What Questions to Ask AI to Find Out If Your Brand Is Being Cited

Your brand can rank on page one of Google and still be completely absent when a prospect asks ChatGPT, "What are the best [category] platforms for a B2B SaaS company?" That absence is not a rankings problem – it is a visibility problem in a different system entirely. Asking AI platforms direct, structured questions is the fastest way to audit where your brand stands, which queries surface your competitors instead of you, and what gaps in your content or authority are responsible.

AI brand citation is the inclusion of a company's name, product, or content in a response generated by an AI system such as ChatGPT, Claude, Gemini, or Perplexity – appearing as a named source, a description, or a recommendation rather than as a ranked link in traditional search results.

Step 1: Define Target Queries and Use Cases

Before opening any AI platform, build your prompt list on paper. The quality of the questions you ask determines how useful your audit results are.

Organize prompts into four categories that reflect how buyers actually research a purchase:

Category discovery prompts ask which tools, platforms, or providers serve a specific buyer type. Evaluation criteria prompts ask what buyers should look for when assessing vendors in your space. Competitor alternative prompts surface which brands AI recommends when a buyer is evaluating your direct competitors. Use-case fit prompts describe a specific scenario and ask which brand is the right fit.

Aim for 20–30 prompts total across these four types. Use buyer language, not internal jargon. If your customers say "marketing automation," use that phrase – not "demand generation orchestration" or whatever your product team calls it.

Category Discovery Prompts

These reveal whether AI systems place your brand in the relevant consideration set at all.

Examples:

• "What are the best [category] platforms for [your buyer profile]?"
• "Which [category] tools do B2B SaaS companies under 500 employees use?"
• "What are the top [category] solutions for [industry vertical]?"

Evaluation Criteria Prompts

These show whether AI associates your brand with expertise and thought leadership on buyer decision criteria.

Examples:

• "What should I look for in a [category] vendor?"
• "What are the most important features in a [category] platform?"
• "How do I evaluate [category] providers for enterprise use?"

Competitor Alternative Prompts

These are strategically critical. If a buyer is dissatisfied with your competitor and asks AI for alternatives, does your brand appear?

Examples:

• "Alternatives to [Competitor A]"
• "[Competitor A] vs [Competitor B] – which is better for [use case]?"
• "What are the best [Competitor A] alternatives for [buyer profile]?"

Use-Case Fit Prompts

These test whether AI can specifically recommend your brand for the scenarios you serve best.

Examples:

• "I run a 200-person B2B SaaS company. Which [category] platform should I use?"
• "Best [category] tool for a company with [specific constraint or requirement]"
• "What [category] solution works best for [industry] with [specific pain point]?"

Step 2: Run Prompts Across All Four AI Platforms

Open four sessions – ChatGPT, Claude, Perplexity, and Google AI Overviews and run every prompt in your list across all four. Do not test on one platform and assume results generalize. Citation behavior varies significantly between systems.

Each AI platform draws from different training data, applies different retrieval logic, and weights authority signals differently. A brand that appears prominently in Perplexity may be completely absent from Claude's responses for the same query.

Run prompts in a clean session without prior conversation context that could bias responses. Log every result immediately. Do not rely on memory.

What to Document for Each Response

For each prompt-and-platform combination, record:

Field	What to Log
Platform	ChatGPT / Claude / Perplexity / Google AI
Prompt used	Exact text of the query
Date	Session date
Was brand mentioned?	Yes / No
Citation type	Not mentioned / Listed / Described / Recommended
Competitors mentioned	Names of any competitors cited instead
Source links (if shown)	URLs cited in the response
Screenshot	Captured for future comparison

Perplexity includes numbered citations with links to original sources. ChatGPT Search includes links when search mode is active. Google AI Overviews surface eligible content from indexed pages. Capture this source data – it tells you which pages on your site (or competitor sites) are actually being cited.

Step 3: Score Each Response

Raw notes are not enough. Apply a consistent scoring system so results are comparable across platforms, prompts, and time periods.

