Naver share of voice tracking
Naver share of voice is reported with a 95% interval and split by corpus, because a brand that wins through Naver blog content is in a very different position from one cited on the open web.
How it renders
Derived across the sample set, split by source corpus.
Sampling
This is the field where n matters most. At n=1 the metric is noise; at n=30 the interval is typically tight enough to defend in a client report.
Gotcha
What the API returns
A single collection call against Naver for the share of voice field, sampled n times and returned as one object per prompt.
{
"engine": "naver",
"field": "share_of_voice",
"prompt": "best ai visibility tracking tool",
"country": "GB",
"language": "en",
"n": 30,
"share_of_voice": [
{
"brand": "Nostimates",
"share": 0.34,
"ci95": {
"low": 0.2,
"high": 0.52
},
"n": 30
},
{
"brand": "Competitor",
"share": 0.21,
"ci95": {
"low": 0.1,
"high": 0.38
},
"n": 30
}
]
}Response fields
| Key | Type | Notes |
|---|---|---|
| brand | string | Brand from the configured competitor set. |
| share | float | Point estimate across the sample set. |
| ci95 | object | 95% Wilson interval as { low, high }. |
| n | integer | Samples behind the estimate. |
| delta_prior | float | null | Change against the previous run of the same prompt set. |
What it costs
Derived at no extra credit cost, but it scales with n — the interval is bought with samples.
See credit pricing →Naver share of voice FAQ
- Why split share by corpus?
- Because platform-dependent visibility can be revoked by a platform change. Owned visibility cannot.
- What sample size?
- n=30 is comfortable, and Naver is cheap enough that oversampling is easy.
Report Korean share with the platform risk visible
We will scope corpus-split share across your Naver prompt set.
Across every engine
Compare how share of voice behaves on every engine we track.
Share of voice across all engines →