Support expertise and authority with evidence readers can check.
Start with the claim, then find the evidence. Make experience, expertise and recognition understandable without overstating what a source proves.
A useful authority review connects material claims to relevant evidence, accurate authorship and clear limitations. Distinguish first-hand work, professional knowledge, external recognition and reported outcomes. Keep public statements consistent with their supporting sources, correct gaps and retain review records. This editorial method does not produce a Google score or guarantee search rankings, AI citations or commercial results.
1. Use E-E-A-T to ask better questions about credibility
E-E-A-T refers to experience, expertise, authoritativeness and trustworthiness in Google Search’s content-quality guidance. Google says E-E-A-T is not a specific ranking factor; quality raters help evaluate the performance of its systems rather than directly determining a page’s ranking. Read the official people-first content guidance for that distinction.
This guide proposes a practical claim-and-evidence review for executives and organizations. It is not a measurement of a Google score, a universal AI ranking model or a record of client results. The objective is to let a reader understand who is making a claim, why it is credible and where its limits lie.
A polished biography is not a substitute for relevant work. Start with the questions that matter to the reader: whether the person or organization has the experience claimed, whether a method is explained and whether a result can be checked.
2. Connect each important claim to an appropriate evidence asset
An evidence asset is a document, source or observable piece of work that helps assess a specific claim. The categories below are a proposed review structure. They are not provider ranking weights or a list of mandatory signals.
| Claim being considered | Potential evidence | Limit to retain |
|---|---|---|
| First-hand experience | A documented project, test method or original work sample | One experience does not establish universal expertise |
| Professional knowledge or qualification | A relevant publication, credential or explained analysis | Check scope, issuer, dates and what was actually demonstrated |
| Independent recognition | A substantive third-party reference with clear context | A mention is not automatically endorsement or proof of outcomes |
| A reported result | Method, period, population, denominator and supporting records | A selected case does not establish typical results or causation |
Download the blank evidence register. It contains column names only. Add real, authorized records and mark unavailable evidence as unknown rather than filling the gaps with assumptions.
3. Show the work behind claims of experience and expertise
Choose a material claim and describe what the author or organization actually did. A useful record makes the task, method, contribution and limits understandable. Publishing a longer biography or adding a credential unrelated to the subject does not resolve a weak claim.
- For a work sample, identify the problem, the contribution made, the method and what the sample demonstrates. Label mockups, prototypes and fictional examples explicitly.
- For a credential, verify the issuer, subject, current status where relevant and the precise qualification. Do not expand a course or participation record into a different professional title.
- For original research, describe the sample, collection dates, method and limitations. Separate observed data, interpretation and proposed action.
- For a case study, distinguish what is documented from what is inferred. Retain the period, scope and evidence necessary to assess a reported change; avoid presenting a selected example as a typical outcome.
Use only material that can be published within its actual permissions and context. When client details cannot be disclosed, describe the limit honestly. An anonymized case still needs underlying evidence; anonymity does not make an invented result acceptable.
4. Read external references in their actual context
Independent coverage can help a reader investigate a claim because it supplies another account. It still needs scrutiny: who published it, what relationship exists, what was said and whether the reference supports the particular assertion. This review does not prescribe a quota of links or press mentions.
- Read the original reference instead of relying on a logo, screenshot or unattributed quotation. Check whether it discusses the entity, its work or merely a related topic.
- Distinguish editorial coverage, contributed articles, paid placements, sponsorship and directory listings. Describe the relationship accurately rather than calling every appearance independent endorsement.
- Keep employment, independent activity, partnerships and client relationships clear. A personal project must not imply that an employer sponsors it without evidence.
- For an award, appointment or public contribution, retain the issuing source, date and relevant context. Check whether the wording supports the title or status claimed.
Fictional example: an executive speaks on a panel sponsored by their employer. That event record may support participation and the topic discussed; it does not automatically prove an independent award, personal client results or employer endorsement of a separate business. No real person or client is represented by this example.
