Skip to main content

CLS by U-turns

CLS by U-turns without noise

Written by Vasil Dachev


What is CLS by U-turns

CLS by U-turns shows how Cumulative Layout Shift (CLS) differs for users who make a U-turn compared to those who stay and interact with the page.

A U-turn occurs when a user lands on a page, stays for five seconds or less, doesn’t interact (no clicks, scrolls, or inputs), and then navigates back to the previous page. It’s a signal that something didn’t resonate — or possibly didn’t render properly.

This insight helps you understand whether unstable layouts are contributing to users leaving before they engage. Since CLS represents unexpected shifts of visible elements, a poor CLS may cause frustration and early exits.

CLS by U-turns sample

In a healthy view, CLS values for U-turn sessions look similar to non-U-turn sessions. Users may still leave quickly, but it’s not because the page layout moved around after loading.

A healthy setup typically shows:

  • CLS consistently green (<0.1) across both groups.

  • No sudden layout movements as content loads.

  • Reserved space for ads, images, and embeds to prevent shifts.

If CLS remains stable and low, U-turns are more likely tied to content relevance or user intent — not performance.

Unhealthy CLS by U-turns

If U-turn sessions consistently show higher CLS values, layout instability may be pushing users away before they interact.

Common causes include:

  • Images or ads without fixed dimensions pushing content down.

  • Fonts swapping late and causing text reflow.

  • Third-party widgets or banners loading unpredictably.

  • Dynamic containers shifting key elements below the fold.

In this case, the U-turn isn’t just about intent — it’s about frustration with an unstable page.

Resolving unhealthy CLS by U-turns

Go-to action plan to resolve an unhealthy CLS by U-turns:

  1. Ask Uxi to analyze your CLS by U-turns values and suggest improvements
    ​

  2. Use Filters to compare CLS between U-turn and non-U-turn sessions by device or traffic source.
    ​

  3. Simulate CLS of the suspected insight to see if fixing it will resolve the CLS by U-turns. 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 U-turns values
    ​

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

Try it yourself

Discover how your website performs with real user data.
​​

Did this answer your question?