E-E-A-T Explained: How to Show Each Letter

E-E-A-T stands for Experience, Expertise, Authoritativeness and Trust. It is the framework Google’s human quality raters use to judge whether a page, and the person or business behind it, is a reliable source for its topic. It is not a ranking factor in itself, but Google says its ranking systems look for signals that line up with it, especially on topics where bad information can hurt people.

This guide is for business owners, marketers and writers who want to know what E-E-A-T actually requires rather than what gets repeated about it. It covers what the rater guidelines say, what “not a ranking factor” really means, how to show each letter on a page, why the bar rises for YMYL topics, and what the 2024 Google leak does and does not add.

On this page

• What does E-E-A-T stand for?
• Is E-E-A-T a ranking factor?
• Why trust sits at the center
• How to show each letter of E-E-A-T on a page
• YMYL: when the bar for E-E-A-T rises
• What the Google leak shows about authorship and quality
• E-E-A-T in AI search
• Building E-E-A-T into your site

What does E-E-A-T stand for?

E-E-A-T stands for Experience, Expertise, Authoritativeness and Trust, and each term has a specific definition in Google’s Search Quality Rater Guidelines. The current edition is dated September 11, 2025 and runs to 182 pages. Section 3.4 defines the four:

• Experience: whether the creator has the necessary first-hand or life experience for the topic. The guidelines’ example: would you trust a product review from someone who has used the product, or from someone who has not?
• Expertise: whether the creator has the necessary knowledge or skill. Their example compares rewiring advice from a skilled electrician with advice from an enthusiast who knows nothing about wiring.
• Authoritativeness: whether the creator or site is known as a go-to source for the topic. Most topics have no single official source, but some do, such as a government passport page.
• Trust: the extent to which the page is “accurate, honest, safe, and reliable.”

The framework was E-A-T for years. Google added the extra E for Experience in December 2022, largely to recognize that someone who has actually done or used the thing is often the most useful source, even without formal credentials.

Is E-E-A-T a ranking factor?

No, not directly, and Google says so plainly. Its guide to creating helpful, reliable, people-first content states that E-E-A-T itself isn’t a specific ranking factor, while “using a mix of factors that can identify content with good E-E-A-T is useful.”

The mechanism matters, because it explains what you can and cannot influence:

1. Raters do not rank pages. The rater guidelines state that no single rating can directly change how a page appears in Search. Google says rater data is not used directly in its ranking algorithms; it compares it to the feedback cards a restaurant collects from diners, a check on whether its systems are working well.
2. The systems learn from that feedback. Google’s algorithms use many signals. Rater evaluations help Google check whether those signals are surfacing the kind of pages raters would score as trustworthy.
3. The weight rises on sensitive topics. Google says its systems give even more weight to content with strong E-E-A-T on YMYL topics.

The systems that do the ranking change often, and the direction is consistent. When Google launched its March 2024 core update, it expected that update, with its earlier efforts, to cut low-quality, unoriginal content in results by 40%, and it later reported 45% less of it once the rollout finished.

So there is no E-E-A-T score to raise. There are signals that correlate with what raters reward: who wrote it, what they have done, what others say about them, whether the facts hold up. Our overview of SEO ranking factors puts E-E-A-T alongside the factors Google has confirmed.

Why trust sits at the center

Trust is the most important member of the E-E-A-T family, according to the rater guidelines, because an untrustworthy page has low E-E-A-T however experienced or expert it looks. The guidelines’ example is blunt: a financial scam is untrustworthy even if its author is a highly expert scammer. Experience, Expertise and Authoritativeness are there to support the assessment of Trust. The diagram below shows that structure, and the two sources of evidence raters are told to use.

Scroll the diagram sideways to see all of it.

The two evidence sources are the practical takeaway. Raters are told to look at what the site or creator says about themselves, starting with the About page or author profile, and then at what others say: independent reviews, references and news. A glowing About page with no outside corroboration is weaker evidence than a modest one that the rest of the web confirms.

How to show each letter of E-E-A-T on a page

You show E-E-A-T with evidence a reader can check, placed where a reader would look for it. Claims like “our experienced team” do nothing. A named author with a linked profile, a photo of the job, a cited source and a reachable phone number all do something. The table maps each letter to what raters ask and what you can publish.

Google’s own self-assessment questions point the same way. The helpful content guide asks whether it is self-evident who authored the content, whether bylines lead to more information about the author, and whether the use of automation or AI is clear to visitors where they would expect it. It also strongly encourages accurate authorship information. The diagram below marks where each signal usually sits on an article page.

