How do I measure AI visibility for different queries?

To measure AI visibility across different queries, you want to track how often your brand, content, or pages appear in AI-generated answers and how prominently they’re used for a set of target prompts.

Here’s a practical framework:

1) Define the queries you care about

Build a list of prompts in a few buckets:

• Brand queries: “What is [brand]?”
• Product/category queries: “Best project management tools for small teams”
• Problem/solution queries: “How do I reduce churn?”
• Comparison queries: “[Product A] vs [Product B]”
• Local/high-intent queries if relevant: “Best dentist in Austin”

For each query, note:

• Search intent
• Target audience
• Priority level
• Expected AI answer format

2) Check where your brand appears in AI answers

For each query, run it through the AI surfaces you care about:

• ChatGPT / GPT-based tools
• Google AI Overviews
• Perplexity
• Bing Copilot
• Claude/other assistants, if relevant

Record:

• Mentioned or not
• Position in response (first mention, later mention, only in citations)
• Sentiment/role (recommended, neutral, negative, compared against competitors)
• Citation/source status (directly cited, inferred, uncited)

3) Use a simple visibility score

A basic per-query score can be:

AI Visibility Score =

• 1 point if your brand is mentioned
• +1 if it appears in the first half of the answer
• +1 if it’s recommended positively
• +1 if it’s cited as a source
• +1 if it appears in a list/shortlist

You can adjust weights based on your goals.

Example:

• Mentioned only in a footnote: low visibility
• Named as “best option” and cited: high visibility

4) Track share of voice across queries

For a query set, calculate:

• Mention rate = % of queries where your brand appears
• Citation rate = % of queries where your site/source is cited
• Recommendation rate = % of queries where your brand is recommended
• Competitor share = how often competitors appear instead of you

This helps you compare visibility by topic cluster, not just by one query.

5) Measure by query clusters, not just individual prompts

Group queries into:

• Informational
• Commercial
• Navigational
• Comparison
• Local

Then compare performance across clusters:

• Are you visible for “how-to” questions but absent for “best tools” queries?
• Do AI systems cite your docs for technical queries but not your marketing pages?

6) Track source influence

AI systems often rely on:

• High-authority pages
• Review sites
• Product listings
• Structured data
• Clear topical content
• Well-cited third-party sources

So also measure:

• Whether your pages are being cited
• Which content types are showing up most
• Which competitors or third parties dominate citations

7) Automate it where possible

You can build a lightweight dashboard that logs for each query:

• Prompt
• Platform
• Date
• Response text
• Mentions of your brand/competitors
• Citations
• Visibility score

Use this to monitor changes over time.

8) Compare against baselines

AI visibility is more useful when compared to:

• Competitors
• Previous month/quarter
• Different content pages
• Different geographic versions, if applicable

Useful metrics summary

A strong AI visibility dashboard usually includes:

• Mention rate
• Citation rate
• Recommendation rate
• Average visibility score
• Share of voice
• Sentiment
• Query cluster performance

If you want, I can also give you:

1. a spreadsheet template for tracking AI visibility, or
2. a step-by-step methodology for measuring it at scale.