Term

E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness)

In short

Google's quality evaluation framework – Experience, Expertise, Authoritativeness, Trustworthiness. Not a ranking factor but four answers to the question "why should we believe this source"; AI models ask the same question.

E-E-A-T is an acronym from the guidelines Google wrote for its search quality raters. It is not a directly measured score; it is four headings used to assess how trustworthy a piece of content and its source are. Generative engines apply a similar filter when building an answer: they prefer sites that are confirmed by many sources, whose identity is clear, and whose information is consistent.

The four headings

Experience: has the author actually done this? Photos of finished work, case descriptions, sentences like "here's how we did it".
Expertise: was it written by someone who knows the subject? Author name, title, certification; the depth of the content.
Authoritativeness: do others refer to this source? Directory listings, press coverage, links from business partners, reviews.
Trustworthiness: is the information accurate and verifiable? A clear address and phone number, real people's names, consistent details, HTTPS, current content.

What it means for AI

When a model chooses between two businesses, it prefers the one with real names and an address on its "about us" page, the one mentioned in local news, the one with forty reviews. Every item in E-E-A-T is a signal that makes it easier for the model to conclude "this business is real and trustworthy".

How to show it on a site

Team and history on the about page; a concrete example on every service page; the full address and phone number on the contact page; an author name on blog posts; and, off-site, consistent directory listings and reviews.