SEO · 30 mins · Live-page review + creator and source checks + Schema.org Validator or Google Rich Results Test when markup matters + any AI

Build an Evidence-Based E-E-A-T Audit in 30 Minutes

30 minsE-E-A-T Audit PackAI includedDifficulty: Hard

The problem

Three pages. Three different reasons to trust, question, or stop.

One page makes a dangerous money promise. One gives careful health guidance and needs a small technical correction. One says products were tested but does not show how. A useful E-E-A-T audit must tell those situations apart.

Stop and protect

A money promise could cause real loss

Northstar promises a guaranteed 18% return without a responsible creator, risk method, or verifiable evidence. A byline or schema would not make the offer safe.

Maintain

Strong health guidance can need a small fix

Harborwell names its writer and reviewer, cites authoritative sources, and gives safety advice. Its visible review date and markup date do not match.

Earn credibility

A test claim needs inspectable proof

Juniper says it tested eight products, but the article does not show the test log, method, original evidence, or an early affiliate disclosure.

The insight

Purpose sets the evidence standard. Trust connects the evidence.

Begin with what the reader may do and what could happen if the page is wrong. Then separate the trust evidence you found from the trust evidence that is missing, decide whether the purpose needs experience, expertise, or both, and act on the largest gap.

3 moves

Purpose and stakes, evidence and gaps, material Trust action

3 live pages

One high-impact risk, one maintenance case, one credibility gap

1 own page

Apply the same method to one query-page pair without making the play too long


The method

The 5-step Trust evidence method

Learn the decision rule, make the initial call yourself, and use AI to challenge the evidence chain and help turn it into an implementation brief.

1

Set the standard

Decide likely purpose, reader action, and possible harm before choosing a route.

2

Inspect the evidence

Check the live page, author, reviewer, dates, links, sources, experience cues, and markup.

3

Build the Trust chain

Connect the evidence you found to the gaps, a conclusion, an action, and a priority.

4

Draft and challenge

AI drafts from the learner's work. The learner checks feedback and edits the sheet.

5

Trace and hand off

Final review checks that priorities and actions trace to evidence and open checks stay visible.


The deliverable

What you will walk away with

A traceable E-E-A-T Audit Pack an editorial team can verify and use.

Purpose-and-stakes route for every active page
Live-page evidence record with gaps
Compact Trust evidence chain
Six-part fix sheet per active page
Open verification items and owner
Learner-selected priority justified by harm and evidence gap
One-sentence editorial handoff note per active page

FAQ

Frequently asked questions

What does the E-E-A-T Audit Pack contain?

It contains a purpose-and-stakes decision, evidence record, Trust evidence chain, and implementation fix sheet for every active page. The sample uses three pages; your own data uses one.

Why does the audit begin with purpose and possible harm?

The same signal can matter differently on different pages. Purpose and possible harm tell you whether the page needs demonstrated experience, qualified expertise, stronger sourcing, clearer accountability, or only maintenance.

Does schema prove E-E-A-T?

No. Markup can describe visible facts in a machine-readable way. It does not prove that a fact is true, a creator is qualified, an experience claim is genuine, or a page deserves Trust.

Will this improve rankings or AI citations?

It may improve clarity, reliability, and accountability. It cannot guarantee crawling, indexing, rankings, traffic, rich results, or selection in an AI answer.

What if a live page cannot be fetched?

The prompt continues, reports the fetch failure, uses the learner's supplied evidence, and must not claim that the page was verified.


Get started

Choose how you want to work

Start play — understand the method first →

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