01
Where your brand appears
Presence across the agreed prompt set and selected engines.
Audit methodology
A structured methodology for AI Visibility analysis
AI answers change across engines, prompts, contexts and time. Our methodology turns that variability into a clear snapshot of brand visibility, competitor presence, cited sources and priority actions.
Structured prompt testing
Multi-engine analysis
Competitor comparison
Source and citation review
No ranking guarantees
Method overview
What the methodology is designed to measure
The method connects individual AI answers to a consistent set of visibility, competitive and source questions.
02
Which competitors are recommended
Brands named in recommendation, comparison and category answers.
03
Which AI engines mention you
Platform-level visibility patterns and material differences.
04
Which sources are cited
Websites, directories, reviews and references supporting answers.
05
Which prompts you win or lose
Questions where your brand is present, absent or less prominent.
06
Which visibility signals need work
Content, source, reputation and consistency gaps worth prioritizing.
Six stages
The audit process
Each stage produces a documented output, from the initial scope through to the final roadmap.
01Method 1
Scope definition
We define the company, market, location, competitors, offers and priority customer questions.
Method output
Documented audit scope
02Method 2
Prompt set creation
We create structured prompts that reflect discovery, comparison, recommendation, trust and local intent.
Method output
Intent-based prompt framework
03Method 3
Multi-engine testing
We test selected prompts across selected AI engines such as ChatGPT, Perplexity, Gemini, Google AI, Copilot and Claude.
Method output
Comparable engine results
04Method 4
Response capture
We record brand mentions, competitor mentions, cited sources, answer patterns, positioning and visible opportunities.
Method output
Structured evidence set
05Method 5
Scoring and interpretation
We calculate a proprietary score and interpret results by platform, prompt type, competitor presence and source influence.
Method output
Score and visibility diagnosis
06Method 6
Recommendations and roadmap
We prioritize actions for content, website clarity, third-party sources, local profiles and monitoring.
Method output
Business-ready action roadmap
Prompt design
Prompt categories we test
Prompts are grouped by intent so the audit reflects how prospects actually ask AI engines for answers.
01Intent
Discovery prompts
“Best providers for [service] in [city]”
02Intent
Comparison prompts
“Compare [brand] vs [competitor]”
03Intent
Recommendation prompts
“Which company should I choose for [need]?”
04Intent
Trust prompts
“Is [brand] reliable?”
05Intent
Local prompts
“Best [service] near me”
06Intent
Category prompts
“Top companies for [category]”
07Intent
Problem-solution prompts
“How to solve [problem]?”
08Intent
Pricing/value prompts
“How much does [service] cost?”
Response evidence
What data is captured
The report records enough context to make each result traceable and interpretable.
Captured fields are interpreted within the documented date, prompt, platform and competitor scope. Missing data is recorded as a limitation rather than inferred.
| Captured field | How it supports interpretation | Status |
|---|---|---|
| Prompt | The exact question tested. | Recorded |
| AI engine | The platform where the answer was generated. | Recorded |
| Date and scope | When and under which defined conditions the test ran. | Recorded |
| Brand mentioned | Whether the audited brand appears in the answer. | Recorded |
| Brand position in answer | The relative prominence and context of the mention. | Recorded |
| Competitors mentioned | Which named competitors appear and how they are framed. | Recorded |
| Sources cited | The domains or pages referenced in the answer. | Recorded |
| Website cited | Whether the audited website is used as a source. | Recorded |
| Answer sentiment / framing | How the answer describes the brand, offer or category. | Recorded |
| Opportunity level | The materiality of the observed visibility gap. | Recorded |
| Notes and limitations | Context required to interpret the result responsibly. | Recorded |
Scroll horizontally to review the complete capture framework.
AI Visibility Score
How the AI Visibility Score works
The AI Visibility Score is a proprietary decision-support indicator. It is not an official AI engine metric. It helps compare visibility across prompts, platforms and competitors within a defined audit scope.
Weighted model
Eight signals · 100% total weight
Brand presence25%
Frequency and relevance of brand mentions.
