E-E-A-T Checklist 2026: 38 Signals Google Uses to Evaluate Your Content

E-E-A-T is one of the most discussed concepts in SEO and one of the most poorly implemented. Most sites treat it as a checklist to fake rather than a framework that describes what genuinely authoritative content looks like.

Google added the framework to its Quality Rater Guidelines because it needed a systematic way for human evaluators to distinguish trustworthy, expert content from persuasive-but-unreliable content. Understanding what raters actually look for — and why — is more useful than mechanically checking boxes.

What E-E-A-T Is and Why the Extra E Changes Everything

E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness. It's the evaluation framework used by Google's human Quality Raters — contractors who score pages against Google's guidelines to help calibrate the algorithmic systems.

The critical clarification: E-E-A-T is not a direct ranking factor with a numeric score that Google's algorithm reads. There is no "E-E-A-T score" attached to your pages. Instead, Quality Rater feedback trains and calibrates the algorithms that do affect rankings directly.

The framework existed as E-A-T (no first E) for years. In December 2022, Google added "Experience" as the first signal — a change that's more significant than it sounds.

The original framework asked: does this author have the credentials and knowledge to be authoritative on this topic? The addition of Experience asks a different question: has this author actually done the thing they're writing about?

That distinction matters enormously. A cardiologist writing about heart health demonstrates Expertise. A patient who has managed their own heart condition for 15 years and is writing from that lived experience demonstrates Experience. Google now explicitly values both — and recognizes them as different signals.

YMYL topics change the calculus entirely. Your Money or Your Life (YMYL) content — health, finance, legal, safety — gets approximately 10x stricter Quality Rater scrutiny. A thin, anonymous article about investing strategies will be rated lower by raters than a similar article on home decor, and those rater signals influence algorithmic rankings on those topics accordingly.

Experience: Proving You've Actually Done the Thing

Experience is the signal most sites are still failing to demonstrate in 2026 — three years after it was formally added to the framework.

The specific patterns that signal genuine experience to Quality Raters:

First-person specificity: "When we migrated 47 client sites from HTTP to HTTPS in 2024, we saw ranking drops in 12 cases, all of which recovered within 6 weeks." Compare that to "Migrating to HTTPS can temporarily affect rankings." The first sentence signals experience. The second signals research.

Failure disclosure: Authentic experience includes failure. "This approach worked for 80% of cases; the 20% where it failed had one thing in common..." is a strong experience marker. Content that presents only successes reads as research-based or promotional.

Operational specifics: Specific tools, versions, timeframes, and conditions — "we ran this in Google Ads from January through March 2026 with a $200/day budget targeting exact match" — anchor claims in specific experience. Generic claims don't.

Evidence artifacts: Screenshots, photographs, data exports, and annotated visuals showing actual work. Not stock photos of generic scenarios — specific documentation of the specific thing you did.

The opposite of experience signals: "studies show," "experts recommend," "it is generally accepted that." These phrases signal that the author synthesized other sources. That may demonstrate research skills, but it demonstrates Experience not at all.

Expertise: Demonstrating Knowledge Depth, Not Just Coverage

Expertise is what most SEOs think of when they think of E-E-A-T. The signal isn't just that an author has credentials — it's that the content itself demonstrates deep, current, accurate knowledge.

Expertise signals in content:

• Correct technical terminology used accurately and precisely. Using terms like "crawl budget" or "Core Web Vitals" without explaining them signals that the author assumes a knowledgeable audience — a marker of expert communication.
• Nuanced positions that acknowledge complexity. Experts say "it depends, and here's what it depends on." Non-experts give simple answers to complex questions.
• Primary source citation. Citing Google's Search Quality Rater Guidelines directly, rather than citing a blog post that summarizes them, signals that the author accesses primary sources.
• Up-to-date information. Outdated claims — citing FID metrics after they were replaced by INP in March 2024 — signal that the author hasn't kept up with the field.
• Topical depth over breadth. A site with 20 deep, specific articles on email marketing demonstrates more email marketing expertise than a site with 200 shallow articles across all of digital marketing.

Expertise at the author level: LinkedIn profiles, academic publications, conference talks, professional certifications, and work history at recognizable institutions. Author pages that include this information and link to verifiable external profiles provide Quality Raters with the evidence they need to score Expertise highly.

Authoritativeness: Building the Off-Page Signals Google Trusts

Authoritativeness is primarily an off-page signal — it's what the broader web says about you, not what you say about yourself. That makes it the slowest E-E-A-T dimension to build and the hardest to shortcut.

The signals Quality Raters look for and that Google's algorithms measure:

Backlinks from authoritative, topically relevant sources. A link from a major industry publication in your field carries more weight than links from generic directories or unrelated sites. Raters look at whether the site linking to you has its own authority on the topic.

Brand mentions (with and without links). Google processes unlinked brand mentions as soft authority signals. Being mentioned in The Wall Street Journal, an academic paper, or a recognized industry publication — even without a link — builds authority.

Wikipedia presence. Having a Wikipedia article about your organization (or your authors) signals a threshold of notability that Google weighs as an authority signal. This is a symptom of authority, not a path to manufacturing it.

Author reputation across the web. Quality Raters look up authors. An author with a strong LinkedIn profile, bylines in industry publications, speaking credits, and social media presence with genuine engagement is an authority signal independent of the site they're writing for.

Consistent positive brand signals. Reviews on independent platforms, media coverage, industry awards, and community recognition all contribute to the broader authority picture.

What doesn't build Authoritativeness: self-published guest posts on low-authority sites, paid link schemes, press releases distributed to wire services, and testimonials on your own site.

