Find out how visible your company is to AI-powered research and buying tools.
25 questions across five dimensions of your AI visibility. Free. Takes around 10 minutes. Results appear on screen immediately and are sent to your inbox.
AI Discoverability
Accuracy of Description
Category Presence
Authority Signals
Structural Legibility
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How easily AI tools can find and surface your company when buyers ask relevant questions. Discoverability depends on how well your presence is distributed across the sources AI tools draw from.
1. How consistently does your company appear when you ask AI tools to recommend providers in your category?
Consider: try prompting ChatGPT, Perplexity, or Claude with a buyer question relevant to your offering.
Not at all. We do not appear in AI-generated recommendations for our category.
Rarely. We appear occasionally but not consistently or prominently.
Sometimes. We appear in some AI responses but not reliably across tools or query types.
Consistently. We appear reliably when buyers ask AI tools about our category or problem area.
2. How well is your company represented across the third-party sources AI tools draw from?
Poorly. We have minimal presence on the platforms AI tools use as source material.
Partially. We appear on some relevant platforms but coverage is incomplete.
Well. We have meaningful presence on most of the key third-party sources AI tools reference.
Comprehensively. We have strong, consistent coverage across the full range of sources AI tools draw from.
3. How clearly does your public web presence signal the category and problem you solve?
Consider: homepage, About page, and service pages. Can an AI tool understand what you do and who you serve within the first paragraph?
Unclear. Our web presence uses vague language that does not clearly state our category or the problem we solve.
Partial. Our category is implied but not stated explicitly enough for AI tools to classify us reliably.
Clear. Our web presence clearly states what we do, who we serve, and the problem we solve.
Optimised. Our category, problem statement, and buyer profile are explicit, repeated across key pages, and structured for AI parsing.
4. How active and visible is your company in the online conversations buyers use AI to research?
Consider: industry publications, thought leadership content, podcast appearances, forum contributions.
Absent. We do not actively participate in the conversations buyers research when evaluating our category.
Minimal. We have some content presence but it is not consistent or focused enough to build discoverability.
Active. We produce regular content that addresses the questions buyers ask when researching our category.
Prominent. We are consistently present in the content ecosystem buyers and AI tools draw on to evaluate our category.
5. How well does your website structure support AI crawling and content extraction?
Consider: structured data markup, clear heading hierarchy, crawlable text (not hidden in images or PDFs), logical page structure.
Not optimised. Our site has no structured data, inconsistent headings, and content that is difficult for AI tools to parse.
Partially optimised. Basic structure is in place but structured data is missing or incomplete.
Well optimised. Our site uses structured data, clear headings, and crawlable text across key pages.
Fully optimised. Comprehensive structured data, semantic markup, and AI-readable content across the entire site.
Dimension 02 of 05
Accuracy of Description
How accurately AI tools describe your company, offer, and positioning when they surface you to buyers. Inaccurate AI descriptions create friction at the moment of consideration.
6. How accurately do AI tools describe what your company does when asked directly?
Consider: prompt an AI tool with "What does [your company name] do?" and evaluate the response.
Inaccurately. AI tools describe us incorrectly, use outdated information, or confuse us with another company.
Partially. AI tools get the general category right but miss important details about our specific offer or positioning.
Mostly accurately. AI tools describe us correctly in most material respects with minor gaps or imprecision.
Accurately. AI tools describe our offer, positioning, and differentiation correctly and consistently.
7. How consistently does your company describe itself across all public channels?
Consider: website, LinkedIn, press releases, directory listings, partner pages. AI tools aggregate these sources to form a description.
Inconsistently. Our description varies significantly across channels, giving AI tools conflicting signals.
Variably. Core details are the same but language, positioning, and emphasis differ across channels.
Mostly consistently. Descriptions are broadly aligned with minor variation across channels.
Consistently. We use precisely aligned language across all public channels, giving AI tools a single coherent signal.
8. How clearly do you articulate your differentiation in language AI tools can extract and repeat?
Consider: is your differentiation expressed in specific, concrete claims rather than vague superlatives?
Not clearly. Our differentiation is expressed in generic language that AI tools cannot distinguish from competitors.
Partially. We have differentiation claims but they are buried, vague, or not repeated consistently enough to register.
Clearly. Our differentiation is stated in specific, concrete language across key pages and channels.
Precisely. Differentiation is expressed in clear, specific, repeatable language and reinforced across every public touchpoint.
9. How well does your public content reflect your current offer and positioning?
Consider: outdated content trains AI tools on old positioning. Is your oldest indexed content still accurate?
