What is E-E-A-T?
Experience, Expertise, Authoritativeness, Trustworthiness
Definition
E-E-A-T — Experience, Expertise, Authoritativeness, Trustworthiness — is the framework Google's quality guidelines use to judge whether content deserves to rank, especially for topics affecting money or health. It's not a single score but a bundle of signals: who wrote this, what have they actually done, and can it be verified?
Experience means first-hand involvement (real campaigns, real dashboards, real clients — not paraphrased theory). Expertise is demonstrated knowledge; authoritativeness is others vouching for you (mentions, links, reviews); trust ties it together with accuracy, transparency and consistent business details.
Practically, E-E-A-T is built with named authors and bios, author schema linked to real profiles, original data and screenshots, published case studies with verifiable numbers, visible credentials and partnerships, and steady third-party reviews. AI engines apply the same logic when choosing which sources to cite — anonymous, unverifiable content loses twice.
Example
Two agencies publish "how we cut CPL" guides. One is anonymous with stock advice; the other names its head of performance, embeds the actual dashboard, links the full case study and carries 100+ Google reviews. Both Google and ChatGPT preferentially surface the second.
Why it matters
Rankings and AI citations increasingly go to provable expertise. Everything that builds E-E-A-T — authors, data, reviews, transparency — also builds buyer trust, so the work pays twice.
Not a single measurable factor — it's the standard Google trains its systems and human raters toward, expressed through many signals (links, mentions, author identity, content quality). Treat it as a content and brand strategy, not a checkbox.
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