SPEED & CORE WEB VITALS

Your Core Web Vitals Are Failing, and Google Has Been Measuring It for Years

UK businesses lose search ranking and prospective customers to page speed problems that are entirely fixable. Slow Largest Contentful Paint, layout shift, and poor Interaction to Next Paint are not abstract metrics. They are reasons a visitor leaves before your page finishes loading, and reasons Google ranks a competitor above you. We audit the root causes, fix them, and show you the before and after.

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/ This is for you if

Three types of UK businesses come to us with a speed and Core Web Vitals brief.

Your rankings have declined or stalled despite consistent content work. You have not been penalised. Your backlink profile is stable. The answer is often in Page Experience signals. Google has incorporated Core Web Vitals into its ranking systems since 2021. If your LCP is slow, your CLS score is poor, or your INP on mobile is failing, you are competing at a structural disadvantage against sites that have fixed these issues. The traffic loss is not random. It has a measurable cause.

You have Google Analytics data showing that mobile visitors leave significantly faster than desktop visitors. The instinct is to blame the content or the design. In many cases, the real cause is load performance. UK mobile users are on variable 4G and 5G connections. A page that loads in two seconds on a fast office connection can take five or six seconds on a mobile network. At that load time, most visitors are already gone.

You installed a caching plugin or ran a GTmetrix report and made some changes. Scores improved temporarily, then degraded again. Or scores improved in the lab but field data in Google Search Console still showed poor performance. Lab scores and field scores measure different things. Field data from real UK users on real devices is what affects rankings. We work from field data, not just lab tools.

/ What's broken

The four performance problems we find most often in UK site audits.

LCP Is Being Pulled Down by an Unoptimised Hero Image

The Largest Contentful Paint metric measures how long it takes for the main visible content to appear. On most sites, that is a hero image or above-the-fold banner. If that image is a large JPEG served without WebP or AVIF encoding, without a preload hint, and without proper width and height attributes, LCP will be slow regardless of everything else on the page. This is the single most common LCP failure we find, and it is fixable without redesigning the page.

Third-Party Scripts Are Blocking the Main Thread

Analytics tags, chat widgets, advertising pixels, and social sharing scripts load on most business websites. When these scripts are not loaded asynchronously or deferred correctly, they block the main thread and delay the page becoming interactive. Interaction to Next Paint, which measures responsiveness to user input, is directly affected by main thread congestion. Every additional third-party tag that loads synchronously costs measurable INP performance.

Cumulative Layout Shift Is Coming from Fonts or Ads Loading Late

Layout shift happens when elements move on screen after the initial render. The most common causes are web fonts loading and swapping in after the page appears, images without declared dimensions, and above-the-fold advertisements loading in reserved but incorrectly sized containers. CLS is one of the most frustrating metrics for users because the page visually rearranges itself mid-read. It is also one of the most fixable with targeted interventions.

JavaScript Bundles Are Too Large and Not Code-Split

Many sites, particularly those built on React or other JavaScript-heavy frameworks, ship large JavaScript bundles to the browser. When the bundle is not code-split, every visitor downloads the entire application's JavaScript before the page becomes interactive. This inflates Total Blocking Time, delays INP, and creates poor mobile performance specifically because mobile CPUs process JavaScript more slowly than desktop CPUs. UK mobile users on variable 4G connections experience this most acutely.

/ What we engineer

Six technical interventions, delivered in a structured sequence with field data at the centre.

Each workstream is built by the team that audits it, and wired into the rest of your growth system.

Full Performance Audit and CrUX Field Data Analysis

We begin with field data from Google Search Console's Core Web Vitals report and Chrome User Experience Report data for your domain. Field data reflects what real UK users are experiencing, not what a test tool reports from a single controlled request. We map LCP, CLS, and INP scores by device type and page group, identify which pages are failing and by how much, and produce a prioritised fix list ordered by ranking impact and implementation effort.

Image Optimisation (WebP, AVIF, and Lazy Loading)

We audit every significant image on the site and implement WebP and AVIF encoding with correct browser fallbacks. Images that are not in the initial viewport are lazy-loaded. Hero images and above-the-fold images receive preload hints so the browser fetches them at the highest priority. Width and height attributes are declared on all images to eliminate CLS from image loading. For e-commerce sites with large catalogues, this is implemented at the build or pipeline level, not manually.

CDN Implementation and Caching Configuration

For sites not already served via a content delivery network, we implement CDN delivery with edge nodes that serve UK users from geographically appropriate points of presence. Cache headers are configured for static assets. Server response times are assessed and improved where hosting infrastructure is the bottleneck. For sites already on a CDN, we audit the caching configuration to ensure it is correctly set up rather than using default settings.

JavaScript Bundle Audit and Reduction

We audit the JavaScript payloads loaded on critical pages. Unused JavaScript is identified and removed. Where framework code allows, bundles are code-split so visitors only download what is needed for the page they are viewing. Third-party scripts are audited for loading strategy: scripts that do not need to block rendering are moved to async or deferred loading. Where a script is not providing value proportionate to its performance cost, we flag it for removal.

Font Loading and Critical CSS

Web fonts are audited for loading strategy. Font-display:swap or font-display:optional is implemented where appropriate to prevent invisible text during font load. Critical CSS, meaning the styles needed to render above-the-fold content, is inlined so the browser does not have to wait for an external stylesheet before painting. This directly improves both LCP and perceived load speed.

