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TTFB by URL sample

TTFB by URL sample without noise

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


What is TTFB by URL sample

TTFB by URL sample shows how Time to First Byte (TTFB) differs between URLs that are part of the Google Chrome User Experience Report (CrUX) and those that are not.

This lens helps you understand whether your server response times are fast and consistent — especially on high-traffic pages visible in Google’s public performance dataset.

Two categories:

  • Google CrUX – URLs included in CrUX due to sufficient real-user visits

  • Non Google CrUX – URLs not publicly tracked by Google, often because of low volume or exclusion filters


Healthy "TTFB by URL sample" sample


Should you worry

In a healthy scenario:

  • Google CrUX URLs return fast TTFB — showing strong backend and edge performance for your most visible pages

  • Non Google CrUX URLs are on par — suggesting you’re delivering speed even on the long tail

  • Overall latency is low and stable across both — a signal of healthy infrastructure and CDN configuration

This kind of balance shows your server strategy is scalable, and not just optimized for SEO-critical paths.

Unhealthy "TTFB by URL sample" sample

When Google CrUX URLs have slow TTFB:

  • You're hurting the pages that Google’s ranking systems pay the most attention to

  • These delays can bottleneck Core Web Vitals like LCP and INP, dragging down overall experience and SEO

When Non Google CrUX URLs are slow:

  • These often fly under the radar, but may hurt the experience of returning users, long-tail searchers, or internal journeys

  • Slow TTFB here often points to neglected routes, legacy infrastructure, or serverless functions with cold starts

A wide gap between CrUX and non-CrUX performance can indicate patchy backend optimization.

Resolving unhealthy TTFB by URL sample

Go-to action plan to resolve an unhealthy TTFB by URL sample:

  1. Ask Uxi to analyze your TTFB by URL sample values and suggest improvements.

  2. Use Filters to isolate slow endpoints by traffic, device, or location.

  3. Simulate TTFB of the suspected lens to see if fixing it will resolve the TTFB by URL sample. If yes, this is where the resolution focus should be.

  4. Use an automated optimization tool like Navigation AI to improve your TTFB by URL sample values.

  5. Once you’ve improved TTFB, 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.

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