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TTFB by U-turns

TTFB by U-turns without noise

Vasil Dachev avatar
Written by Vasil Dachev
Updated over 2 months ago


What is TTFB by U-turns

TTFB by U-turns breakdown shows how Time to First Byte (TTFB) 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 load fast enough.

This breakdown helps you determine whether server response time (TTFB) is contributing to early abandonment. Since TTFB measures how quickly the browser receives the first byte from the server, poor values mean users wait longer before seeing any content.


TTFB by U-turns sample


Should you worry

In a healthy view, TTFB values for U-turn sessions are similar to those without them. U-turns may still occur, but they’re likely due to intent or content relevance rather than slow server responses.

A healthy setup typically shows:

  • TTFB consistently green (under 800ms).

  • No noticeable delay in starting to load the page.

  • Fast CDN or edge delivery across geographies.

If TTFB is low and stable, U-turns are unlikely to be caused by server delays.

Unhealthy TTFB by U-turns

If U-turn sessions consistently show higher TTFB values, users may abandon before the page even begins to load properly.

Common causes include:

  • Slow origin servers under heavy load.

  • Poor CDN coverage or missing edge caching.

  • Dynamic rendering slowing down response generation.

  • Database queries or backend logic delaying the initial response.

Here, slow TTFB means users wait too long before anything renders, making abandonment more likely.

Resolving unhealthy TTFB by U-turns

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

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

  2. Use Filters to compare U-turn vs non-U-turn TTFB by device, region, or traffic type.

  3. Simulate TTFB of the suspected breakdown to see if fixing it will resolve the TTFB by U-turns. If yes, this is where the resolution focus should be.

  4. Use an automated optimization tool like Navigation AI to improve your TTFB by U-turns values.

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

Try it yourself

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