Website Speed Checker

What are Core Web Vitals and why do they matter?

Core Web Vitals are Google's user-experience metrics used as a ranking signal in search results. Largest Contentful Paint (LCP) measures loading performance — how fast the main content becomes visible. Cumulative Layout Shift (CLS) measures visual stability — how much content jumps around during load. Interaction to Next Paint (INP, replaced First Input Delay in March 2024) measures responsiveness — how fast the page reacts to user input. Google uses field data from real Chrome users to score each URL, and sites in the 'Good' band for all three metrics get a small but real SEO boost over sites in 'Needs Improvement' or 'Poor'.

Why do my results vary between runs?

Performance measurement is inherently noisy. Between any two runs, the CDN cache state may differ (first request warms the cache, second request hits it), TCP connections may reuse from a prior run, the measurement server's CPU load fluctuates, third-party scripts load from shared infrastructure whose own latency varies, and Chrome's own scheduling jitter introduces milliseconds of randomness. Expect a 10 to 20 percent spread across runs on a typical page. To get a reliable reading, run at least three times and compare the median rather than the first or last individual result. Consistent patterns across multiple runs are trustworthy; single readings are suggestive at best.

What is the difference between lab data and field data?

Lab data comes from a synthetic measurement in a controlled environment — one simulated device on one simulated network, run on demand, reproducible. This tool and Lighthouse produce lab data. Field data comes from the Chrome User Experience Report (CrUX), aggregated from real Chrome users on their real devices over a rolling 28-day window. PageSpeed Insights shows both; Search Console shows only field data in its Core Web Vitals report. Lab data is fast and good for debugging specific regressions or A/B comparing page variants. Field data is what actually determines your Core Web Vitals pass/fail for SEO purposes.

My lab score is good but Search Console shows poor — which is right?

Search Console is the one that matters for SEO because it uses field data from actual users. Lab data represents one simulated device on one simulated network; real users span a range of devices (old phones, high-end laptops), network conditions (gigabit fiber, congested LTE), and geographic latencies (on-continent CDN POPs vs trans-oceanic). Field data averages all of that into a p75 score that is often worse than the best-case lab reading. If lab is green and field is red, improve the field experience: look at the p75 distribution, identify which user segments are struggling, and optimize for those paths. Lab-only optimization will not move the Search Console score.

What causes a high CLS score?

CLS penalizes unexpected layout movement after page load — content jumping around as images, ads, or async components finish loading. The common causes are images without explicit width and height attributes (reserve space in HTML so the browser does not have to re-layout when the image arrives), web fonts that cause text to reflow when the custom font loads (use font-display: swap with a metric-matched fallback), ads or embeds inserted above existing content (always reserve their space with a min-height container), and dynamically injected banners (cookie notices, announcement bars) that push content down. Fixing CLS usually means adding explicit dimension hints to async content so the browser lays out once, not multiple times.