Share of Voice in AI search is the percentage of AI-generated answers on a given topic or query set that mention or cite a specific brand, measured against how often competitors are mentioned across the same queries. It's a proportion, not a raw count. And unlike a Google ranking, there's no single "position one" to fight over.
Share of voice in plain English
Imagine running 20 real buyer questions from your niche through ChatGPT, Perplexity, Google AI Overviews, and Claude. Things like "best material for a dog crate cover" or "how much biltong should I buy for a party of 10." For each answer, you note which brands got named. If your brand shows up in 6 of those 80 total answers (20 questions × 4 engines) and your biggest competitor shows up in 22, your share of voice on that query set is roughly 7.5% against their 27.5%. Even if you've never lost a single Google ranking to them.
That's the core shift: AI answers don't have ten blue links to split attention across. They usually cite somewhere between two and six sources per answer, and plenty of answers cite one brand exclusively. Share of voice is the metric that captures who's actually winning those scarce citation slots across a whole category of questions, not just one.
How share of voice is actually measured
In practice, nobody runs this by hand for long. Dedicated AI-visibility platforms . Otterly.AI, Peec AI, Profound, and Semrush's AI Visibility Toolkit among them. Automate the whole loop: they maintain a prompt set built from real buyer questions, rerun it daily across ChatGPT, Perplexity, Google AI Overviews, and other engines, parse which brands got cited in each response, and calculate the percentage split. The output is usually a trend line over time plus a competitor breakdown, so you can see not just your own number but whether it's moving in the right direction relative to whoever's currently ahead.
The mechanics matter for interpreting the number correctly: share of voice is scoped to whatever query set you (or the tool) chose to track. A narrow, well-targeted prompt list gives you a meaningful, actionable number. A vague or too-broad prompt list produces a share-of-voice figure that looks precise but doesn't actually tell you anything useful about a real buyer's path to your product.
Why it matters for ecommerce
Share of voice is the closest thing AI search has to a scoreboard. A single AI citation tells you one answer went your way. Share of voice tells you whether that's a pattern or a fluke across the actual questions your buyers ask. For a store trying to decide whether new content is working, tracking share of voice over time. Rather than checking one query occasionally. Is what turns "did that article help?" into an answerable question with a real trend line behind it.