What Is E-E-A-T, and What Evidence Does Google Look For?

E-E-A-T letters: experience, expertise, authoritativeness and trust

E-E-A-T breaks into four qualities, and each one answers a different reader question. Has the writer done this? Do they know the subject? Do others recognise them? Can the page be relied on? Google’s guidance treats the last of these, trust, as the one the other three support.

The extra “E” for experience is the newest part. It recognises that a person who has done something often helps more than a summary.

Google’s own example of experience is everyday. Someone describing a new way to clear snow from a driveway generally needs no special expertise.

So a small business owner explaining their own work can show strong experience without formal qualifications.

E-E-A-T and Google: rater guidelines vs ranking systems

E-E-A-T appears in two places at Google, and mixing them up causes most confusion. Quality raters use it, through the Search Quality Rater Guidelines, to judge whether results look good. Ranking systems use many other signals that, together, tend to identify content with strong E-E-A-T. There is no single E-E-A-T score.

Google’s page on creating helpful, reliable, people-first content is clear on the split. “E-E-A-T itself isn’t a specific ranking factor.”

It also says raters “have no control over how pages rank”. Their data is not used directly in ranking algorithms.

Instead, Google compares rater feedback to diners’ comment cards. It tells Google whether its systems seem to be working.

That makes the Search Quality Rater Guidelines a self-assessment tool. Google suggests reading them to judge your content from an E-E-A-T angle.

Digital Magma uses the guidelines exactly that way. They are a lens for reviewing pages, never a list of tricks.

E-E-A-T for YMYL topics: why trust weighs most

E-E-A-T carries extra weight on “Your Money or Your Life” topics, which Google defines as those that could significantly affect people’s health, financial stability or safety, or society’s welfare. For these, Google says its systems give even more weight to content aligned with strong E-E-A-T.

Medical clinics, financial advisers, law firms and safety-critical manufacturers all publish YMYL content. A wrong answer can hurt someone.

Trust matters most here because readers cannot easily check the facts themselves. They rely on who wrote the page and how.

Google also lists accuracy as a factor for these topics. Its guidance says informational pages should be factually accurate, especially where lives or well-being are at stake.

For YMYL pages, Digital Magma looks for a named, qualified author or reviewer, cited primary sources, and a visible date on every page.

Non-YMYL pages still benefit from the same habits. They simply carry less risk when something is missing.

E-E-A-T evidence Google looks for on a page: who, how and why

E-E-A-T evidence on a page comes down to three questions Google itself suggests asking: who created the content, how it was created, and why. Google calls “why” perhaps the most important. Answering all three in visible text gives raters and readers what they need to judge trust.

Who. Is the author obvious? Google asks whether pages carry a byline where one is expected, and whether it leads to background on the author.

It warns against fakes. Made-up names, AI-generated headshots or false credentials are deception, which Google treats as a sign of low quality.

How. Explain the process. For reviews, Google mentions how many products were tested and how. For AI-assisted work, it suggests disclosing how automation was used.

Why. The answer should be “to help people”. Content made mainly to attract search visits is, in Google’s words, “not aligned” with what its systems reward.

Digital Magma answers all three on its own knowledge-base pages. The byline names the author, the sources line says how facts were checked and when, and the opening says who the page is for.

E-E-A-T in AI search: why first-hand experience stands out

E-E-A-T gains weight in AI search because generative answers can already summarise common knowledge. Google’s guide to its generative AI features asks for “non-commodity content”, meaning pages with unique expert or experienced takes. A first-hand account offers something a model cannot easily produce from existing pages.

Google’s generative AI guide contrasts a first-hand review, which offers personal experience, with a summary that “simply restates information already available elsewhere”.

It gives a pair of example titles. A generic “7 Tips for First-Time Homebuyers” is commodity content. A specific, lived story is not.

Google’s guidance on generative AI content adds a warning. Mass-producing pages without added value may breach its scaled content abuse policy.

So AI-assisted writing is allowed, but it must be checked. Google says to fact-check AI output before publishing, metadata included.

Every page in Digital Magma’s knowledge base carries real client experience for this reason, using only approved results.

E-E-A-T checks: a 7-point page audit

E-E-A-T can be checked page by page with seven questions taken from Google’s helpful content guidance. Each one has a clear pass or fail. Run them on your most important pages first, especially any that touch health, money or safety, and fix failures in this order.

1. Byline. Does a named author appear, linked to a profile page?
2. Credentials. Does the profile list real, relevant qualifications or experience?
3. First-hand detail. Does the page include something only the author could know?
4. Sources. Are facts cited to primary sources, named in the text?
5. Accuracy. Are there any easily verified errors? Google asks this directly.
6. Date and ownership. Is there an updated date and a clear About page?
7. Purpose. Would a visitor who came directly find the page useful?

This page’s own author box shows points one and two. It names Ankit Sachan, links his profile, and lists only certifications he holds.

E-E-A-T in our client work

E-E-A-T shaped Digital Magma’s work most clearly for a Toronto ENT clinic, a YMYL site where patients decide about their health. Over a four-year engagement, the priorities have been accuracy, named doctors and clear service details, each written in plain text on the relevant pages.

For a Canadian welding equipment manufacturer, experience shows through exact specifications and application detail. That site holds 40+ keywords in Google’s top 10 and appears in AI Overviews and ChatGPT.

For an app development company selling in six countries, trust signals include clear ownership and the same contact details on every market page.

Each element answers a question a careful buyer would ask before calling, booking or sending an enquiry.

E-E-A-T: frequently asked questions

E-E-A-T questions from writers, SEO executives and site owners.

E-E-A-T: related terms, sources and author

E-E-A-T links to these Digital Magma entries:

• Entity SEO: making authors and brands recognisable
• AI citation: what earns a mention in AI answers
• Schema markup: Person and Organization details
• Semantic search: search by meaning
• What content can AI quote?

Sources: Google Search Central on helpful, people-first content, the Search Quality Rater Guidelines, Google’s generative AI features guide and its guidance on generative AI content. Checked on 26 October 2026.