E-E-A-T Audit for AI Search and Google

What does an E-E-A-T audit check?

An E-E-A-T audit checks whether important pages give readers enough evidence to assess who is speaking and why they should trust the information. It is not a badge or a single score. We connect each finding to a specific page, profile or missing proof point so your team can act on it.

The review can cover product pages, educational content, leadership biographies, company profiles and policy pages. For a SaaS business, we may inspect how product claims are supported and who reviews technical guidance. For a crypto business, we may check whether project identity, risk disclosures, team information and documented product details are consistent across public-facing materials. We record what is visible; we do not infer private qualifications or claim that a mention alone establishes authority.

The scope is set around your buyers and priority topics. If you also need a broader view of answer engines, see AI search visibility or the dedicated GEO audit.

Which trust signals should your team prepare?

Prepare materials that let a reviewer verify the claims your pages make. Start with the pages that influence a purchase decision, then gather the sources behind factual statements, author information, customer-facing policies and descriptions of your product. If a claim has changed, note what should replace it rather than leaving outdated copy unexplained.

We use a Spec Review to agree on scope, priority audiences and the pages to inspect. The client supplies access or URLs for the agreed properties and identifies any restricted or confidential materials. Public evidence is assessed as public evidence; private documents are not treated as proof that a visitor or search system can independently inspect.

A useful preparation checklist:

• List your priority services, products and audiences.
• Identify who owns content, technical fixes and legal review.
• Flag claims that require careful wording, including financial or product-risk statements.
• Share existing brand, author and editorial guidelines if available.

For a site-wide review, we can also map related technical questions through technical AEO.

How does the audit assess Google and AI search visibility?

We compare the site’s evidence with what is visible for a defined set of business-relevant questions. The purpose is to spot mismatches: a useful page with unclear authorship, an important claim without a supporting source, or company details that vary across public profiles. We document the query and observed output so your team can distinguish a site issue from a change in the answer being displayed.

For Perplexity, the review can include answer examples and the sources shown alongside them. For Google, it can examine relevant search results and visible AI answer features where available during the review. The assessment is an evidence review, not a claim about how either platform selects, ranks or summarizes material. For service-specific work, see Perplexity optimization and Google AI Overviews optimization.

We use a Channel Matrix to keep each platform, query, observed source and recommended action together. This makes the output useful for assigning work instead of treating AI visibility as a vague content goal.

What will the E-E-A-T audit deliver?

The project begins with scope confirmation and a request for priority URLs, target audiences and available documentation. We then review the selected materials, capture relevant public examples and separate findings into content, identity, trust and technical actions. When a recommendation needs specialist review, such as a legal or security statement, we label that dependency rather than rewriting it as if we were the responsible expert.

A Run Log records the pages and observable examples reviewed, along with open questions and agreed exclusions. The final Readout summarizes what to fix first, who should own each action and what evidence would close the gap. The audit is designed to help your team make decisions; implementation, ongoing publishing and monitoring can be scoped separately.

Typical timing is agreed after we see the number and type of pages, the number of markets or languages, and how quickly your team can answer clarification requests. To keep the work focused, send a small set of representative URLs and your primary business question first. If you need ongoing observation after remediation, review AI visibility monitoring.

What can an E-E-A-T audit not control in Google and AI answers?

The audit can verify the work performed and the evidence visible during the review, but Google and AI answer services control their own crawling, presentation and source selection. Their displays can change, so an audit cannot promise a ranking, citation, recommendation or lasting placement.

Use the findings as a decision document, not as a pass/fail certificate. First fix factual inconsistencies and unsupported high-impact claims; then clarify authorship, review responsibilities and trust information. After those changes, capture a fresh set of representative queries and page examples to assess what is now visible. Keep the original Readout so your team can compare observations and identify remaining work without assuming that a change in one answer proves a broader result.

If the audit surfaces thin or hard-to-verify explanations, pair the evidence work with content for AI answers. For entity inconsistencies, entity and knowledge graph building may be a better next scope.

When should you commission an E-E-A-T audit?

Commission the review when a team needs to understand whether its public evidence is clear and consistent before expanding content or investing in ongoing visibility work. It is especially useful when several people own content, product facts and policy decisions, because the findings provide a shared list of decisions rather than another disconnected set of recommendations.

The audit scope should match the decision you need to make. A focused review can concentrate on a set of commercial pages and related author or company information. A broader engagement can include more topics, markets and answer samples. We confirm those boundaries before work starts, along with the information required and the format of the Readout.

Send AEOTech your website, priority pages, target audience and the questions you want the review to answer. We will check fit, clarify the scope and provide a project plan. The project price is from $540 / project.

Prices

Starting prices in USD. Custom bundles and volume discounts on request. Payment in USDT, USDC, BTC, ETH, SOL, TON or your project token.

How it works

1. Scope the reviewShare priority pages, audiences and business questions. We agree what is included and which public examples to inspect.
2. Gather evidenceProvide relevant author, product and policy information. We note which items are public and which require client confirmation.
3. Review pages and answersWe assess visible evidence, sample agreed searches and record findings in the Run Log.
4. Prioritize actionsThe findings are grouped by issue and owner, with evidence or clarification needed for each recommendation.
5. Walk through the ReadoutWe review priorities and open questions with your team so the next workstream is clear.