Access and retrieval
Can search engines and relevant AI systems reach, crawl, index, and retrieve the pages that explain the business?
Our evaluation framework
How we evaluate AI visibility
We evaluate whether a business is accessible, understandable, verifiable, relevant, and sufficiently supported to be considered when AI platforms form answers and recommendations.
The principles
AI visibility is evaluated as a connected system
No single page, schema property, review, citation, or prompt determines whether a business will appear. We look at how the full set of available signals works together.
Entity clarity
Are the business name, category, people, services, locations, and relationships represented clearly and consistently?
Relevance and coverage
Does the website answer the questions buyers ask and explain when the business is an appropriate choice?
Trust and evidence
Do experience, reviews, credentials, case studies, policies, and service details support the claims being made?
External corroboration
Can important facts be confirmed through credible third-party mentions, profiles, citations, and other independent sources?
Recommendation readiness
When alternatives are compared, is there enough specific and consistent evidence to make the business a defensible answer?
The client-facing process
From visibility questions to prioritized decisions
The purpose of the evaluation is not to produce a long list of disconnected technical findings. It is to identify what is most likely to improve clarity, trust, and qualified visibility.
Our work connects strategic SEO, content, technical access, structured information, website authority, third-party proof, and competitive context.
- 1
Define the business and buyer context
We establish the services, audiences, locations, competitors, and recommendation questions that matter.
- 2
Examine the available evidence
We review what a search engine, AI platform, or prospective buyer can access and verify across the website and supporting sources.
- 3
Identify clarity and confidence gaps
We look for missing, inconsistent, unsupported, or difficult-to-retrieve information that may weaken recommendation confidence.
- 4
Prioritize the work
Recommendations are organized by likely business impact, dependency, effort, and the order in which improvements should be made.
What the evaluation produces
A practical view of what should be strengthened first
The output is designed to support decisions, not create false precision.
Depending on the engagement, findings may include access problems, unclear entity signals, weak service coverage, unsupported claims, missing trust evidence, inconsistent third-party information, or competitors with clearer proof.
What clients can expect
- A clear explanation of the most important visibility gaps
- Evidence showing why each issue matters
- Priorities organized around likely impact and sequence
- Connections between AI visibility, SEO, authority, and conversion
- Recommended next steps appropriate to the business
Important boundaries
What this methodology does—and does not—claim
AI platforms use different systems, sources, retrieval methods, and proprietary processes. Results can change by prompt, location, timing, available evidence, and platform updates.
No legitimate provider can guarantee that a particular AI platform will recommend a business. Our methodology is intended to improve the quality, clarity, consistency, and support behind the signals available to those systems.
For a deeper explanation, read how AI decides which businesses to recommend.
To understand the grading system, review the AI Visibility Score Benchmarks.
Start with evidence
See where your AI visibility may be breaking down
Use the free checker for an initial view, or book a focused review to examine the signals, competitive gaps, and priorities behind the result.