Experience, Expertise, Authoritativeness, and Trust — E-E-A-T isn't a direct ranking algorithm, but it shapes the quality raters and systems that decide whether your content is worth surfacing at all.
E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trust. It comes from Google's Search Quality Rater Guidelines — the document human quality raters use to evaluate search results and provide feedback that shapes Google's ranking systems. It isn't a single algorithm or a score you can check, but its underlying concepts show up across how content gets evaluated, including in automated quality assessments.
Added as a distinct pillar in 2022, Experience asks whether the content creator has real, first-hand experience with the topic — having actually used the product, visited the place, or performed the task being described. A review written by someone who owns the product reads differently than one assembled entirely from other reviews, and Google's guidelines explicitly call this distinction out.
Does the creator have the knowledge or skill required to write authoritatively on the topic? For YMYL (Your Money or Your Life) topics — medical, financial, legal — this bar is high. For a hobbyist topic, demonstrated practical expertise can matter more than formal credentials.
Is the content, the creator, or the website recognized as a go-to source on the topic — by other sites linking to it, by reputation, by citation? This is built over time and is difficult to fake; it's the accumulation of being useful and accurate consistently.
Google's guidelines describe trust as the most important member of the group — it underpins the other three. Is the site transparent about who runs it and how to contact them? Is information accurate and kept up to date? Are transactions and data handled securely? A site can have expertise and authority and still fail on trust if, for example, it lacks basic transparency like an about page or contact information.
Quality rater feedback doesn't directly move individual rankings, but it trains and validates the automated systems that do. The same underlying signals raters look for — clear authorship, transparency about the site's purpose, accurate and current information, a legitimate way to contact the people behind it — are exactly what automated content-quality systems (including ad network reviews) are approximating at scale. A site that would score well with a human quality rater tends to also score well with automated equivalents, because both are checking for the same underlying thing: is this a real, accountable source providing genuine value.
E-E-A-T isn't a checklist you complete once. It's closer to a description of what genuinely useful, accountable content already looks like — the practical takeaway is to build content that would hold up to a skeptical, knowledgeable reader, not content that merely covers a keyword.
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