Measuring AI visibility is fundamentally different from tracking SEO rankings. There's no "position #1" in AI search—instead, you need to track whether your brand is being mentioned, recommended, and cited across AI platforms.
Why Measurement is Different for GEO
Traditional SEO metrics don't translate directly to GEO:
| SEO Measurement | GEO Equivalent | Key Difference |
|---|---|---|
| Keyword ranking (#1-100) | Mention presence (yes/no) | No numbered positions |
| Search volume | Query frequency across LLMs | Less standardized data |
| Click-through rate | Citation inclusion rate | Often no clicks at all |
| Impressions | Share of voice in responses | Harder to quantify |
The Challenges
- No centralized console: Unlike Google Search Console, there's no unified dashboard for AI visibility
- Response variability: AI responses vary based on conversation context, user history, and model updates
- Multiple platforms: ChatGPT, Claude, Gemini, and Perplexity each behave differently
- Evolving models: AI systems are constantly updated, changing how they cite sources
Key Metrics to Track
1. Mention Frequency
The most basic metric: How often does your brand appear in AI responses for relevant queries?
How to measure:
- Track a set of target queries across multiple AI platforms
- Run queries multiple times (AI responses vary)
- Record whether your brand is mentioned in each response
- Calculate mention rate: (mentions / total queries) x 100
2. Sentiment Analysis
Being mentioned isn't enough—the context of mentions matters:
- Positive: "Brand X is highly recommended for..."
- Neutral: "Brand X is one option for..."
- Negative: "Brand X has had issues with..."
Track the sentiment distribution of your mentions to understand how AI positions your brand.
3. Share of Voice
Compare your mentions to competitor mentions for the same queries:
Share of Voice Formula
Your Share of Voice = (Your Mentions / Total Mentions of All Brands) x 100
For example, if you're mentioned 3 times and competitors are mentioned 7 times across 10 queries, your share of voice is 30%.
4. Citation Quality
Not all mentions are equal. Track the quality of how you're cited:
- Primary recommendation: "I recommend Brand X for this use case"
- Listed option: "Options include Brand X, Brand Y, and Brand Z"
- "Also consider": "You might also want to look at Brand X"
- Link citation: AI includes a direct link to your content
5. Position in Response
Where in the AI response does your brand appear?
- First mention: Most prominent, often the primary recommendation
- Middle mention: Listed among options
- Last mention: Often an afterthought or "alternative"
Manual Testing Approach
Until you have dedicated tools, manual testing provides valuable insights:
Step 1: Define Your Query Set
Create a list of queries that matter for your business:
Query Categories to Include:
- Category queries: "Best [your category] tools"
- Use case queries: "What [solution] for [use case]?"
- Comparison queries: "Compare [you] vs [competitor]"
- Problem queries: "How to solve [problem you address]?"
- Recommendation queries: "What do you recommend for [situation]?"
Step 2: Test Across Platforms
Run your queries on each major AI platform:
- ChatGPT: Both GPT-4 and GPT-3.5 if accessible
- Claude: Anthropic's Claude
- Gemini: Google's Gemini
- Perplexity: Particularly important for research queries
Step 3: Record Results Systematically
For each query and platform, record:
- Date and time of query
- Whether your brand was mentioned
- Position in the response
- Sentiment (positive/neutral/negative)
- Competitors mentioned
- Direct quotes or context
Step 4: Repeat Regularly
AI responses vary. Run the same queries weekly to:
- Account for response variability
- Track changes over time
- Identify trends and patterns
- Measure the impact of your GEO efforts
Tools for AI Visibility Tracking
Several tools are emerging to automate AI visibility tracking:
Dedicated GEO Tools
Platforms specifically built for tracking AI visibility across multiple LLMs.
View GEO Tools →Manual Tracking Templates
Spreadsheet-based tracking for teams just getting started with GEO measurement.
Coming soonKey features to look for in GEO tracking tools:
- Multi-LLM support: Track across ChatGPT, Claude, Gemini, Perplexity
- Automated query testing: Schedule regular query runs
- Competitor tracking: Monitor competitor mentions alongside yours
- Sentiment analysis: Automatically categorize mention sentiment
- Historical data: Track changes over time
- Alerting: Get notified of significant changes
Benchmarking Your Progress
Setting Baselines
Before implementing GEO strategies, establish your baseline metrics:
- Run your query set across all platforms
- Record mention rates, sentiment, and share of voice
- Document competitor performance
- Save this as your "day zero" benchmark
Tracking Improvement
After implementing GEO strategies, compare against your baseline:
| Metric | Baseline | After 30 Days | After 90 Days |
|---|---|---|---|
| Mention Rate | Track % | Track % | Track % |
| Share of Voice | Track % | Track % | Track % |
| Positive Sentiment | Track % | Track % | Track % |
| First Position % | Track % | Track % | Track % |
Industry Benchmarks
While GEO is still emerging, here are general benchmarks based on early data:
- Market leaders: 60-80% mention rate for category queries
- Strong performers: 30-60% mention rate
- Average: 10-30% mention rate
- Needs improvement: <10% mention rate
Note on Benchmarks
These benchmarks are early estimates. As GEO measurement matures, more precise industry-specific benchmarks will emerge.
Next Steps
Now that you understand how to measure AI visibility:
- Learn the strategies that improve these metrics
- Explore tools that can help automate tracking
- Set up your baseline measurements today