E-E-A-T – experience, expertise, authoritativeness and trustworthiness

Definition

E-E-A-T (EEAT) stands for Experience, Expertise, Authoritativeness and Trustworthiness and is used by Google to assess the credibility, quality and reliability of content – especially important for content that can affect people's health or finances.

What E-E-A-T means and why it matters

E-E-A-T – sometimes written EEAT, without hyphens – is Google's central quality framework for deciding which content is reliable enough to appear high in search results and to be used as the basis for AI-generated answers. What counts is not only what is said but who says it, based on what experience and in what context.

Experience has become more important as the volume of AI-generated content has grown. Google wants to see signs of real, practical experience – not just theoretical correctness. Expertise means subject depth and correct use of technical terms, while Authoritativeness is built through consistent presence, recognition and mentions from other credible players. Trustworthiness ties it all together through transparency, accuracy and a clear sense of who is behind the content.

The framework used to be called E-A-T (without Experience) and was expanded in December 2022, when Google added the fourth E, Experience, to give more weight to content based on first-hand experience (Google Search Central).

E-E-A-T carries particular weight for YMYL content (Your Money or Your Life) – content that can affect people's health, finances, safety or life decisions. But the principles apply to any industry that wants to build credibility online over the long term.

The extra E – how to show first-hand experience

Experience – the fourth E, added in 2022 – is the most concrete change compared with the earlier E-A-T. Google wants to see that the content is based on real experience, not just knowledge picked up from reading. Concrete ways to show it:

• Case studies with real data – Show results from real projects with concrete figures, timeframes and a description of the method
• Screenshots and your own examples – Images from your own tools, analyses and platforms confirm that the writer has actually worked with what is described
• Clear bylines and author profiles – Author names linked to LinkedIn, published articles and industry experience strengthen the Experience signals at website level
• Specific context and the first person – "We saw this in a project for a client in industry X" communicates experience in a way general phrasing does not

YMYL – not just health and finance

YMYL (Your Money or Your Life) covers content that can affect health, finances, safety or important life decisions. The E-E-A-T requirements are at their highest for these pages. The obvious categories are medical information, financial advice and law – but the concept goes further and is directly relevant to many B2B companies:

• SaaS agreements and subscription services – Buying advice on expensive agreements can end up in YMYL's grey zone. Google judges YMYL by the risk of harm to health, financial security or safety, not by the price tag
• Accounting and auditing – Advice on VAT, payroll and tax planning requires clear expertise and a clearly accountable author
• Law and compliance – Contracts, employment law and regulatory advice demand a high level of credibility and accuracy
• B2B consulting with a major business impact – Strategic recommendations that affect a company's direction and finances should be held to YMYL standards

The role of schema markup in E-E-A-T

With structured data you tell search engines and AI systems who is behind the content, what expertise they have and how different parts of the website fit together. The most important schema types for E-E-A-T:

• Person – Name, role, image and sameAs attributes pointing to LinkedIn and external profiles
• Organization – With founder, sameAs (external mentions and profiles), contactPoint and address
• Article – With an author reference and dateModified to signal freshness and editorial responsibility
• FAQPage – valid markup for questions and answers, but it no longer produces a FAQ box in Google. What makes the answers easy to cite is the format of the text itself

In an AI-driven search environment, where content is summarised and reproduced without human review, machine-readable credibility matters even more. AI systems rely on structural signals to decide whether a source is safe to cite – especially in YMYL areas.

E-E-A-T and AI visibility

E-E-A-T is not just a ranking concept – it is the selection system that decides which sources AI chooses to cite. Google AI Overviews, ChatGPT and Perplexity use similar signals to judge whether a source is credible enough to present as an answer.

In concrete terms: a page with clear author profiles, source references, an external presence and structured data stands a better chance of being cited in AI answers than an anonymous page where it is unclear who is behind it – however well written the content is. So work on E-E-A-T pays off in organic search and in AI answers alike.

E-E-A-T in practice

Working with E-E-A-T comes down to making the website and the people behind it transparent and verifiable – for search engines, for AI systems and for visitors. Google publishes its EEAT guidelines in the Search Quality Evaluator Guidelines, which are updated regularly and openly available.

At SEOS Design we help organisations build credible visibility online, for SEO and AEO alike. Read a case study in medical technology, or get in touch for advice on E-E-A-T, YMYL and AI visibility.