E-E-A-T and trust audit for AI search and Google

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

An E-E-A-T and trust audit checks whether people and search systems can understand who is responsible for your content, what supports its claims and why the source is relevant. It turns broad trust concerns into specific evidence and page-level actions.

We review representative pages, brand information and the proof you make available. For each important claim, we ask: Is the author or organization identifiable? Is relevant experience or expertise shown rather than merely asserted? Can a reader find supporting sources, policies, contact details and a clear explanation of the service? Are the same facts presented consistently across the site?

The review can include:

• Author, reviewer and company profiles, including relevant credentials or first-hand work.
• Evidence behind product, financial, security or performance claims.
• Editorial standards, corrections, disclosures, contact information and policies.
• Alignment between your website, public profiles and the entities associated with your brand.
• Whether important pages answer the questions your audience actually brings to search.

We distinguish missing evidence from evidence that exists but is difficult to find. This matters: adding a new page is not always the right fix. Sometimes a clearer author profile, source citation or consistent company description resolves the underlying issue. For entity-level work, see entity and knowledge graph building.

How do Google and AI systems use trust evidence?

A useful audit separates the trust evidence you control from the selection and presentation decisions made by search and AI platforms. Google and answer systems can surface information from different pages and sources, so a strong website profile alone does not tell the whole story.

We inspect the pages most relevant to your buyers and note whether they expose clear, attributable information in a form people can check. That includes identifying authors and subject-matter contributors, linking claims to credible supporting material, keeping important details current, and making the organization’s purpose and contact routes easy to find. We also look for conflicts: a product description, founder biography or company name that changes across important sources can make the overall picture harder to interpret.

For an AI-focused review, we test a scoped set of relevant buyer questions and record whether answers show your brand, what sources appear, and whether those sources support the answer. This is a diagnostic sample, not a claim that every user will receive the same result. For a platform-specific view, explore Perplexity optimization and Google AI Overviews optimization.

The practical output is a map from observed issue to action. For example: clarify the author’s role, add evidence to a claim, improve internal navigation to a policy, or resolve inconsistent company descriptions. We prioritize changes by relevance to audience decisions and by how directly the current evidence supports them.

What evidence and deliverables will your team receive?

You receive an audit your team can act on: findings tied to specific pages or brand evidence, a reason for each recommendation, and a practical order for addressing the work. The report is designed to help marketing, content, product and leadership teams agree on what to fix first.

Before review begins, we align on your audience, priority services, target markets and the claims that matter most to buyer decisions. You can share relevant page URLs, author details, editorial materials, product documentation, research, certifications and public profiles. We assess the evidence you provide alongside what is visible on the agreed public surfaces; we do not treat an unsupported claim as proof simply because it appears in a brief.

Deliverables are scoped to the project and can include:

• A findings report with examples of strong, missing or inconsistent trust evidence.
• A prioritized action list for content, site structure, brand information and supporting proof.
• Guidance on author and organization presentation, claim sourcing and content ownership.
• A review of technical or structured-data questions that affect discoverability, with implementation needs identified separately.
• A handoff discussion so owners understand the reasoning behind recommendations.

Where the audit reveals a broader need, we can map the next workstream to content for AI answers, technical AEO or a wider GEO audit. The recommendations remain grounded in your actual pages and evidence, not a generic checklist presented as a score.

How does the E-E-A-T audit run from kickoff to handoff?

The audit runs as a focused review: agree the business questions, inspect evidence, validate findings and hand over a prioritized plan. We confirm the scope and project timing with you before work starts, based on the materials and access needed.

First, we define which brand, site areas, audiences and search surfaces belong in the review. This keeps the work relevant and makes clear what has not been assessed. Next, we collect the page list and supporting materials, then examine how experience, expertise, authority and trust are presented. We record examples rather than relying on vague labels such as “low trust.”

During analysis, we compare key claims with their visible support, review author and organization context, and look for gaps or inconsistencies that could confuse a prospective buyer. If the AI visibility review is in scope, we also agree the question set and capture observations with the date and context of the check. We then rank recommendations by buyer relevance, evidence impact and implementation ownership.

At handoff, we walk through the findings, answer questions and clarify which actions are editorial, technical or dependent on new proof from your team. If you need ongoing observation after fixes, AI visibility monitoring can help your team track how the sampled results change over time. The audit itself is a defined project; any implementation or continued monitoring is separately scoped.

What can’t an E-E-A-T audit promise?

An audit can verify and improve the clarity of your evidence; it cannot control how Google or an AI platform selects, ranks, cites or summarizes sources. Those systems change, may retrieve different material for different queries, and make their own decisions about what to show. A citation or visibility result observed during an audit is a snapshot, not a commitment about future answers.

We will not present E-E-A-T as a score that can be switched on, or claim that a particular file, markup change or author page guarantees inclusion. Nor can we create first-hand experience, qualifications, independent recognition or substantiation on your behalf. When a recommendation requires proof your organization does not yet have, we will identify the gap and state what kind of evidence would make the claim more credible.

Before approving the work, use this checklist:

• Confirm the pages, brand properties and AI surfaces included in scope.
• Gather the source material behind important product and company claims.
• Identify internal owners who can verify credentials, policies and factual details.
• Separate recommendations that can be implemented now from those requiring new evidence.
• Treat AI answer checks as observations, not a promise of a stable placement.

We commit to delivering the agreed review, documented findings and recommendations. We do not promise a Google ranking, a particular Perplexity citation or a permanent AI answer position. This distinction keeps the audit useful: it focuses the team on transparent proof and improvements it can actually control.

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. Define the scopeChoose the brand, audience, priority pages and search surfaces. We confirm what the project will and will not assess.
2. Share the evidenceProvide page URLs and available author, company, product and editorial materials. We identify any important evidence that is missing.
3. Review pages and signalsWe examine clarity, attribution, substantiation and consistency, then record concrete examples tied to the agreed scope.
4. Prioritize the actionsFindings are organized into practical next steps with a reason and a likely owner, so your team can plan implementation.
5. Discuss the handoffWe walk through the report, answer questions and distinguish audit recommendations from separately scoped implementation.