AI Share of Voice
AI share of voice is the percentage of AI-generated answers in your category that include your brand, measured against the competitors who appear in the same answers. It reframes visibility as a competitive share: not just whether you show up, but how big your slice is versus everyone else. Rankry computes it per model and over time.
What this page covers
Section titled “What this page covers”- What AI share of voice means
- Why it beats a raw mention count
- How Rankry measures it
- Related metrics
Why it beats a raw mention count
Section titled “Why it beats a raw mention count”A rising mention rate can still mean falling ground if competitors rise faster. Share of voice captures the competitive reality a raw count misses, and it maps to the question leadership asks: are we winning or losing against our rivals?
How Rankry measures it
Section titled “How Rankry measures it”Rankry counts how often your brand appears across your category prompts, counts how often each competitor appears in the same answers, and expresses yours as a percentage of the total. The Compete view also shows head-to-head win rate against each competitor.
Related metrics
Section titled “Related metrics”Share of voice pairs with Visibility (your absolute presence) and competitor win rate (your standing against a specific rival). See Metrics reference.
Frequently asked questions
Section titled “Frequently asked questions”How is AI share of voice calculated?
Section titled “How is AI share of voice calculated?”Count your mentions across a set of category prompts, count each competitor’s mentions in the same answers, and express yours as a percentage of the total.
Why use share of voice instead of mention rate?
Section titled “Why use share of voice instead of mention rate?”Mention rate can rise while you lose ground if competitors rise faster. Share of voice is relative, so it reflects the competitive picture.
Can I track share of voice per model?
Section titled “Can I track share of voice per model?”Yes. Your slice can be large on one model and small on another, so a per-model view shows where to focus.