Use this four-point scale for each response:

Score	Citation Level	What It Means
0	Not mentioned	Your brand does not appear in the response
1	Awareness	Brand is named in a list with no description
2	Solution description	Brand is named and described – what it does, who it serves
3	Trust / recommendation	Brand is recommended for a specific buyer type or use case

Score every prompt-platform pair. Your maximum possible raw score is: [number of prompts] × 4 platforms × 3 points per response.

Divide your total score by the maximum possible score and express as a percentage. This is your baseline AI visibility score.

Most B2B brands score 8–15% at baseline. Brands with active content programs but no GEO work typically land between 18–22%. Brands at Level 2 citation (described with what they do) average 40–60%. Reaching Level 3 – where AI actively recommends your brand for specific scenarios – requires an average score of 65–85%.

What Each Score Level Tells You

A score below 20% means AI systems have minimal entity clarity about your brand. Your content may exist but is not structured for retrieval. The problem is usually a combination of missing structured data, thin topical coverage, and inconsistent brand descriptions across the web.

A score of 20–40% means AI systems recognize your brand exists but cannot describe or recommend it accurately. The gap is typically in content depth and specificity. You are winning awareness citations but losing at the evaluation stage – exactly where a B2B buyer decides whether to add you to a shortlist.

A score above 60% means AI can describe your brand and is beginning to recommend it. At this level, focus shifts to why certain brands consistently win citations while others plateau – usually tied to original research, external citation authority, and case study specificity.

Step 4: Identify the Pattern Behind Missing Citations

Once you have scored all responses, analyze the gaps – not just where your brand was absent, but what the AI said instead.

Map Competitor Citations

For every response where your brand scored 0 or 1, record which competitors were cited at score 2 or 3. This builds a competitor citation map: the specific queries where other brands are being recommended instead of you, and at what level of specificity.

If one competitor appears repeatedly at score 3 across category discovery and use-case prompts, that brand has built deeper topical authority and stronger entity clarity than yours. The gap is diagnosable.

Check Which Pages AI Cites

When platforms like Perplexity and ChatGPT Search include source links, those links tell you exactly which pages on a competitor's site are driving citations. Common patterns:

• Competitor comparison pages that name your category explicitly
• Long-form how-to guides that answer evaluation criteria questions
• Original research or data reports that other sources have cited
• FAQ pages with explicit structured markup

These are the content types you are missing or under-investing in. The signals that consistently build AI citation authority map almost exactly to what competitor citation pages share in common: topical depth, external citation, and structured content format.

Look for Entity Description Accuracy

When your brand does appear, check whether the description is accurate. AI systems sometimes describe brands incorrectly – wrong positioning, outdated product descriptions, or misattributed features. An inaccurate description at score 2 can be more damaging than no mention at all if it confuses buyers about what you do.

If AI describes your brand inaccurately, the cause is usually inconsistent brand language across your website, third-party directories, and review platforms. AI builds its entity model from all of these sources simultaneously.

AuthorityStack.ai provides an Authority Radar audit that queries ChatGPT, Claude, Gemini, Perplexity, and Google AI Mode simultaneously, then scores your brand across five authority layers – entity clarity, structured data, AI platform visibility, content interpretation, and competitive authority so you can see exactly where descriptions are drifting from your intended positioning.

Step 5: Run Prompts That Test Specific GEO Weaknesses

Beyond the four core query types, add a set of diagnostic prompts designed to surface specific weaknesses in your content structure and entity authority. These questions target the exact conditions that determine AI retrieval behavior.

Entity Clarity Prompts

These reveal whether AI systems have a clear, consistent model of what your brand is.

• "What does [Your Brand] do?"
• "Who is [Your Brand] best for?"
• "What is [Your Brand] known for in the [category] space?"
• "How long has [Your Brand] been in the [category] market?"

Score these for accuracy, not just presence. If the description is vague, generic, or wrong, entity clarity is the underlying problem.

