AI Visibility Audit
Fresh
This content reflects a synthesized audit workflow from Metehan Alp's methodologies as of 2025-2026.
A systematic audit workflow to assess your current visibility across AI search platforms. Run this before building an optimization strategy -- you need a baseline before you can measure improvement.
Audit Overview
Step 1: CC Rank Check
Establish your domain's citation authority baseline using Metehan's CC Rank Checker tool.
Process
- Open the CC Rank Checker at metehan.ai
- Enter your domain
- Record the citation rank score
- Run the check for your top 3 competitors as well
- Document the gap between your score and the top competitor
What You Learn
- Your domain's relative citation authority
- How you compare to competitors in AI citation strength
- Whether your domain is even in the running for AI citations
Output
- Domain CC rank score
- Competitor CC rank scores (top 3)
- Gap analysis (numeric difference)
Step 2: Temperature Zero Brand Audit
Test what AI platforms currently say about your brand when asked directly.
Process
- Open ChatGPT, Perplexity, Claude, and Google AI Mode
- For each platform, ask these 5 prompts:
- "What is [Brand Name]?"
- "Is [Brand Name] good at [your primary service]?"
- "Compare [Brand Name] to [Top Competitor]"
- "What do people say about [Brand Name]?"
- "Who is the best [your category] company?"
- Record each response verbatim
- Score each response: Positive / Neutral / Negative / Not Mentioned
What You Learn
- Whether AI platforms know your brand exists
- What they say about you (accuracy, sentiment, completeness)
- Whether competitors are mentioned instead of you
- Specific inaccuracies that need correction
Output
- 20 recorded responses (5 prompts x 4 platforms)
- Sentiment scoring grid
- Inaccuracy list
- Competitor mention tracking
Step 3: Log Probability Analysis
Analyze how confidently AI models associate your brand with your topic area.
Process
- Use an AI model that exposes token probabilities (OpenAI API with logprobs enabled)
- Submit prompts like: "The leading company for [your service] is"
- Record the log probability assigned to your brand name as the next token
- Compare against competitors' brand names for the same prompt
- Test across 10-15 prompt variations
What You Learn
- How strongly the AI model associates your brand with your category
- Whether competitors have stronger token-level associations
- Which topic areas your brand is most/least associated with
Output
- Log probability scores per prompt per brand
- Ranking of brands by association strength
- Weak association areas (optimization targets)
Step 4: Server Log Review
Analyze your server logs for AI bot crawl patterns.
Process
- Pull server logs for the last 90 days
- Filter for known AI bot user agents:
- GPTBot
- OAI-SearchBot
- GoogleOther
- PerplexityBot
- CCBot
- ClaudeBot
- For each bot, record:
- Total requests
- Pages crawled (unique URLs)
- Crawl frequency (requests per day)
- Most-crawled pages (top 20)
- wp-json and sitemap access patterns
- Verify bot identity using reverse DNS (see Bot Crawlers Reference)
What You Learn
- Which AI bots are crawling your site
- How frequently they crawl
- Which pages they prioritize
- Whether wp-json endpoints are being accessed (1.6x GPTBot activity signal)
- Any blocked bots that should be allowed
Output
- Bot traffic summary table
- Top 20 most-crawled pages per bot
- Crawl frequency trends (daily/weekly)
- Blocked bot list review
Step 5: Prompt Tracking
Transform your GSC data into AI prompt intelligence using the AI Prompt Tracking methodology.
Process
- Export GSC query data (last 90 days, all queries with impressions > 10)
- Filter for conversational queries (4+ words, question format, comparison structure)
- Cluster by semantic similarity using embeddings
- Generate AI prompt variants from clusters
- Validate top 50 prompts against ChatGPT, Perplexity, and Google AI Mode
- Record citation status for each validated prompt
What You Learn
- Which prompts you should be tracking (data-driven, not guessed)
- Current citation rate across platforms
- Highest-value prompt targets (high GSC impressions + not yet cited)
Output
- Prompt cluster list (23+ clusters typical)
- Citation status grid (prompt x platform)
- Priority targets (high impression, non-cited prompts)
Step 6: Platform Coverage
Synthesize findings into a platform-by-platform coverage assessment.
Process
For each platform (ChatGPT, Perplexity, Google AI Mode), compile:
- Brand awareness: Does the platform know your brand? (from Step 2)
- Citation frequency: How often are you cited? (from Step 5)
- Bot crawl activity: Is the platform's bot crawling you? (from Step 4)
- Association strength: How strongly does the platform link your brand to your topic? (from Step 3)
- Content coverage: What percentage of relevant prompts cite your content? (from Step 5)
Coverage Scoring
| Metric | Score |
|---|---|
| Brand recognized + cited in 50%+ of prompts | Strong |
| Brand recognized + cited in 20-49% of prompts | Moderate |
| Brand recognized + cited in < 20% of prompts | Weak |
| Brand not recognized | Not Present |
Output
- Platform coverage scorecard
- Platform-specific optimization priorities
- Cross-platform gap analysis
Audit Report Template
Compile all outputs into a single audit report:
AI VISIBILITY AUDIT: [Brand Name]
Date: [Date]
1. CC RANK: [Score] (Competitor avg: [Score])
2. BRAND AWARENESS: [Platform coverage summary]
3. CITATION RATE: [X]% across [N] validated prompts
4. BOT ACTIVITY: [Summary of crawl patterns]
5. PRIORITY TARGETS: [Top 10 optimization opportunities]
6. RECOMMENDED NEXT STEP: [Workflow recommendation]Next Steps After the Audit
| Audit Finding | Recommended Workflow |
|---|---|
| Low citation rate, good content exists | AEO Content Pipeline (optimize existing) |
| Content gaps in key topic areas | Topic Cluster Building |
| Bots not crawling | Fix technical access (robots.txt, sitemap, wp-json) |
| Brand not recognized | Build brand signals (schema, E-E-A-T, CiteMET distribution) |