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CLS by user type

CLS by user type without noise

Vasil Dachev avatar
Written by Vasil Dachev
Updated over a month ago


What is CLS by user type

CLS by user type shows Cumulative Layout Shift (CLS) across different user types (e.g., First-time visitor, Returning visitor). This breakdown helps you identify whether layout instability is affecting new users, returning users, or both — and how that might impact trust and usability.

The list includes only user types that generated traffic to your site during the selected period.

First-time visitors are more likely to experience visual instability due to cold-start conditions — such as uncached fonts, styles, or third-party scripts — which can lead to layout shifts during the initial load.

Healthy CLS by user type sample


A healthy CLS by user type view is all green — showing that both new and returning users are experiencing visually stable pages.

Some variation is normal, but if no user type shows yellow or red, your layout is considered stable across sessions and cache states.

Unhealthy CLS by user type sample

In the example below, returning visitors are experiencing poor CLS, while first-time visitors remain stable. This often points to layout shifts triggered by personalized or dynamic content — such as toolbars, banners, or account-specific UI elements — that load after the initial page render.

Common causes include:

  • Personalized banners or toolbars injected after load.

  • Layout changes driven by logged-in state or localStorage flags.

  • Dynamic components that shift content once user data is available.

Even though returning users benefit from cached assets, these logic-driven shifts can undermine visual stability and lead to frustration over time.

Resolving unhealthy CLS by user type

Go-to action plan to resolve an unhealthy CLS by user type:

  1. Ask Uxi to analyze your CLS by user type values and suggest improvements

  2. Use Filters to isolate user type and compare with CLS breakdowns like device, page, and third party.

  3. Simulate CLS of the suspected breakdown to see if fixing it will resolve the CLS by user type. If yes, this is where the resolution focus should be.

  4. Use an automated CLS optimization tool like Navigation AI to improve your CLS by user type values

  5. Once you’ve improved CLS, set an alert to be the first to know if it starts worsening again.

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