How to Audit Your Brand in ChatGPT, Claude, and Perplexity (Step-by-Step)

Three months ago, a client came to me panicked. A routine Google search had turned into a deeper investigation, and they'd discovered that when people asked AI assistants about their industry, their biggest competitor was mentioned 10x more often than they were – despite having similar market share and larger marketing budgets.

The problem wasn't their content or their SEO. The problem was that they'd never audited their AI search presence, so they had no idea what people were actually hearing about their brand.

If you haven't audited your brand's performance in AI search yet, you're flying blind in an increasingly important channel. Here's exactly how to conduct a comprehensive AI brand audit that reveals both problems and opportunities.

Phase 1: Brand Visibility Assessment (Week 1)

Step 1: Prepare Your Query List

Before you start testing, you need a comprehensive list of queries that represent how people actually ask about your industry.

Core Query Categories:

1. Direct brand queries (5-7 queries)

   • "Tell me about [your company]"
   • "What is [your company] known for?"
   • "Is [your company] a good choice for [use case]?"

2. Category comparison queries (8-10 queries)

   • "What's the best [product category] for [target customer]?"
   • "Compare the top [product category] options"
   • "What [product category] do most companies use?"

3. Problem-solving queries (10-12 queries)

   • "How do I solve [primary problem you address]?"
   • "What's the best way to [achieve outcome you deliver]?"
   • "How can I [customer goal related to your product]?"

4. Use case specific queries (8-10 queries)

   • "What [product category] works best for [specific industry]?"
   • "Best [product category] for [company size]?"
   • "What do [role/title] teams use for [specific challenge]?"

Your action step: Create a list of 30-40 queries across these categories. Focus on how your customers actually talk, not how you talk about your product.

Step 2: Systematic Testing Protocol

Test each query across ChatGPT, Claude, and Perplexity using this standardized approach:

Testing Framework:

• Use the same query wording across all platforms
• Test from a clean session (no conversation history)
• Test at the same time of day to minimize model variation
• Save full response text, not just summaries

Documentation Template: For each query, record:

• Platform (ChatGPT/Claude/Perplexity)
• Query text
• Your brand mentioned? (Yes/No)
• Position in response (1st, 2nd, 3rd, etc.)
• Context of mention (positive/neutral/negative/comparison)
• Competitors mentioned
• Key themes in response

Step 3: Initial Analysis & Pattern Recognition

After testing all queries across all platforms, look for these patterns:

Visibility Patterns:

• Which query categories mention you most often?
• Which platforms favor your brand vs. competitors?
• Are you mentioned for specific use cases but not general queries?

Positioning Patterns:

• When you're mentioned, how are you positioned?
• Are you compared favorably or unfavorably to competitors?
• What attributes are associated with your brand?

Gap Identification:

• Which important queries completely ignore your brand?
• Where do competitors appear that you don't?
• Are there emerging topics where no one has established authority yet?

Phase 2: Competitive Intelligence Gathering (Week 2)

Step 1: Deep Competitor Analysis

Identify your top 5 competitors based on AI mention frequency (not just traditional market competitors).

For each competitor, analyze:

• Mention frequency: How often they appear across your query set
• Positioning themes: What they're known for in AI responses
• Authority topics: Which query categories they dominate
• Content strategy clues: What types of content AI systems reference

Step 2: Competitive Advantage Mapping

Create a detailed comparison matrix:

Visibility Comparison:

• Overall mention frequency vs. each competitor
• Category-specific performance (where you win/lose)
• Platform-specific differences

Positioning Analysis:

• How competitors are described vs. how you're described
• What unique value propositions AI systems associate with each brand
• Which competitor claims are strongest/weakest

Content Gap Analysis:

• Topics competitors cover that you don't
• Content formats they use effectively
• Distribution channels that amplify their AI visibility

Step 3: Market Opportunity Assessment

Based on your competitive analysis, identify:

Quick Wins:

• Queries where no competitor dominates (opportunity to establish authority)
• Topics where current information is outdated or incomplete
• Use cases that are underserved by existing content

Strategic Opportunities:

• Emerging topics where you could establish early authority
• Market segments where competitors are poorly positioned
• Adjacent categories where your expertise could expand

Phase 3: Content Performance Audit (Week 3)

Step 1: Content Attribution Analysis

When AI systems mention your brand, which of your content pieces are they likely drawing from?

Investigation Method:

• Review AI responses that mention you favorably
• Identify themes, statistics, or frameworks mentioned
• Cross-reference with your published content
• Note which content formats get referenced most often

Key Questions:

• Which blog posts/resources appear to influence AI responses most?
• Are AI systems pulling from recent content or older, established pieces?
• Do certain content formats (case studies, guides, data) get referenced more?

Step 2: Content Gap Assessment

Compare what AI systems say about your industry vs. what content you've actually created.

