Glossary
Entity optimisation is the work of making a machine able to identify your organisation, people and products unambiguously, as distinct things in the world rather than as strings of text that happen to appear on a page.
They resolve it to an entity: a specific organisation with a name, a location, a set of relationships and a body of things said about it. If that resolution fails, or resolves to the wrong company, everything downstream weakens, including whether a model is willing to cite you.
A company name shared with a larger brand, an address written three different ways across the site, a founder credited under two spellings, structured data on one template but not the others. Each is small; together they make the entity harder to pin down than a competitor whose details agree everywhere.
One canonical organisation record with a stable identifier, the same name, address and contact details everywhere they appear, structured data that references that record rather than repeating it, and external profiles that agree with the site rather than contradicting it.
It does not produce a ranking on its own, and no reputable practitioner can promise it will. What it does is remove a class of reason for a system to be uncertain about who you are, which is a precondition for being retrieved and attributed.
No. Schema markup is one way of stating an entity in machine-readable form. Entity optimisation is the broader work of making the identity consistent everywhere it appears (on the site, in structured data and on external profiles), so those statements agree.
It still helps. Entity clarity supports knowledge panels and brand results in conventional search as well as citation in AI answers. The two goals share most of the same underlying work.
Entity optimisation is the work of making a machine able to identify your organisation, people and products unambiguously, as distinct things in the world rather than as strings of text that happen to appear on a page.
Connected