Content Authority Prompts

These test whether AI associates your brand with expertise on specific subtopics.

• "What is the best resource for understanding [core topic in your category]?"
• "Who publishes the best content on [specific subtopic]?"
• "What research exists on [specific challenge your buyers face]?"

If competitors appear and you do not, they have earned content authority on these subtopics. Your content cluster has gaps.

Problem-Solution Prompts

These simulate how buyers describe pain points before they know which category of solution they need.

• "We are struggling with [specific pain point]. What should we do?"
• "How do companies solve [specific operational problem]?"
• "[Specific symptom of a problem your product solves] – what causes this and how do companies fix it?"

These prompts test whether your content reaches buyers at the problem-awareness stage – before they know what product category to search. Brands that appear here have published content that addresses buyer problems directly, not just product features.

Recency and Update Prompts

• "What are the best [category] tools in 2025?"
• "What has changed in [category] recently?"
• "Which [category] platforms have added [feature type] in the last year?"

If AI cites competitor content and not yours for recency-sensitive queries, your content library needs more frequent updates. AI systems weight recently published and recently updated content for topics that evolve quickly.

Step 6: Document and Repeat Monthly

A single audit session gives you a baseline. The value compounds when you repeat it consistently. Citation behavior is volatile – content cited today for a specific query may not appear tomorrow due to model updates, new competing content, or retrieval weighting shifts. You are measuring trends, not guarantees.

Build a monthly tracking spreadsheet with these columns:

• Prompt text
• Platform
• Date
• Citation score (0–3)
• Competitors cited
• Source URL (if provided)
• Notes on description accuracy

After 90 days of consistent tracking, you will have enough data to see whether your GEO and content investments are actually shifting citation share. Brands that restructure content for AI retrieval and build consistent entity signals typically see measurable improvement within that window.

Running the same 25 prompts monthly across all four platforms takes 90–120 minutes. That time investment produces the only evidence that tells you whether your content changes are working – not just in Google rankings, but in the AI answers your buyers are actually reading.

The Authority Radar automates this process by running structured queries across all five major AI platforms simultaneously and tracking changes over time, so your monthly audit produces a scored trend rather than a manual snapshot.

How to Interpret What You Find

Three Citation Outcomes

Every prompt produces one of three meaningful outcomes:

Your brand is cited at score 2 or 3. This is the outcome you want. Document the prompt, the platform, and the response text. These are the content types and query patterns where your GEO work is succeeding. Replicate the content structure and topical approach elsewhere.

A competitor is cited at score 2 or 3 while you score 0 or 1. This is the most actionable outcome. You now know exactly which queries you are losing, which competitor is winning them, and (via source links) which pages are responsible. That is your content and GEO roadmap.

No brand is cited clearly at score 2 or 3. This means the query is producing weak AI responses overall. Either the topic is too niche for current AI training data, or no brand has built sufficient authority on this subtopic yet. This is a first-mover opportunity – structured, specific content on this topic published now can establish your brand as the default citation before competitors recognize the gap.

What Changes After the Audit

Most brands that run this audit for the first time discover the same pattern: strong awareness citations (score 1) and almost no solution description or trust citations (scores 2–3). The gap is almost never about brand recognition. It is about content structure.

AI systems cannot recommend a brand for a specific use case if no content on that brand's site describes that use case in specific, citable language. The fix is not more content – it is better-structured content that matches how AI models choose sources and generates answers.

FAQ

What Prompts Should I Use to Check If My Brand Is Cited by AI?

Use four categories of prompts: category discovery ("What are the best [category] platforms for [buyer profile]?"), evaluation criteria ("What should I look for in a [category] vendor?"), competitor alternatives ("Alternatives to [Competitor Name]"), and use-case fit ("Best [category] tool for a company with [specific constraint]"). Run 20–30 prompts total and repeat them across ChatGPT, Claude, Perplexity, and Google AI Overviews to get a complete picture.

