E-E-A-T content scoring, explained without the mysticism

6 min read

E-E-A-T stands for experience, expertise, authoritativeness and trust. It is not a single ranking factor but a set of qualities evaluators and systems look for, and each one maps to concrete, checkable edits: firsthand detail for experience, precision and depth for expertise, credible citation and author identity for authoritativeness, and transparency for trust.

Score each dimension separately

Averaging the four into one number hides the problem. A page can be technically expert and completely untrustworthy because it has no author, no date and no sources. Score them individually and fix the lowest.

  • Experience: firsthand specifics — what you did, on what data, with what result
  • Expertise: correct terminology, real numbers, edge cases addressed
  • Authoritativeness: named author with credentials, linked primary sources
  • Trust: publication and update dates, clear contact route, no unverifiable claims

The edits that move the score fastest

Add one concrete example with real figures. Attribute the page to a named person with a linked bio. Replace vague superlatives with a measurement. Link the two most important claims to primary sources. Those four edits usually take under an hour and lift the weakest dimension immediately.

Score before you publish, not after

Scoring a live page tells you what to retrofit; scoring a draft tells you what to write. Orion scores E-E-A-T and on-page SEO live in the editor and suggests the specific copy-paste improvement for whichever dimension is weakest, so the fix happens before publication rather than in a later audit.

Frequently asked

Is there a target E-E-A-T score?
Aim for 80 or above before publishing. Below that there is almost always an obvious missing element — no author, no sources, or no firsthand detail.
Does E-E-A-T affect AI answers too?
Yes, and often more visibly. Assistants prefer sources with clear authorship, dates and citations, so the same edits improve both classic rankings and citation likelihood.

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