Keep Core Web Vitals strong for search and conversions.

Frequently asked questions about Core Web Vitals monitoring

What are Core Web Vitals?

Core Web Vitals are three performance metrics that Google uses as ranking signals: LCP (Largest Contentful Paint) measures loading speed, INP (Interaction to Next Paint) measures responsiveness, and CLS (Cumulative Layout Shift) measures visual stability. Pages that score 'Good' on all three may rank higher than equivalent pages with 'Poor' scores.

Does AuditJet monitor Core Web Vitals automatically?

Yes. AuditJet runs automated Lighthouse scans of your pages on an hourly schedule, tracking LCP, INP, CLS, TTFB, and FCP over time. When any metric regresses below your configured threshold — for example after a deploy — it sends an alert to your team via Slack or email with the specific page, metric, and magnitude of the drop.

What happens if my Core Web Vitals score drops?

A sustained drop in Core Web Vitals scores can reduce your pages' search rankings in Google, as CWV are an active ranking signal. It can also hurt conversion rates — Google's research shows each additional second of LCP reduces conversions by approximately 7%. AuditJet catches regressions within hours so your team can fix them before sustained damage to rankings and revenue.

How do I improve my Core Web Vitals score?

The fixes depend on which metric is failing. For LCP: add priority/fetchpriority to your hero image, reduce TTFB with edge caching, and eliminate render-blocking resources. For INP: use React's startTransition to defer non-urgent renders and avoid synchronous DOM reads in event handlers. For CLS: set explicit width/height on all images and never inject content above the fold after page load.

What is the difference between lab data and field data for Core Web Vitals?

Lab data is collected in a controlled environment using tools like Lighthouse, which simulates a page load under fixed network and CPU conditions — AuditJet uses this for its hourly automated scans. Field data, also called Real User Monitoring (RUM), captures how actual visitors experience your page across their real devices and connections. AuditJet combines both: lab scans detect regressions quickly after deploys, while the RUM script tag captures real-world distributions so you can validate that lab improvements translate to genuine user experience gains.

How does AuditJet's Core Web Vitals monitoring differ from Google Search Console?

Google Search Console reports Core Web Vitals from CrUX (Chrome User Experience Report), which aggregates real-user data over a 28-day rolling window — meaning it reflects the past, not the present. By the time a regression appears in Search Console, your rankings may already be affected. AuditJet runs Lighthouse scans hourly and alerts your team within minutes of a threshold breach, giving you the ability to catch and fix issues before they show up in Google's data. AuditJet also provides per-page breakdowns and AI-generated fix blueprints, which Search Console does not offer.

What causes Core Web Vitals regressions after a deploy?

Common post-deploy regression causes include: newly introduced render-blocking JavaScript or CSS bundles that delay LCP, layout shifts caused by dynamically injected banners or font swaps that inflate CLS, heavier above-the-fold images without explicit dimensions, and new third-party scripts (analytics, chat widgets) that block the main thread and hurt INP. AuditJet compares your latest scan against the pre-deploy baseline and flags exactly which metric changed and by how much, so engineers know precisely where to look rather than auditing the entire release.

How long does it take to see Core Web Vitals improvement after fixing LCP?

In lab data — like AuditJet's hourly Lighthouse scans — improvements are visible immediately after the fix is deployed, often within the next scan cycle. However, Google's field data in Search Console updates on a 28-day rolling basis, so ranking improvements tied to better CWV scores typically appear four to six weeks after the fix goes live. AuditJet's historical charts let you pinpoint the exact scan where LCP crossed back below the 2.5-second Good threshold, giving you a verifiable timestamp to share with stakeholders while awaiting the downstream ranking effects.