Poorly. Significant amounts of our indexed content reflect outdated offers, old positioning, or discontinued services.
Partially. Most content is current but some outdated material remains indexed and accessible.
Well. The majority of our indexed content reflects our current offer and positioning accurately.
Fully. All indexed content is current, accurate, and reviewed regularly to ensure AI tools draw from up-to-date material.
10. How precisely does your content define the buyer you serve and the outcomes you deliver?
Consider: AI tools match companies to buyer queries. Specific buyer and outcome language improves match accuracy.
Not precisely. We use broad language about customers that does not help AI tools match us to specific buyer queries.
Partially. We describe our buyer type but outcomes and use cases are not specific enough for AI matching.
Precisely. Buyer profile, use cases, and outcomes are stated clearly across our key content.
Comprehensively. Buyer profile, industry, use cases, outcomes, and differentiation are all explicitly defined and consistently expressed.
Dimension 03 of 05
Category Presence
How strongly your company is associated with the categories and problems buyers research. Category presence determines whether AI tools include you when a buyer describes a problem rather than a company name.
11. How clearly does your company own a specific category or problem in the minds of AI tools?
Consider: when AI tools answer "who solves [your problem]?" do they include you reliably?
Not at all. AI tools do not associate us with any specific category or problem.
Weakly. There is a loose association but it is not consistent or strong enough to drive reliable inclusion.
Clearly. AI tools associate us with our primary category and surface us when buyers describe related problems.
Strongly. We are clearly and consistently associated with our category across AI tools, with strong presence in problem-based queries.
12. How well does your content address the specific questions buyers ask when researching your category?
Consider: are you answering the questions that appear in AI overviews and featured snippets in your space?
Poorly. Our content does not directly address the questions buyers ask when researching our category.
Partially. We address some buyer questions but significant gaps remain in our category content coverage.
Well. Our content addresses most of the key questions buyers ask when researching our category.
Comprehensively. We have authoritative content covering the full range of questions buyers ask across all stages of category research.
13. How well are you represented in category-defining content produced by third parties?
Consider: analyst reports, comparison articles, industry guides, "best of" lists, media coverage in your category.
Not represented. We do not appear in third-party category content that AI tools draw from.
Minimally represented. We appear in some category content but not in the primary sources AI tools reference.
Well represented. We appear in most significant third-party sources that define our category.
Prominently represented. We are featured in the leading category-defining sources AI tools prioritise, often as a primary reference.
14. How consistently do you use the exact category language buyers and AI tools recognise?
Consider: if buyers search "revenue growth advisory" and you call yourself a "commercial performance firm," AI tools may not make the connection.
Inconsistently. We use proprietary or non-standard language that does not map to how buyers describe our category.
Partially. We use some category-standard language but our terminology does not consistently match buyer and AI vocabulary.
Consistently. Our language maps clearly to the category terms buyers and AI tools use.
Precisely aligned. We use exact category language throughout, with deliberate alignment to how buyers describe the problem and how AI tools categorise solutions.
15. How well do you address adjacent categories and use cases that buyers might research on the way to your offer?
Consider: buyers often start with a broader problem before narrowing to a specific category. Are you present at the earlier stages of that journey?
Not at all. Our content is focused narrowly on our core category with no coverage of adjacent problems or use cases.
Minimally. We address adjacent topics occasionally but without a deliberate strategy for early-stage buyer presence.
Well. We have meaningful content presence across the adjacent problems buyers research before arriving at our category.
Comprehensively. We have a deliberate content strategy covering the full buyer research journey from early-stage problem awareness to category-specific evaluation.
Dimension 04 of 05
Authority Signals
How strongly your company is associated with credibility, expertise, and trust in the sources AI tools use. AI tools weight companies with stronger authority signals more heavily in recommendations.
16. How strong is your external validation from clients, analysts, and third-party sources?
Consider: case studies, testimonials, awards, analyst mentions, media coverage, review platform ratings.
Weak. We have minimal external validation that AI tools can draw on to assess our credibility.
Partial. Some external validation exists but it is not prominent, specific, or consistently distributed across sources.
Strong. We have meaningful external validation across multiple credible sources that AI tools draw from.
Comprehensive. We have strong, consistent external validation across case studies, reviews, media coverage, and analyst references.
17. How consistently do you produce and distribute original thought leadership in your category?
Consider: articles, frameworks, research, point-of-view content. Original thinking cited by others is a strong AI authority signal.
Not at all. We do not produce original thought leadership content in our category.
