research
2026 K-Beauty AI Search Visibility Benchmark: 20 Brands and 108 Responses
A benchmark of how 20 K-beauty brands appeared across 108 AI search responses, with a practical framework for interpreting visibility.
Findable analyzed 108 AI search responses across 20 K-beauty brands to understand how brand visibility is formed in generative answers. This benchmark is a snapshot, not a promise of future rankings.
What we measured
We used a consistent question set and recorded whether a brand was mentioned, how it was described, whether the answer cited a source, and which source type was used. The same brand can look strong on one question and absent on another, so question-level reporting matters.
How to read the result
Mention rate is only the first signal. A useful diagnosis separates four questions:
- Was the brand mentioned?
- Was the description accurate and specific?
- Was a first-party or otherwise useful source cited?
- Did the answer satisfy the intent of the question?
What brands can do next
Start with a stable set of customer questions, repeat the measurement across engines, and improve the pages that should act as sources. Clear product facts, consistent entity information, and direct answers make a page easier to retrieve and summarize.
Limits
AI answers vary by model, date, wording, and retrieval context. A benchmark should therefore be treated as an observation system. Re-run it on the same questions before making a content or brand decision.
Findable uses this approach to connect SEO, GEO, and AI search visibility into one measurement workflow.