Use case
AI share of voice
Share of voice has always mattered in marketing. Now it matters in AI too. How often does AI recommend your brand compared to competitors?
The metric that tells you where you stand
When someone asks an AI model "What's the best [your category]?", the brands mentioned in the response get the attention. Share of voice measures how often your brand appears compared to competitors across these recommendations.
A brand mentioned in 10 out of 13 models has a 77% share of voice. A brand mentioned in 1 out of 6 has 17%. The difference between these two positions can determine who gets the customer.
Unlike traditional share of voice (media mentions, ad impressions), AI share of voice is harder to measure because conversations are private. You can't see what AI says unless you systematically ask it.
What Cited Monitor measures
Cross-model share of voice
How many models mention your brand for a given prompt? See the percentage across ChatGPT, Claude, Gemini, Llama, Mistral, and Perplexity.
Per-model breakdown
Your share of voice might be strong on ChatGPT but weak on Gemini. Per-model data shows you exactly where to focus your efforts.
Mention position
Being mentioned first carries more weight than being mentioned last. Track your average position in AI recommendations over time.
Trend tracking
Share of voice shifts with model updates, new content, and competitor activity. Daily and weekly tracking catches changes before they become problems.
How to improve your AI share of voice
Understand where you stand first. Set up prompts that reflect the questions your customers actually ask AI. Run them across all models. Establish your baseline.
Identify the gaps. Which models skip your brand? Which prompts favour competitors? The data tells you exactly where to focus.
Track the impact of your changes. Published a new blog post? Updated your product page? Added structured data? Run the prompts again and see if your share of voice improved.
Measure your AI share of voice
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