5. Make authorship, source support and corrections visible
Give the reader a clear route from a material assertion to the evidence behind it. Explain how a page or analysis was produced when that helps evaluate it. Correct inaccurate claims across the visible article, its Markdown edition and any structured answer index.
- Use accurate author attribution and a relevant public profile. Separate author, reviewer and subject where those roles differ; never invent an expert identity or review.
- Describe the method and limits of material analysis. If automation contributed substantially, explain the contribution where needed to understand the work; automation does not verify facts by itself.
- Maintain useful publication and update dates. Make a correction because the substance changed, not to give unchanged material an artificial appearance of freshness.
- Keep contact, service scope and relevant policies understandable. An attractive page or a technical security feature cannot establish the truth of an unsupported professional claim.
Google’s Article structured-data documentation covers properties such as author and dates. Its general structured-data policies require truthful representation of the page and do not guarantee a rich result. Markup should describe verified content, not manufacture experience, credentials or endorsements.
Use the entity schema reference to keep the relationships between people, organizations and pages consistent. The executive digital-footprint guide helps locate conflicting public descriptions.
6. Review credibility separately from search and AI outcomes
Use a repeatable editorial review: select important claims, collect the best available evidence, record limitations, decide what to correct and assign the next review. This proposed process has no fixed 90-day promise or guaranteed number of external mentions.
- Start with claims that affect a real decision: current role, service capability, professional qualification, reported result or material relationship. Prioritize incorrect or unsupported claims.
- Record whether each source supports the full claim, a narrower statement or none of it. Revise the wording to the evidence rather than stretching the source.
- Retain the evidence reference, reviewer and revision. Recheck time-sensitive facts when roles, services, credentials or source pages change.
- Report content corrections separately from search appearances, AI mentions, cited links and qualified enquiries. A better-supported page does not by itself prove why a ranking or answer changed.
Google’s guidance for AI features in Search does not establish an evidence-register score or a special schema requirement for its AI features. Do not turn this workflow into a promise of citations, and do not assume another AI provider applies the same evaluation.
Use the AI reputation audit for observed answer problems, the prompt-set guide for declared tests and the dashboard for separate measures and limitations.
Documentation checked on 29 October 2026. This page proposes an editorial review method; it is not an audit of a particular organization’s evidence or an assurance of search performance.
Questions and answers
What does E-E-A-T mean?
E-E-A-T refers to experience, expertise, authoritativeness and trustworthiness in Google Search’s content-quality guidance. It can help frame questions about credibility. Apply those questions to the page’s purpose and evidence rather than treating the initials as a publishing checklist that guarantees rankings.
Is E-E-A-T a specific Google ranking factor or an AI visibility score?
Google says E-E-A-T is not a specific ranking factor. This guide does not calculate a Google score or a universal AI visibility score. Its register is a proposed editorial review tool; assessments of evidence must stay separate from observed rankings, mentions and citations.
What is an evidence asset?
An evidence asset is a document, source or observable piece of work that helps assess a specific claim. Examples include an explained work sample, relevant credential, original analysis or substantive external reference. Record exactly what it supports and what remains unverified.
Do external mentions automatically prove authority?
No. Read the original source and its context. Distinguish editorial coverage, contributions, paid placements, sponsorship and listings. A mention may support a narrower fact without establishing endorsement, expertise across a field or a reported business outcome.
Can a case study establish typical results?
A selected case does not by itself establish typical outcomes or causation. Explain the period, scope, method, contribution and supporting evidence. Label fictional examples clearly and do not invent client details, metrics or first-hand experience to fill an evidence gap.
How should an international team review credibility claims?
Select the claims that matter to the intended audience, verify the best available sources and record their scope and limitations. Correct unsupported wording across public pages and copies, assign an owner and retain the review history. Measure search and AI outcomes separately without promising a result from the review.
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