Content Strategy
E-E-A-T
Google's evaluation framework for content quality — Experience, Expertise, Authoritativeness, and Trustworthiness — used by quality raters and reflected in ranking signals.
Definition
E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness. It is the criteria Google's Search Quality Rater Guidelines instruct human evaluators to apply when judging whether a page deserves to rank for a given query. The framework does not map to a single ranking signal; it is encoded indirectly through many signals — author transparency, citation patterns, original information, site reputation, technical trust markers — that Google's ranking systems are tuned to recognise. The 'second E' (Experience) was added in 2022 to capture first-hand knowledge specifically, as opposed to summarised expertise.
Why it matters
E-E-A-T is the most useful published rubric for evaluating whether content stands a chance of ranking long-term, especially in the YMYL categories (Your Money, Your Life — health, finance, legal) where the bar is highest. It is also the framework most directly relevant to whether AI-assisted content earns trust. The framework does not penalise AI use; it penalises content that lacks experience, expertise, authority, or trust signals — which a lot of unedited AI content does by default. For publishers and product sites, the practical move is to make every E-E-A-T signal explicit: named authors with credentials and bios, clear editorial standards, transparent AI use policy, original examples and data, citations to primary sources, and structured information about the organisation behind the content. None of these signals are difficult; most sites simply do not implement them.
Examples
Experience signal
A review article that says 'I tested this software for six months on a team of twelve' and shows screenshots beats a review that summarises features from the vendor's site.
Expertise signal
A named author bio with relevant credentials, links to other work, and a real photograph carries more weight than 'Editorial Team.'
Trustworthiness signal
A published editorial policy, an explicit AI use disclosure, a corrections process, and contact information for the publishing organisation all signal trust to both raters and ranking systems.
Frequently asked
Does E-E-A-T penalise AI-assisted content?
Not directly. It penalises content that lacks experience, expertise, authority, and trust — which a lot of AI-only content does by default. AI-assisted content with strong E-E-A-T signals ranks fine.
How do I show 'Experience' on a topic I have not lived?
Either get the experience and write about it, or commission a contributor who has. Faking it is the failure mode E-E-A-T is designed to catch.
Is E-E-A-T a ranking factor?
Not as a single signal. It is a rubric the ranking systems are tuned toward via many indirect signals.
Related terms
AI Content Policy (search)
The set of guidelines that search engines use to evaluate AI-assisted content for ranking purposes.
AI Detection
The practice of estimating, using statistical signals, whether a piece of text was produced by a language model rather than a human.
Humanization (of AI text)
The process of editing AI-generated writing so that it reads, scans, and lands as work by a thoughtful human author.
Audience Fit
The degree to which a piece of writing matches the vocabulary, expectations, and decision-making style of its intended reader.
Put the concept to work
Open the rewrite engine and apply this principle to a draft of your own.
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