scrapes old data. It decays quietly and it decays continuously.
Treat it as something checked on a cadence rather than fixed once and assumed. Most of the work lands in the first sixty days; stragglers surface for months.
Chapter last reviewed 2026-07-26. Platform behaviour changes, so read every chapter of this guide against the date it carries.
Rankings are never guaranteed. Anything we could not trace to a primary source is absent from this page, not estimated. The audit runs the same six layers described on the pricing page, and Share of Answer is scored quarterly.
Read in order, or jump
Twelve chapters, sequenced the way the work actually runs. The opening four carry the structure; the platform chapters close with two surfaces we choose not to score, and the reasoning for that.
01 How AI search picks local businesses 02 Eligibility: can AI even see your site? 03 Robots.txt: block AI crawlers or allow them? 04 Measuring AI visibility honestly 05 Entity foundations for local businesses 06 Reviews as AI input 07 Citation surfaces: where AI engines look 08 Getting ChatGPT to recommend your business 09 Showing up in Perplexity 10 Showing up in Google AI Overviews 11 Showing up in Gemini 12 Copilot, and why we don't sample itSee where you actually stand
Everything measured in this guide, run against your business, free.
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