AI Visibility Audit

See where your business appears in AI recommendations.

We test realistic buyer-intent questions, measure whether and where your company appears, compare that visibility with businesses being recommended, and investigate the public evidence that may be contributing to stronger visibility.

Request an AI Visibility Audit See how the process works

Questions buyers ask

Useful answers before an audit begins.

These questions frame what can be observed, what remains unknown, and what a disciplined analysis can test.

Why does ChatGPT recommend our competitors but not us?

There usually isn't one simple reason. AI recommendations can reflect what an AI system can find, understand, corroborate, and associate with a buyer's specific question. A company can have a strong website, good traditional search visibility, and an established reputation while still being absent from AI-generated consideration sets.

The useful question isn't simply, “Why aren't we ranking?”

Company-specific next question

What observable evidence distinguishes the companies AI recommends from us for the questions our buyers actually ask?

AI Insights 716 analysis

AI Insights 716 tests representative buyer questions, documents which companies are recommended, and compares their observable evidence environments against the target company.

Relevant product path

AI Visibility Audit

See What the Audit Examines

How can we find out why our company isn't showing up in AI recommendations?

Start with the questions real buyers are likely to ask rather than searching for the company by name.

Establish a baseline across those buyer questions, identify which companies AI systems recommend instead, and compare the observable evidence associated with those companies across their websites and relevant independent sources. Repeated differences can produce testable explanations for the visibility gap.

Company-specific next question

What baseline, competitors, sources, and evidence must be preserved so later results can be compared with the starting point?

AI Insights 716 analysis

A meaningful analysis requires more than asking an AI system once. AI Insights 716 preserves the buyer questions, baseline observations, competitors, sources, evidence, and subsequent changes.

Relevant product path

AI Visibility Baseline → AI Visibility Audit

Evaluate Our AI Visibility

Can we improve how often AI recommends our company—and actually measure whether it's working?

Potentially, but no legitimate analysis can guarantee that an AI system will recommend a particular company.

What can be done is establish a controlled baseline, identify evidence differences associated with stronger visibility, make targeted changes based on testable hypotheses, and measure whether recommendation frequency, inclusion, or position changes afterward.

Company-specific next question

Which controlled change should be tested first, and what result would support, weaken, or disprove the hypothesis?

AI Insights 716 analysis

This creates a measurable process rather than a promise of AI rankings. Ongoing monitoring may follow where appropriate, but it is not presented here as a currently available product.

Relevant product path

Baseline → Audit → Controlled Intervention → Measurement

Start With an AI Visibility Audit

Because proprietary AI ranking and recommendation systems are not fully observable, findings are classified as known, calculated, inferred, unknown, or company confirmation required—not presented as knowledge of a hidden algorithm.

What we measure

A structured view of an uncertain system.

AI recommendations can vary by wording, context, and time. The audit captures observable patterns without treating them as permanent or deterministic rankings.

Recommendation visibility: Whether your business appears in response to relevant buyer-intent questions.
Position observations: Where your business appears among recommended companies, when a meaningful order is present.
Prompt consistency: How visibility varies across multiple questions that express related commercial needs.
Competitor visibility: Which businesses are surfaced repeatedly, and in which decision contexts.
Evidence patterns: The public sources and signals surrounding companies that receive stronger visibility.
Visibility gaps: Material differences between your business and the companies AI systems choose to surface.

The buyer-prompt approach

Test the questions buyers actually ask.

Prompts are selected to reflect real commercial intent—not vanity queries. We summarize the question set used, while keeping internal testing protocols and proprietary prompt sets private.

Representative question patterns

“Which companies should I consider for…”
“Who are the best providers of…”
“What are the best options for…”

Competitive diagnostic

The analysis does not stop at absence.

When a business is absent or underrepresented, we compare it with the companies AI systems are recommending and examine the public evidence around those results.

These factors may contribute to recommendation behavior. They are diagnostic evidence—not a universal ranking formula.

01Website content
02Product and service specificity
03Question-relevant evidence
04Independent references
05Reviews and trust signals, where appropriate
06Brand and entity clarity
07Public authority and supporting evidence

What your business receives

A concrete record of findings and next steps.

Each deliverable is designed to make the current state visible and support measured decisions. They are findings and recommendations—not guaranteed outcomes.

01AI visibility baseline
02Tested buyer-intent question set summary
03Recommendation and position observations
04Identified competing companies
05Competitor evidence comparison
06Visibility gaps and opportunities
07Prioritized recommendations for controlled changes
08Measurement plan for re-testing

The method

Measure. Diagnose. Intervene. Measure again.

Positive, negative, and null results all provide useful information. Each result narrows the next question and supports a more disciplined decision.

01
Measure
Establish the current visibility baseline across a focused set of relevant questions.
02
Diagnose
Determine where the company differs from businesses being surfaced.
03
Intervene
Recommend focused, evidence-based changes that can be evaluated.
04
Measure again
Re-test to determine whether visibility changed and what the result teaches us.

What this is not

Clear boundaries make the work more useful.

Not a guarantee of ai rankings
Not manipulation of ai systems
Not a generic seo checklist
Not a list of invented “ai ranking factors”
Not a promise that every intervention will improve visibility

Request an audit

Find out what AI sees when buyers look for a company like yours.

Request an AI Visibility Audit