Why Does My Brand Appear in Google but Not in AI Answers?

Strong organic SEO rankings do not automatically translate to AI citation. Content optimized for keyword ranking is often structured as continuous prose that AI systems cannot easily extract. AI systems prefer definitions, named frameworks, step-based explanations, FAQ blocks, and comparison tables – formats that produce self-contained, quotable answers. Most B2B brands with active SEO programs score 18–22 out of 100 on initial AI visibility audits precisely because their content is built for Google, not for retrieval.

How Do I Score My Brand's AI Visibility?

Score each AI response on a 0–3 scale: 0 means your brand is not mentioned; 1 means your brand is named in a list without description; 2 means your brand is described with what it does and who it serves; 3 means your brand is recommended for a specific buyer type or use case. Total your scores across all prompts and platforms, divide by the maximum possible score, and express as a percentage. Most brands score 8–15% at baseline.

Which AI Platforms Should I Test My Brand Citations On?

Test ChatGPT, Claude, Perplexity, and Google AI Overviews at minimum. Each platform draws from different training data and applies different retrieval logic – a brand cited prominently in Perplexity may be completely absent from Claude for the same query. Microsoft Copilot is worth adding if your buyers work in enterprise environments where Microsoft 365 is standard. Run every prompt across all platforms to avoid drawing conclusions from a single system.

How Often Should I Repeat the AI Citation Audit?

Run the full prompt set monthly. Citation behavior is volatile – model updates, new competing content, and retrieval weighting shifts can all change results between sessions. A single audit gives you a baseline; monthly repetition reveals whether your content and GEO changes are actually moving your citation share. After 90 days of consistent tracking, patterns become clear enough to guide content investment decisions.

What Does It Mean When AI Describes My Brand Inaccurately?

Inaccurate AI descriptions signal entity ambiguity – inconsistent brand language across your website, third-party directories, review platforms, and press mentions. AI systems build their model of your brand from all of these sources simultaneously. If your positioning language differs between your homepage, your G2 profile, and your LinkedIn page, AI synthesizes a blended description that may match none of them accurately. Consistent brand language across all sources is the fix.

How Long Does It Take to Improve AI Citation Scores?

Brands that restructure content for AI retrieval and build consistent entity signals across the web typically see measurable improvement within 90 days. There is no fixed timeline because AI systems update their indexes and retrieval logic at different intervals, and the relationship between publishing and citation is less direct than in traditional SEO. Content clusters – multiple related articles that collectively demonstrate topical depth – compound results faster than single articles.

What Should I Do When a Competitor Consistently Scores 3 and I Score 0?

Record which competitor is cited, which specific prompts trigger the citation, and which source pages are linked in the AI response. Those source pages show you exactly what content is driving the competitor's trust citations – typically original research, detailed comparison pages, specific case studies with documented outcomes, or comprehensive how-to guides on subtopics you have not addressed. Each gap is a specific content and GEO investment decision, not a general "publish more content" problem.

What to Do Now

1. Write your 20–30 prompt list using the four categories in Step 1. Use your buyers' language, not internal product terminology.
2. Open ChatGPT, Claude, Perplexity, and Google AI Overviews and run every prompt. Document every result in a spreadsheet with the scoring fields from Step 2.
3. Calculate your baseline AI visibility score. If you score below 20%, prioritize entity clarity and content structure before anything else.
4. Map which competitors appear at score 2 or 3 for queries where you score 0 or 1. Check the source links those platforms provide to identify which specific pages are driving competitor citations.
5. Add the diagnostic prompts from Step 5 – entity clarity, content authority, problem-solution, and recency – to surface the specific GEO weaknesses behind your citation gaps.
6. Repeat the full audit monthly for 90 days. The trend line, not the single snapshot, is what tells you whether your content investments are shifting your citation share.

To track how AI recommends your brand across all five major platforms in one workflow, you can improve your ai visibility with a structured audit that scores every authority layer and shows exactly where to focus next.