Scroll the diagram sideways to see all of it.

Two implementation notes. First, a byline is only as strong as the author page it leads to, and that page is stronger when it is a consistent entity across the web. Our guide to Person schema and author entities covers the markup and the author page itself, so it is not repeated here. Second, the business behind the site needs the same treatment: a complete About page, consistent details, and Organization schema that ties your site to your profiles elsewhere.

What does not work: fake author personas, stock photos presented as your work, “reviewed by an expert” labels with no named expert, and credentials no one can verify. These are the opposite of Trust, which is the letter that matters most.

YMYL: when the bar for E-E-A-T rises

The amount of trust a page needs depends on how much harm a bad page could do. Google calls the high-risk topics “Your Money or Your Life,” defined in the rater guidelines as topics that could significantly impact the health, financial stability or safety of people, or the welfare of society. Medical, legal, tax, investment and safety information all sit here. The spectrum below uses the guidelines’ own examples of how the required level of trust varies.

Scroll the diagram sideways to see all of it.

If your business sits in a YMYL field, three things follow. Named, qualified authors or reviewers stop being optional. Claims need sources, ideally primary ones such as regulators and peer-reviewed research. And your reputation off the site, in reviews and professional listings, carries more of the load, because raters are told to research it and Google’s systems weigh YMYL trust more heavily.

What the Google leak shows about authorship and quality

The May 2024 leak of Google’s internal Content Warehouse API documentation, more than 2,500 pages of it, confirms that Google stores attributes related to authorship and page quality, but it does not show how, or how much, any of them are weighted. SparkToro’s write-up is explicit that the documentation does not show the weight of elements or prove which are used in ranking, and iPullRank’s analysis makes the same caveat.

With that framing, a few attributes are relevant to E-E-A-T. In each case, Google stores this attribute; the leak does not show how much it is weighted:

• RepositoryWebrefDetailedEntityScores.isAuthor, described as true if an entity is the author of the document. It suggests Google tries to connect documents to author entities, not just byline strings.
• QualityNsrPQData.contentEffort, described as an LLM-based effort estimation for article pages. It is the closest thing in the leak to a measure of how much work went into a page.
• QualityNsrNsrData.ymylNewsV2Score and QualityNsrNsrData.healthScore, site-level fields whose names point to YMYL and health classification. The documentation says little about them beyond the names (healthScore is described only as “categorical signals”), so treat them as evidence that such classifications are stored, nothing more.

None of this is a secret E-E-A-T score. It is consistent with what Google says publicly: the systems look for measurable proxies of the qualities raters judge. Our Google leak explainer covers the documents in more depth.

E-E-A-T in AI search

The same evidence that builds E-E-A-T in Google Search also decides whether AI systems will cite you, because those systems prefer sources they can attribute and corroborate. For Google’s own AI features, the link is direct, and the audience is large: Google said at I/O 2025 that AI Overviews had scaled to over 1.5 billion users. The sourcing rule is simple: its AI features documentation says a page must be indexed and eligible to show with a snippet to appear as a supporting link in AI Overviews or AI Mode. The pool is the same pool Google already trusts, though not only its top results: an Ahrefs study of 863,000 keywords found that 38% of pages cited in AI Overviews also rank in the top 10 for the query.

For ChatGPT, Perplexity and Gemini, the pattern is indirect but similar. A model deciding which passage to quote is looking for a clear author or organization, a verifiable fact, and agreement from other sources. That is Experience, Expertise and Trust expressed as extraction criteria. We cover the selection process in how AI engines choose citations, and the off-site half, earning the independent mentions raters and models both look for, in digital PR for AI search.

One honest caveat: no AI company publishes an E-E-A-T equivalent. The overlap is an inference from how these systems describe source selection and from what gets cited in practice, not a documented rule.

Building E-E-A-T into your site

E-E-A-T is built by publishing checkable evidence, not by adding trust badges. A practical order of work for most businesses:

1. Fix the basics of Trust first. A complete About page, real contact details, clear ownership, secure checkout if you sell, and accurate dates on content.
2. Put named people on your content. Bylines that link to real author pages, with background and relevant work.
3. Show the work. Original photos, results you are allowed to share, test notes, and the specific details only someone who did the job would know.
4. Cite primary sources. Especially on YMYL topics, and especially for numbers.
5. Earn outside corroboration. Reviews, professional listings, interviews and mentions from recognized sources in your field.

If you would like help working out which of these your site already shows and which it is missing, in Google Search and in AI answers, that is what our AI SEO service is built around.