How We Run a Core Web Vitals Audit: From Lighthouse Scores to Real-User Data

A real CWV audit starts with users, not tools. We combine field data, lab analysis, and architecture review to prioritize impact.

How We Run a Core Web Vitals Audit

From Lighthouse Scores to Real-User Data

Why Core Web Vitals audits often fail in practice

Many websites technically "pass" Core Web Vitals - yet still feel slow, unstable, or frustrating to use. At the same time, other sites fail Lighthouse scores but perform well in real life.

The reason is simple: Core Web Vitals are user experience signals, not synthetic test scores.

A meaningful audit cannot rely on a single tool or snapshot. It must combine lab data, real-user data, and architectural analysis.

What Core Web Vitals actually measure

Google's Core Web Vitals focus on three metrics:

  • LCP (Largest Contentful Paint) - how fast the main content becomes visible.
  • INP (Interaction to Next Paint) - how responsive the page is to user interactions.
  • CLS (Cumulative Layout Shift) - how visually stable the layout is during loading.

These metrics do not measure "speed" in isolation - they measure perceived quality of experience.

Why Lighthouse alone is not enough

Lighthouse provides lab data:

  • controlled environment,
  • simulated device and network,
  • single-page snapshots.

This is useful for debugging, but it does not represent:

  • real devices,
  • real networks,
  • real user behavior,
  • logged-in states,
  • cookie and consent logic.

Relying on Lighthouse alone often leads to:

  • optimizing the wrong things,
  • chasing scores instead of impact,
  • regressions in real usage.

Step 1: Understand the business context

Before looking at metrics, we clarify:

  • Which pages are entry points?
  • Which pages generate leads or revenue?
  • Which audiences matter (mobile vs desktop, region, device)?

Core Web Vitals optimization without context leads to wasted effort.

Step 2: Analyze real-user data (RUM)

We prioritize field data, typically from:

  • Google Search Console (CWV report),
  • Chrome User Experience Report (CrUX),
  • GA4 performance events (where available).

This tells us:

  • which pages actually fail CWV,
  • on which devices,
  • for which users,
  • and how consistently.

A page that fails CWV for 5% of users needs a different approach than one failing for 60%.

Step 3: Identify patterns, not isolated scores

Instead of fixing individual URLs, we look for patterns:

  • layout-level issues,
  • shared components,
  • global scripts,
  • design system constraints.

Core Web Vitals problems are rarely page-specific - they are architectural.

Step 4: Controlled lab testing

Only after understanding real-user behavior do we use:

  • Lighthouse,
  • WebPageTest,
  • browser performance profiles.

Here we answer why a metric fails:

  • What blocks LCP?
  • What causes long tasks affecting INP?
  • What triggers layout shifts?

Lab tools explain causes - not impact.

Step 5: Map issues to root causes

Typical root causes include:

  • oversized JS bundles,
  • late-loading fonts or images,
  • heavy third-party scripts,
  • hydration delays,
  • unstable layout components,
  • unscoped CSS.

Each issue is mapped to:

  • affected pages,
  • affected metrics,
  • estimated business impact.

Step 6: Prioritize fixes realistically

Not all CWV issues deserve equal attention.

We prioritize based on:

  • user impact,
  • SEO importance of pages,
  • effort vs gain,
  • risk of regression.

The goal is meaningful improvement, not perfect scores.

Step 7: Validate with real users

After changes:

  • we monitor CWV field data,
  • check trends, not snapshots,
  • confirm improvements persist across devices.

Core Web Vitals optimization is iterative, not one-off.

How this impacts SEO and conversion

Proper CWV improvements typically lead to:

  • better mobile engagement,
  • lower bounce rates,
  • higher form completion,
  • more stable rankings over time.

Google rewards consistency and quality - not temporary score spikes.

Key takeaway

A real Core Web Vitals audit:

  • starts with users, not tools,
  • combines field data and lab analysis,
  • focuses on root causes,
  • prioritizes business impact.

Optimizing for Lighthouse alone is easy. Optimizing for users - and search engines - requires method.