What it is
AI visibility tracking measures how your brand appears inside AI-generated search results, including platforms like:
Google AI Overviews
ChatGPT
Gemini
Perplexity
AI Mode
Claude
Other large language model (LLM) interfaces
Instead of tracking blue links in Google’s traditional results, AI Visibility tracks:
Whether your brand is mentioned
Where it appears in the AI response
How prominently it is positioned
How frequently it appears across test runs
How it is described (sentiment)
Whether it is cited or referenced
In AI Visibility, your domain is tracked as a brand. This allows you to monitor both domain-based and non-domain brand mentions (e.g., a company name that may appear without a direct link).
Why it matters
AI-generated answers are becoming a primary way users discover products, services, and brands.
This fundamentally changes search behaviour:
Users receive summarized answers instead of browsing 10 links
Brands may be recommended without a click
Citations and mentions influence trust and perception
Visibility can shift even if traditional SEO rankings stay stable
AI visibility tracking gives you:
A measurable way to track brand presence inside AI answers
Competitive benchmarking across AI engines
Early detection of brand perception shifts
Insight into which topics and prompts surface your brand
A new performance layer beyond traditional SEO
Even for experienced SEO teams, AI search introduces new mechanics. Rankings alone no longer tell the full story - brand mentions, citations, and contextual placement now directly influence visibility.
AI Visibility helps quantify this new search layer.
💡 AI search is evolving quickly. Measuring visibility early gives you a competitive advantage as this channel grows.
How it works
AI Visibility runs structured test queries (search terms) against selected AI engines.
For each term:
The exact prompt is sent to the selected AI model
The AI-generated response is captured
Brands are detected within the response
Position, frequency, sentiment, and citation data are analyzed
Metrics are calculated based on multiple test runs
Each term can be scheduled to update:
Hourly
Daily
Weekly
Monthly
Because AI responses are probabilistic, multiple runs help create a more reliable visibility score over time.
What is measured
For each brand and search term, AI Visibility tracks:
Visibility score - Combines detection rate and ranking position
Detection rate - How often your brand appears across runs
Average position - Where your brand ranks in responses
Top 3 visibility - How often your brand appears in the top 3 positions
Mentions - Total number of brand references
Citations - Whether the AI references external sources
Sentiment - Positive, neutral, or negative tone
These metrics allow you to monitor both presence and perception.
Brand vs domain in AI visibility
In AI Visibility, you create a brand.
A brand typically starts with a domain (e.g., disney.com), but AI engines may reference:
A company name
A product line
A business unit (e.g., “Disney Parks”)
Tracking at the brand level ensures visibility is captured even when the AI does not explicitly reference the root domain.
What to expect
AI visibility behaves differently from traditional SEO:
Results may vary slightly across runs
Different AI engines may produce different brand rankings
Brand mentions may appear without citations
AI engines may summarize competitors without linking
Because of this, trends over time are more meaningful than single snapshots.
AI Visibility is designed to monitor consistency, prominence, and perception, not just isolated mentions.
Best practices
Start with high-intent, commercially relevant search terms
Track across multiple AI engines to compare differences
Monitor both visibility score and citation trends
Review AI result snapshots to understand context
Use topic grouping to identify strategic strengths and gaps