Glossary

What is E-E-A-T?

Experience, Expertise, Authoritativeness, Trustworthiness — Google's quality framework, now echoed in how AI systems select sources to cite.

Definition

E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) is the framework from Google's Search Quality Rater Guidelines describing what makes content credible. It is not a direct ranking factor but a description of what Google's systems are built to reward — and its logic extends naturally to AI answer engines choosing which sources to trust.

The added first E, Experience, rewards first-hand knowledge: original testing, real usage, primary data — precisely the material AI summaries cannot generate themselves.

Why it matters

Generative engines have an authority bias measurable in the data: citations concentrate in sources with demonstrable expertise, and the Princeton GEO study found authoritative language and cited evidence increase inclusion odds. Content with original data or hands-on experience gives assistants something they must attribute — commodity summaries give them nothing to cite that they can't say themselves.

Frequently asked

How do I demonstrate E-E-A-T to an AI system?

Author bylines with credentials (marked up with Person schema), original data and methodology notes, citations to primary sources, and consistent third-party corroboration of your claims.

Is E-E-A-T more important for some topics?

Yes — YMYL (Your Money or Your Life) topics like finance and health face the strictest source selection in both classic search and AI answers.

Related terms