The three metrics that matter
Core Web Vitals are Google's field measurements of how your pages feel to real visitors. LCP measures how fast the main content loads, INP measures how quickly the page responds to interactions, and CLS measures how much the layout unexpectedly shifts.
Google uses these as a page-experience signal, and they matter to users regardless of rankings: slow, janky, jumpy pages lose visitors. We target the specific metric that's failing rather than applying generic fixes.
- LCP: speed up the largest element, often a hero image or main text block
- INP: reduce the delay between a user's action and the page's response
- CLS: stop layout shifts from images, ads, and late-loading fonts
- Diagnose with field data (real users) plus lab tools for reproducibility
- Fix the failing metric specifically instead of a scattershot speed pass
How we improve them
Each metric has distinct causes. LCP issues often trace to slow servers, oversized images, or render-blocking resources. INP problems usually come from heavy JavaScript. CLS is typically unset image dimensions or fonts and ads that reflow the page.
We measure against real-user field data, make targeted changes, and re-measure to confirm the metric actually passes, because lab scores and field scores don't always agree.
- Optimize and correctly size images, and preload the LCP element
- Reduce and defer JavaScript to lower interaction latency for INP
- Reserve space for images, ads, and embeds to eliminate CLS
- Address render-blocking CSS and slow server response times
- Validate against Search Console field data, not just lab tests
More on technical seo
Frequently asked questions
Will passing Core Web Vitals boost my rankings?
They're a real but modest ranking signal, and content relevance and authority usually matter more. That said, better vitals improve the experience for every visitor and can reduce bounce, so the work pays off even where the direct ranking effect is small. We set that expectation honestly.
Why does my score differ between tools?
Lab tools like Lighthouse simulate a single load under set conditions, while Google's ranking signal uses field data from real users on real devices and networks. They often disagree. We optimize against the field data, since that's what Google actually uses, and use lab tools to reproduce and debug.
Can Core Web Vitals be fixed once and forgotten?
Not entirely. New images, third-party scripts, and design changes can regress your metrics over time. We fix the current issues and can recommend guardrails, but ongoing changes to the site mean vitals need periodic checking, especially after major updates.