Glossary
E-E-A-T stands for experience, expertise, authoritativeness and trust. It is not a score a search engine calculates; it is the framework human quality raters use, which describes the kind of quality the ranking systems are built to approximate.
Search engines publish rater guidelines describing what good looks like, then build systems intended to identify it automatically. E-E-A-T describes the target, not the mechanism.
It asks whether the content shows evidence of having actually done the thing (specific detail, real constraints, failure modes) rather than having summarised other sources. That is also, not coincidentally, what makes content worth citing in an AI answer.
It penalises anonymous, generic content that could have been written by anyone about anything.
Not a single measurable one. It describes the quality that ranking systems are designed to approximate. Any tool reporting an E-E-A-T score is reporting its own estimate, not a search engine's judgement.
Attribute content to identifiable people with relevant experience, be specific enough that claims can be checked, keep material current, and keep the organisation's identity consistent everywhere it appears.
E-E-A-T stands for experience, expertise, authoritativeness and trust. It is not a score a search engine calculates; it is the framework human quality raters use, which describes the kind of quality the ranking systems are built to approximate.
