AI SEO Glossary

Impression Share in AI Search is a metric borrowed from paid search advertising that measures what percentage of the total possible AI search impressions for a defined set of queries your brand is actually capturing. In PPC, impression share is the percentage of auctions in which your ad was shown out of the total auctions you were eligible for. In AI search, the analog is the percentage of relevant query responses in which your brand appears out of the total responses generated for that query set. It quantifies the gap between your current AI visibility and the maximum visibility you could theoretically achieve.

Google Impression Share is a precise, platform-reported metric with exact data from Google’s ad serving system. AI Impression Share is an estimated metric calculated from sampled prompt testing, since AI platforms do not report impression data directly. The concept is identical: how much of the available visibility are you capturing versus missing. But the measurement methodology differs fundamentally. AI Impression Share requires running representative samples of prompts, recording presence or absence in each response, and calculating the resulting percentage. The sampling introduces more uncertainty than the exact PPC metric, but the directional signal it provides is highly useful for setting AI search visibility targets.

Why it matters: Impression Share framing helps stakeholders who come from a paid search background understand AI visibility gaps in terms they already use to evaluate performance.