E‑E-A‑T
E-E-A-T stands for Experience, Expertise, Authoritativeness and Trust. It is the framework from Google's Search Quality Rater Guidelines for judging whether a source deserves trust. It is not a direct ranking factor but a filter content passes through before a search engine or an AI model uses it as the source of an answer.
In short
| Experience | The author has actually done or used the thing. The newest component (added late 2022) and the hardest to fake |
| Expertise | The author demonstrably understands the topic |
| Authoritativeness | The field recognizes the author or the site as a reference |
| Trust | The facts hold, sources are traceable, the site is transparent. The most important component, the others support it |
How E-E-A-T shows up and how it is judged
Where each component comes from
None of the four components is a declaration. Each is inferred from what is visible on the page and from what independent sources say about the author and the site. Both sides have to hold: an author box without a traceable history proves nothing, and a reputation off the site does not help a page that has no author and no sources.
| Experience | On the page: original photos, screenshots from accounts and tools, a process described with data, numbers from your own measurement. Off the site: case studies naming clients, the author's public work |
| Expertise | On the page: an author with stated qualifications and an author page, precise terminology, depth of explanation. Off the site: publications, talks, profiles, the author cited elsewhere |
| Authoritativeness | On the page: content that others in the field refer to. Off the site: links and mentions from industry sites, media and directories, recommendations by other experts |
| Trust | On the page: operator, contact, terms, secure payment, sources behind claims, reviews from verified purchases. Off the site: independent reviews, the registry, matching company facts everywhere |
How raters read it and how algorithms do
Quality raters are people who assess samples of results according to the guidelines. They find out who stands behind the page, what reputation the site and author have in independent sources, and whether the content fulfills the page's purpose. Their ratings do not move a specific page up or down; they let Google measure whether algorithm changes reward what the guidelines describe. The algorithms work with signals that can be measured at scale: links and mentions from topically related sites, consistency of the author and company entities across sources, originality of the content against what the index already holds, user behavior. For topics that affect health, money or safety, the threshold is stricter. E-E-A-T therefore has no single score. It is the combined outcome of several systems that Google designs to prefer content with these properties.
Why Trust decides
Trust is judged against the purpose of the page. An e-shop needs a traceable operator, contact details, terms, secure payment and correct product information; a guide on a health topic needs a qualified author and sources. A page that cannot be trusted is low quality no matter how much experience, expertise and authority it displays. In practice this means: every article has an author with an author page and Person schema including sameAs, every claim has a source, numbers come from your own data and match across the site, products carry reviews from verified purchases, and company details are identical in the registry, in profiles and in structured data.
Why E-E-A-T matters in AI answers too
Language models face the same problem as Google's raters: which source to trust when sources disagree. The signals are similar: an author with a traceable history, original data instead of borrowed claims, consistent company facts and independent third-party confirmation. Content written from real practice, with numbers nobody else has, is exactly what the Experience component describes, and at the same time a strong citation factor.
From our own practice: independent reviews as a trust signal
Part of our own trust work was building a Clutch profile: today it holds 9 verified client reviews with a 5.0 rating. A verified review on an independent platform is precisely the kind of signal a machine can check by itself: not a company's claim about itself, but confirmation by a third party. Industry directories, case studies naming real clients and author pages with real people belong in the same category.
Common mistakes
- Anonymous content. Articles without an author and a company without people are less credible to machines and readers alike.
- Borrowed claims without first-hand experience. Paraphrasing other people's texts does not fill the Experience component.
- Inconsistent facts. Contradictory numbers undermine Trust faster than anything else builds it.
- Buying signals. Purchased reviews and links are detectable and the risk outweighs the gain.
Related terms
See also entity SEO, Knowledge Graph, GEO and citation share.
Frequently asked questions
Is E-E-A-T a ranking factor?
Not directly; it has no score. It is the framework Google uses to describe what its systems should reward, and it shows most strongly in sensitive topics.
How do I prove Experience?
With original data, artefacts of real work, specific processes and numbers from your own accounts. Generic text can be told apart from first-hand experience at a glance.
Does it apply to small sites?
Yes. Authority is measured within a topic, not by site size. A narrow site with deep practice can beat a large portal.
How we can help
We build brand credibility for search engines and AI as part of our AI visibility agency service.