Website / source citation15%
Whether brand-connected sources support answers.
Competitive share of voice15%
Visibility relative to named competitors.
Position and prominence10%
How clearly and prominently the brand appears.
Platform coverage10%
Consistency across the selected AI engines.
Source authority10%
Strength of the sources connected to the brand.
Brand consistency10%
Alignment of descriptions across prompts and platforms.
Technical and content clarity5%
Clarity of relevant website and content signals.
Score interpretation
0–39Weak visibility
40–59Partial visibility
60–79Strong but fragile visibility
80–100High visibility
Interpret the score with the underlying prompt, platform, competitor and source evidence.
Competitive and source context
Why competitors and sources matter
AI-generated answers are shaped not only by your website, but also by third-party sources, directories, articles, reviews, comparison pages, local profiles and broader brand signals.
Competitor analysis
Where other brands win
- Which competitors appear more often
- Which prompts they win
- Which engines recommend them
- What sources support them
- Where your brand is missing
Source analysis
What supports the answers
- Which domains are cited
- Whether your website is cited
- Which third-party profiles are missing
- Which source gaps can be improved
- Which pages should be strengthened
Prioritization
How recommendations are prioritized
Recommendations are ranked by business impact, feasibility and visibility relevance.
01
Impact: HighEffort: Low
High impact / low effort
Clear improvements that can be implemented quickly.
02
Impact: HighEffort: Medium
High impact / medium effort
Material opportunities requiring focused execution.
03
Impact: HighEffort: Medium
Strategic content opportunities
Missing pages or evidence for important buyer prompts.
04
Impact: MediumEffort: Medium
Third-party source opportunities
External profiles and references that support competitor answers.
05
Impact: MediumEffort: Low
Local and reputation improvements
Location, listing and review signals relevant to the scope.
06
Impact: OngoingEffort: Low
Monitoring recommendations
Prompts and signals worth tracking after the baseline audit.
Limitations and variability
Why AI answers can vary
AI-generated answers can change depending on platform, model version, prompt phrasing, user context, location, timing, interface and available sources. This is why the audit is presented as a repeatable snapshot, not an official ranking.
01i
Different engines use different source logic
Platforms retrieve, synthesize and cite information differently.
02i
Prompt wording can change answers
Small phrasing changes can alter intent, emphasis and named brands.
03i
Models and interfaces update over time
Provider updates can change answer behavior and available features.
04i
Location and context may influence results
Geography, user context and conversation history can affect an answer.
05i
Citations are not always available
Some interfaces expose sources while others provide uncited summaries.
06i
Repeated testing improves confidence
Repetition reveals patterns but cannot remove answer variability.
Clear boundaries
What we do not claim
Credible analysis requires explicit limits. These boundaries are part of the methodology, not footnotes.
×We do not guarantee AI mentions.
×We do not guarantee fixed positions.
×We do not claim to control AI engines.
×We do not sell fake citations or fake reviews.
×We do not treat the score as an official metric.
×We do not replace SEO; we extend visibility analysis into AI search behavior.
AI Visibility and GEO analyses are based on tests performed at a specific date within a defined scope of prompts, platforms and competitors. Results may vary depending on users, contexts, models, interfaces and AI engine updates. The score is a proprietary decision-support indicator, not an official metric. Recommended actions are designed to strengthen visibility and credibility signals, without any guarantee of appearance, citation or ranking in AI-generated answers.
Decision support
What teams can decide from the analysis
The method is designed to support business priorities, not produce a score without context.
01
Which prompts deserve attention first
02
Which competitors are influencing AI answers
03
Which sources need to be strengthened
04
Which pages should be improved
05
Which content gaps matter
06
Whether monthly monitoring is useful
07
Whether local or reputation signals need work
08
What to prioritize over the next 30 days
Methodology FAQ
Questions about the method
No. It is a proprietary decision-support indicator used to compare visibility within a defined audit scope.
Use a structured method to understand your AI visibility
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