Executive Metric

Roll messy AI answers into one visibility score.

Klairia summarizes model responses into a score that shows whether your brand is becoming more or less visible in AI recommendations.

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Problem

Screenshots do not make a reliable visibility metric.

Manual AI checks are hard to compare over time. Klairia stores structured scan results and turns them into a consistent score that leadership can understand.

Outcome

What Klairia gives you

Replace anecdotal AI screenshots with a tracked metric.
Connect brand visibility changes to campaigns and content work.
Spot downward movement before it becomes a strategic issue.
Summarize multi-model, multilingual data in one number.

How it works

A repeatable workflow for visibility score tracking.

1

Each result is judged for mention presence, position and context.

2

Prompt specificity and model-language coverage feed the scan score.

3

Snapshots are stored for trend reporting.

4

The dashboard shows current score and historical movement.

Questions

Common questions about visibility score tracking.

What goes into the visibility score?

The score is based on whether the brand is mentioned, where it appears, how specific the prompt was, and how results aggregate across selected models and languages.

Can the score be compared week over week?

Yes. Klairia is built around recurring scans so teams can compare score movement over time.

Related features

Build the full AI visibility workflow.

Trend Tracking

Weekly scan history

Klairia stores recurring scan snapshots so teams can see whether AI visibility is improving, declining or flat.

Specificity Signal

First mention level

First mention level shows whether your brand appears in broad category recommendations or only after the prompt becomes highly specific.

Result Analysis

Mention detection

Klairia analyzes model responses for brand mentions, URL mentions, recommendation position, context and competitor presence.