How it’s calculated
Why repeated sampling matters
Ask an AI engine the same question several times and you’ll get different answers: different brands, different ordering, different emphasis. A single-sample audit collapses that variability into a yes or no. It can’t distinguish a brand that appears in nearly every answer from one that slipped into a single lucky response. Both would show as “appeared”, yet they’re in fundamentally different positions. Repeated sampling turns “did we appear” into a reliability measurement. A brand appearing 90% of the time is established in the engine’s answer set. A brand appearing 10% of the time is on the edge of visibility, and a small shift in the engine’s behavior could remove it entirely.Reading the spread
A project’s Appearance Rate is an average across every prompt and engine, and an average hides its own shape. Two brands can share the same headline rate while one appears in nearly every run on every prompt and the other dominates a handful of prompts but is invisible on the rest. zued shows the distribution behind the number, so you can see that shape directly: how many prompts you appear in reliably, and where you have a weak tail. You can read the spread grouped by prompt, page, or topic, and a ranked view surfaces exactly where your brand is missing. A tight distribution means the engines treat your brand consistently; a wide one means your presence depends heavily on the specific question, which is usually a content coverage problem you can act on. You can also filter the whole competitive view to a single page, prompt, or topic to see your standing in that narrower context.Appearance Rate and Share of Voice
The two metrics answer complementary questions. Appearance Rate asks: how often do you make it into the answer at all? Share of Voice asks: when you do appear, how much of the answer do you own?| Appearance Rate | Share of Voice | What it means |
|---|---|---|
| High | High | You’re a default part of the answer and you dominate it. Defend this position. |
| High | Low | You’re reliably present but as one name among many. The lever is stronger positioning and depth, not more presence. |
| Low | High | When you make it in, you dominate. The bottleneck is getting into the answer at all, usually a content alignment or coverage problem. |
| Low | Low | You’re marginal in this conversation. Start with Alignment Score and content gaps. |
In the competitive landscape
Appearance Rate is the horizontal axis of the competitive landscape, where every brand the engines mention is mapped by how reliably it appears versus how much of the answer it owns when present. That view puts your Appearance Rate in direct competitive context.Where to drill down
- Per engine: Appearance Rate is tracked per engine. A healthy aggregate can hide a complete absence on one engine.
- Per page: clicking the metric shows your pages ranked by lowest appearance, so you see which pages need attention first.
- Per response: the Compare view lets you read every sampled response. One response per prompt and engine is the analyzed response, the one that receives the full deep analysis (alignment, gaps, recommendations); the remaining samples measure reliability.
- Across audits: pick previous snapshots to compare against and see whether your changes moved the rate.
Because every prompt is sampled repeatedly, Appearance Rate is more robust within a single audit than single-sample metrics. It’s still measured at audit cadence, so use it to track trends between audits rather than day-to-day fluctuations.