Know Your E-E-A-T Score
Before Google and AI Do

E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness — the four-pillar framework Google uses to evaluate content quality. AI engines use the same signals when selecting citation sources. Pages with strong E-E-A-T signals are cited at approximately 4x the rate of pages with weak signals, making E-E-A-T optimisation the highest-leverage activity for improving AI citation rates.

The 9 signals are: Author schema with name, credentials, and sameAs links; Author bio page with verifiable expertise; Publication date with datePublished and dateModified; External citations to peer-reviewed or authoritative sources; Organisation schema with contactPoint and address; Regulatory or accreditation identifiers for YMYL content; Third-party trust marks and review aggregates in schema; Editorial standards documentation; and Content accuracy signals including fact-check schema where applicable.

The four highest-impact improvements are: Add complete Person schema to author pages including credentials and sameAs links to LinkedIn. Add datePublished and dateModified to all article schema. Include 3 to 5 external citations to authoritative sources per article. Complete your Organisation schema with full contactPoint and address data. Each of these can typically be implemented in under 30 minutes and produces measurable E-E-A-T score improvements.

Pages scoring above 70 are cited at approximately 4x the rate of pages scoring below 40. In competitive niches like health and finance, you typically need above 80 for consistent AI citations. The E-E-A-T Scorer benchmarks your score against AI-cited content in your specific niche, not just generic averages.

Yes. The audit works on any publicly accessible URL — blog articles, product pages, category pages, landing pages, and documentation. The signal weighting adjusts automatically based on detected content type: YMYL content types like health and finance receive additional regulatory signal checks, while informational content receives heavier weighting on semantic and entity signals.

Yes. The E-E-A-T Scorer is fully available on the free plan with 15 runs per month. Every run includes all 9 signal scores, the prioritised fix list, and schema code generation.

The fastest method is using Yoast SEO or Rank Math — both have built-in Author schema fields in their content settings. For manual implementation, create a Person schema JSON-LD block with name, jobTitle, worksFor (your Organisation), sameAs array with LinkedIn and other verified profile URLs, and url pointing to your author archive page. Paste this into the page head using a header injection plugin or the theme's functions.php wp_head hook. The E-E-A-T Scorer generates the exact JSON-LD for your author details — copy it directly.

Yes. Google applies heightened E-E-A-T scrutiny to YMYL topics — Your Money Your Life — which includes health, finance, legal advice, safety, and major life decisions. For YMYL content, E-E-A-T scores below 75 are strongly associated with ranking suppression. For informational and entertainment topics, the threshold is lower — pages scoring above 55 typically remain competitive. The E-E-A-T Scorer detects your content type automatically and adjusts the benchmark threshold in its scoring accordingly.

Yes. The most impactful E-E-A-T improvements do not require expert credentials — they require proper documentation of the expertise you already have. Completing your Author schema with accurate job title and employer, adding sameAs links to your LinkedIn profile, adding dateModified to your articles, and including external citations to authoritative sources are all implementable by any content team member in under an hour per article. The E-E-A-T Scorer prioritises these high-impact, low-effort improvements first.

Traditional SEO signals — keyword density, backlink count, page speed — are technical and quantitative. E-E-A-T signals are qualitative trust indicators: who wrote this, are they credible, does the content cite authoritative sources, is the brand verifiable as a real entity? AI engines weight E-E-A-T more heavily than traditional search engines because AI citation selection requires confidence that the cited source is accurate and trustworthy — not just topically relevant and technically optimised.