Gap Categories:

• Topic gaps: Important industry topics you haven't covered
• Depth gaps: Topics you've covered superficially that need comprehensive treatment
• Format gaps: Content types that perform well for competitors but you haven't tried
• Perspective gaps: Unique viewpoints or approaches you could contribute

Step 3: Content Quality Evaluation

Audit your existing content through an "AI favorability" lens:

AI-Friendly Content Characteristics:

• Conversational tone that sounds natural when quoted
• Clear, actionable advice that helps solve specific problems
• Original research, data, or frameworks
• Comprehensive coverage of topics rather than surface-level treatment
• Examples and case studies that illustrate key points

Content Optimization Checklist:

• Does this content answer questions people actually ask?
• Would an AI system quote this content in a helpful response?
• Is it better than what competitors have published on this topic?
• Does it demonstrate genuine expertise and experience?

Phase 4: Reputation & Brand Safety Analysis (Week 4)

Step 1: Sentiment & Accuracy Assessment

Analyze not just whether you're mentioned, but how accurately and favorably.

Sentiment Analysis Framework:

• Positive mentions: Actively recommended or praised
• Neutral mentions: Factually mentioned without judgment
• Negative mentions: Criticized or mentioned with significant caveats
• Inaccurate mentions: Factually incorrect information about your company

Step 2: Brand Safety Audit

Look for potential reputation risks in AI responses:

Risk Categories:

• Factually incorrect information about your company
• Outdated information that no longer reflects your business
• Association with negative industry trends or events
• Confusion with similarly named companies

Documentation Process:

• Screenshot problematic responses
• Note specific inaccuracies or concerning associations
• Track which platforms have which issues
• Identify patterns in misinformation themes

Step 3: Crisis Preparedness Assessment

Evaluate your ability to respond to AI-related reputation issues:

Preparedness Checklist:

• Do you have processes for monitoring AI mentions regularly?
• Can you quickly identify when new negative information appears?
• Do you have strategies for improving information quality over time?
• Are you prepared to address factual inaccuracies if they persist?

Phase 5: Strategic Recommendations & Action Planning (Week 5)

Step 1: Priority Opportunity Ranking

Based on your audit findings, rank opportunities by impact and effort:

High Impact, Low Effort (Do First):

• Updating existing content to address identified gaps
• Claiming authority on topics where no competitor dominates
• Improving content that's almost getting AI mentions

High Impact, High Effort (Strategic Projects):

• Creating comprehensive content series on underserved topics
• Building original research or data that differentiates your brand
• Establishing authority in adjacent market categories

Low Impact (Deprioritize):

• Optimizing for queries where strong competitors already dominate
• Creating content on topics with little business relevance
• Pursuing visibility in platforms that don't serve your audience

Step 2: Content Strategy Roadmap

Create a 6-month content plan based on audit findings:

Month 1-2: Foundation

• Address the most critical content gaps
• Update existing content for better AI favorability
• Create comprehensive resources for your strongest topic areas

Month 3-4: Expansion

• Develop original research or frameworks that differentiate your brand
• Create content series that establish authority in new topic areas
• Begin targeting competitor weakness areas

Month 5-6: Optimization

• Double down on content types and topics showing strongest AI visibility gains
• Expand into adjacent topics where you've proven expertise
• Develop thought leadership content that shapes industry conversations

Step 3: Measurement & Monitoring Plan

Establish ongoing processes to track improvement:

Weekly Monitoring:

• Test core query set for mention frequency changes
• Track competitor performance shifts
• Monitor for new inaccurate or problematic mentions

Monthly Analysis:

• Assess content performance against AI visibility goals
• Review competitive positioning changes
• Identify new opportunity areas

Quarterly Strategic Reviews:

• Evaluate overall strategy effectiveness
• Adjust priorities based on market evolution
• Plan next phase of content and positioning investments

How Llumos Streamlines AI Brand Auditing

Conducting a comprehensive AI brand audit manually is thorough but time-intensive. Llumos automates much of this process, providing continuous monitoring and analysis that would otherwise require weeks of manual work.

Our platform automatically tracks your brand mentions across ChatGPT, Claude, and Perplexity, analyzes competitor performance, and identifies content gaps and opportunities. You get the strategic insights of a comprehensive audit updated weekly, not just once per quarter.

Instead of spending a month gathering data manually, you can focus on strategic analysis and content creation while Llumos handles the monitoring and measurement. Start your free trial and get your complete AI brand audit report instantly.

Getting Started: Your First Audit This Month

Week 1: Create your query list and begin systematic testing Week 2: Complete competitive analysis and identify key patterns
Week 3: Audit your content performance and identify gaps Week 4: Assess brand safety and reputation issues Week 5: Create your strategic action plan and implementation roadmap

The goal isn't to achieve perfect AI visibility immediately – it's to understand where you stand, where you have opportunities, and what specific actions will drive the biggest improvements.

Remember: Your AI search audit is a snapshot of today. The brands that win are the ones who audit regularly, act on insights quickly, and adapt as the AI landscape evolves.