Glossary

E-E-A-T

Experience, Expertise, Authoritativeness, and Trustworthiness: the quality signals that AI and search engines use to evaluate content reliability.

Definition

What this term means

A quality framework standing for Experience, Expertise, Authoritativeness, and Trustworthiness, originally defined by Google for search quality evaluation, now increasingly relevant to AI-generated content curation. E-E-A-T is not a single metric but a collection of signals: first-hand experience with a topic, demonstrated professional expertise, recognised authority within a field, and overall trustworthiness of both the content and the publisher.

Why it matters

The business impact

Both search engines and AI systems use E-E-A-T signals to evaluate content quality and determine which sources deserve to be cited. For 'Your Money or Your Life' topics (health, finance, legal, safety), E-E-A-T is especially critical. Brands that invest in demonstrable expertise (author credentials, case studies, original research) and trust (security, transparency, reviews) earn preferential treatment in AI-generated responses.

Used in context

How you might use this term

A health supplement brand struggled with AI visibility because their content lacked E-E-A-T signals. After adding medically-reviewed labels, qualified author bios, clinical study citations, and implementing trust-related schema markup, they saw a dramatic improvement in how AI assistants described and recommended their products.
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