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

E-E-A-T is Google's framework — Experience, Expertise, Authoritativeness, Trustworthiness — for evaluating content quality. It originated in the Search Quality Rater Guidelines as E-A-T in 2014, expanded to E-E-A-T in 2022, and now drives a substantial share of AI Overviews and Gemini citation decisions.

The four signals: Experience asks "does the author have first-hand experience with the topic?" Expertise asks "are they qualified to write about it?" Authoritativeness asks "do other reputable sources cite or link to them?" Trustworthiness asks "is the page accurate, secure, and from a verifiable source?"

For practical AEO work, E-E-A-T manifests through specific structural signals: identified authors with bios + sameAs links to social profiles, an /about page with company background, an /contact page with verifiable details, Organization schema with sameAs to social profiles, dates of authorship and last update, citations to authoritative third-party sources, and HTTPS + valid SSL.

AI engines (especially Gemini, but increasingly ChatGPT and Claude) penalise sites that fail E-E-A-T basics. A site without an /about page, without identified authors, without Organization schema, is harder to cite confidently — the model has no signal that the content is trustworthy. AEOlens scores E-E-A-T as one of its 48 structural checks.