Occasionally. We produce some thought leadership but without consistency or a deliberate distribution strategy.
Regularly. We produce and distribute original content consistently and it is being referenced by others in the category.
Systematically. We have a deliberate thought leadership programme that produces original content, earns citations, and builds measurable authority in our category.
18. How well-established is your founder or leadership team as a credible voice in your category?
Consider: personal brand signals from founders and senior leaders are aggregated by AI tools as company authority indicators.
Not established. Our leadership team has minimal or no public presence in the category.
Emerging. Some leadership presence exists but is not yet consistent or prominent enough to register as an authority signal.
Established. Our founders or leaders are recognised voices in the category with consistent public presence.
Well established. Leadership team members are prominent, cited authorities in the category with strong cross-platform presence.
19. How well does your site reflect expertise signals that AI tools recognise?
Poorly. Our site lacks the expertise signals AI tools use to assess credibility: no author attribution, credentials, or original research.
Partially. Some expertise signals are present but they are not consistent or prominent across key content.
Well. Key expertise signals are present and visible across our most important content.
Comprehensively. Author attribution, credentials, methodology, and expertise signals are embedded throughout our content in a way AI tools can parse.
20. How often is your company cited, linked, or referenced by credible third parties in your category?
Consider: inbound links from industry sources, citations in other content, mentions in category-relevant publications.
Rarely. We receive minimal external citations or references from credible third-party sources.
Occasionally. We receive some external references but not consistently or from the most credible sources in our category.
Regularly. We receive consistent external citations from relevant and credible sources in our category.
Frequently. We are regularly cited by leading sources in our category and have a growing base of external references AI tools can draw from.
Dimension 05 of 05
Structural Legibility
How easy it is for AI tools to read, interpret, and accurately represent your company from your website and public content. Structural legibility is the technical foundation that determines whether everything else gets used.
21. How well structured is your website for machine reading and AI content extraction?
Consider: logical heading hierarchy (H1, H2, H3), semantic HTML, clear paragraph structure, no content locked in images or JavaScript.
Poorly structured. Inconsistent headings, content in non-crawlable formats, and no semantic HTML structure.
Partially structured. Basic structure exists but headings are inconsistent and some key content is not machine-readable.
Well structured. Clear heading hierarchy, semantic HTML, and machine-readable content across most key pages.
22. How completely have you implemented structured data markup on your site?
Consider: Schema.org markup for Organization, WebPage, FAQPage, Article, BreadcrumbList. Structured data makes your content directly parseable by AI tools.
Not implemented. We have no structured data markup on our site.
Minimally implemented. Basic structured data on some pages but coverage is incomplete.
Well implemented. Core structured data types are implemented across our main pages.
Comprehensively implemented. Full structured data coverage across all key page types with Organisation, FAQ, Article, and BreadcrumbList markup validated and current.
23. How clearly does each key page of your site communicate a single, specific topic?
Consider: pages that try to cover too many topics give AI tools mixed signals. Each page should have a clear, singular focus.
Poorly. Most pages cover multiple topics and do not have a clear primary focus AI tools can extract.
Partially. Some pages are focused but many mix topics in ways that reduce AI legibility.
Well. Most key pages have a clear singular focus with supporting content that reinforces rather than dilutes the primary topic.
Precisely. Every key page is built around a single, clear topic with content structure that maximises AI extraction accuracy.
24. How well does your meta content (titles, descriptions, Open Graph) accurately reflect page content?
Consider: AI tools use meta content as a strong signal for what a page is about. Mismatched or missing meta content creates confusion.
Poorly. Meta titles and descriptions are missing, duplicated, or do not accurately reflect page content.
Partially. Meta content is present on most pages but accuracy and alignment with page content is inconsistent.
Well. Meta content is accurate, unique, and aligned with page content across most key pages.
Precisely. Every page has unique, accurate meta content that precisely reflects the page topic and buyer intent it addresses.
25. How well does your content directly answer the questions buyers ask rather than describing your company in marketing language?
Consider: AI tools prefer content that answers questions directly. Marketing language ("we are the leading...") is less useful to AI than factual, specific statements.
Mostly marketing language. Our content is primarily brand-focused and does not directly answer buyer questions.
Mixed. Some content answers questions directly but most pages are still written in marketing voice.
Mostly question-answering. Most key content is written to directly address buyer questions in specific, extractable language.
Question-first throughout. Our content is systematically structured to answer buyer questions directly, with specific, factual language AI tools can extract and cite.
FCP AI Visibility Diagnostic · Full Court Press Pte. Ltd.
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