Trustworthiness: Why This Is the Most Important Layer

Google's Quality Rater Guidelines describe Trustworthiness as "the most important member of the E-E-A-T family." A site can have high Experience, Expertise, and Authority signals — but if it fails Trustworthiness, it fails overall.

The key insight: Trustworthiness is about accuracy and transparency, not just security signals. It's not sufficient to have HTTPS and a privacy policy. Raters evaluate whether the site is honest about what it is and who is behind it.

Trustworthiness signals:

• HTTPS with valid certificate. A non-negotiable baseline — any site serving content over HTTP in 2026 fails immediately.
• Accurate, complete About page. Raters read About pages carefully. Vague descriptions ("a team of passionate experts") lower trust scores. Specific information about the organization, its mission, and its team raises them.
• Reachable contact information. A working contact email or form. Phone numbers where appropriate for the business type. Physical addresses for businesses that have them.
• Clear correction and update policies. When content is updated, showing the update date and noting what changed is a trust signal. Quietly editing articles without acknowledging changes is a trust deficit.
• Accurate, well-sourced claims. Raters fact-check specific claims in articles. Inaccurate claims — even minor ones — lower trust scores. Cited sources that don't support the claims lower trust scores further.
• No deceptive UX. Clickbait headlines that don't reflect content, misleading meta descriptions, hidden advertising labels, and dark patterns all reduce Trustworthiness scores.

The Complete E-E-A-T Checklist: 38 Items

Use this as an audit framework. Each item is binary — either you have it or you don't.

Experience (8 signals)

1. Articles contain first-person accounts with specific details ("we tested," "when I ran this," "our client's data showed")
2. Content discloses failures and what was learned from them, not only successes
3. Operational specifics are present: tools, dates, conditions, versions
4. Visual evidence of actual work: screenshots, photographs, data visualizations from original sources
5. Content reflects current, firsthand familiarity with the topic — not reliance on older research
6. Authors make claims that could only come from direct experience, not from synthesizing others' work
7. Time-specific details anchor the experience (month/year, project duration, specific context)
8. Anecdotes include resolution: what happened, what was tried, what worked, what didn't

Expertise (9 signals)

9. Every article has a real, named author byline
10. Author page exists and links from the byline
11. Author page lists relevant credentials, experience, and professional history
12. Author page links to external verifiable profiles (LinkedIn, industry publications, professional association pages)
13. Content uses correct technical terminology accurately — no misused jargon
14. Claims cite primary sources (official documentation, peer-reviewed research, original studies) rather than only citing other blogs
15. Content reflects current state of the field — no outdated information presented as current
16. Nuanced positions are taken where the topic has genuine complexity
17. The topical depth of the site suggests genuine specialization, not surface coverage of many topics

Authoritativeness (11 signals)

18. Site has earned editorial backlinks from recognized sources in your industry
19. Site or authors have been mentioned in publications independent of your own content
20. Author has bylines or cited work in external, independent publications
21. Author has a verifiable external profile (LinkedIn, professional bio, academic profile)
22. Author has been cited by others in the field
23. Organization or author has speaking credits or media appearances
24. Brand name is searchable and returns consistent, positive signals
25. Reviews or ratings exist on independent platforms (G2, Trustpilot, Google Business)
26. Site demonstrates consistent, sustained publication — not a burst of content followed by inactivity
27. Other recognized sites link to the site as a resource, not just a transaction
28. Social profiles are maintained and reflect genuine engagement with the topic area

Trustworthiness (10 signals)

29. Site is served over HTTPS with a valid certificate
30. About page clearly describes the organization, its mission, and who runs it — no vague descriptions
31. Contact information is complete and reachable (working email, form, or phone)
32. Privacy policy is present, accurate, and clearly describes data handling
33. Update dates are visible on articles and reflect genuine updates
34. When content is corrected, corrections are disclosed transparently
35. Headlines match the content — no clickbait titles that the body doesn't deliver on
36. Advertising is clearly labeled and separated from editorial content
37. Sponsored content and affiliate relationships are disclosed
38. Factual claims are accurate and sources are cited — no statements that contradict evidence

E-E-A-T for AI Search: How LLMs Read Trust Signals

LLMs don't use Google's Quality Rater Guidelines explicitly, but they've been trained on vast amounts of text that correlates with trustworthy sourcing — and they've been fine-tuned to prefer citing authoritative, accurate content.

The result is that the signals LLMs use to evaluate citation-worthiness map almost exactly to E-E-A-T:

Named authors with discoverable expertise. When an LLM evaluates a page for citation, a named author with verifiable credentials increases the likelihood of citation. Anonymous content or "Staff Writer" bylines reduce it.

Specific, evidenced claims. LLMs are explicitly trained to prefer citing sources that support their claims with evidence rather than making assertions without backing. "Our analysis of 500 sites found X" is more citable than "experts believe X."

Consistency with established knowledge. LLMs have internal knowledge bases they evaluate sources against. Content that contradicts established facts without strong evidence is flagged as low-reliability and rarely cited.

Institutional or professional context. Content from organizations with clear institutional identity — a recognized business, a professional association, an academic institution — is cited more readily than content from anonymous or unidentifiable sources.

The practical implication for your E-E-A-T strategy in 2026: improving your E-E-A-T signals serves your Google rankings and your AI search visibility simultaneously. These are not separate optimization paths. The same investments — real author profiles, primary source citations, specific experience markers, and accurate claims — improve both.

Treat E-E-A-T as a description of what genuinely trustworthy, authoritative content looks like — not as a set of boxes to check. Sites that build the underlying substance those signals reflect will outperform sites trying to manufacture the signals without the substance.