Before and After Scores and Monitoring Setup

Every implementation is documented with before and after Core Web Vitals scores from both field data and lab tools. We set up Google Search Console alerts and, where appropriate, a lightweight real user monitoring configuration so you have ongoing visibility into performance for your UK user base. You do not need to run another audit to know whether performance has degraded.

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/ What changes

Four things that change when Core Web Vitals are fixed properly.

Before
After
BeforeThe Largest Contentful Paint metric measures how long it takes for the main visible content to appear. On most sites, that is a hero image or above-the-fold banner. If that image is a large JPEG served without WebP or AVIF encoding, without a preload hint, and without proper width and height attributes, LCP will be slow regardless of everything else on the page. This is the single most common LCP failure we find, and it is fixable without redesigning the page.
AfterGoogle's Page Experience system uses Core Web Vitals as ranking inputs. Sites with poor LCP, CLS, or INP field data are at a disadvantage in competitive search results, all other factors being equal. When Core Web Vitals pass in field data, that disadvantage is removed. For businesses in competitive UK verticals where multiple strong sites are competing for the same positions, this is a material ranking factor.
BeforeAnalytics tags, chat widgets, advertising pixels, and social sharing scripts load on most business websites. When these scripts are not loaded asynchronously or deferred correctly, they block the main thread and delay the page becoming interactive. Interaction to Next Paint, which measures responsiveness to user input, is directly affected by main thread congestion. Every additional third-party tag that loads synchronously costs measurable INP performance.
AfterWhen pages load faster and do not shift layout mid-load, mobile visitors stay longer. UK mobile users on 4G and 5G connections are sensitive to load time. The relationship between page load speed and bounce rate is well-documented in both Google's own research and in the analytics of sites we have worked on. A two-second improvement in LCP typically produces a measurable reduction in mobile bounce rate within a few weeks of implementation.
BeforeLayout shift happens when elements move on screen after the initial render. The most common causes are web fonts loading and swapping in after the page appears, images without declared dimensions, and above-the-fold advertisements loading in reserved but incorrectly sized containers. CLS is one of the most frustrating metrics for users because the page visually rearranges itself mid-read. It is also one of the most fixable with targeted interventions.
AfterSpeed affects conversion as well as engagement. A visitor who has waited four seconds for a product page to load is less likely to add to cart than one who saw it render in under two seconds. For landing pages and checkout flows, the performance gap between a passing Core Web Vitals page and a failing one can have a direct effect on revenue per session.
BeforeMany sites, particularly those built on React or other JavaScript-heavy frameworks, ship large JavaScript bundles to the browser. When the bundle is not code-split, every visitor downloads the entire application's JavaScript before the page becomes interactive. This inflates Total Blocking Time, delays INP, and creates poor mobile performance specifically because mobile CPUs process JavaScript more slowly than desktop CPUs. UK mobile users on variable 4G connections experience this most acutely.
AfterPerformance degrades over time as new content is added, third-party scripts accumulate, and plugins are updated. The monitoring setup we implement gives you ongoing field data visibility so degradation is caught early rather than discovered during the next audit. The fix is not a single event. The monitoring makes it a continuous baseline.

/ How it works

Four stages. Field data drives every decision, from audit to sign-off.

  1. Field Data Audit and Prioritisation Week 1

    We pull Core Web Vitals field data from Google Search Console and CrUX for your domain. We identify which pages are failing, which metrics are causing the failures, and what the likely root causes are based on the data. The output is a written audit report with a prioritised fix list. Prioritisation is based on ranking impact, traffic volume affected, and implementation complexity. You receive the prioritised list before any implementation begins.

  2. Root Cause Analysis and Fix Plan Week 2

    We go into the site's code, asset pipeline, and server configuration to confirm the root causes identified in the audit. For each fix, we define the implementation approach, the expected score improvement, and any risks or dependencies. The fix plan is agreed before implementation begins. No changes are made to your site without a confirmed plan.

  3. Implementation Weeks 2–5

    We implement fixes in priority order. Image optimisation, CDN configuration, and JavaScript bundle changes are typically the highest-impact items and are addressed first. Font loading, critical CSS, and third-party script audit follow. Implementation timelines vary by site complexity and access method. We work on staging environments and move to production after verification.

  4. Verification, Documentation, and Monitoring Setup Week 5–6

    We verify improvements in both lab tools and, after sufficient time has passed, in field data. Before and after scores are documented and shared. Monitoring is configured. We provide a written summary of what was changed, why, and what the measured result was.

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/ Common questions

FAQ

Straight answers on scope, timelines and cost. Anything else, ask us directly.

Ask us directly
What is the difference between lab scores and field data scores?

Lab tools like PageSpeed Insights and GTmetrix run a simulated test from a single location on a controlled connection. Field data from CrUX and Google Search Console is aggregated from real users visiting your site on their actual devices and connections. Google uses field data, not lab scores, for ranking purposes. A site can score well in lab tests and still have poor field data if real users, particularly mobile users on variable UK 4G connections, are experiencing slow loads. We work from field data first.

Will fixing Core Web Vitals improve our search rankings?

Core Web Vitals are one input into Google's ranking systems, not the only one. Fixing failing Core Web Vitals removes a disadvantage and meets the Page Experience threshold, which is a positive ranking input. For sites currently failing field data thresholds, this typically produces ranking improvements, particularly in competitive verticals where multiple strong sites are otherwise well-matched. We do not promise specific ranking improvements. We fix measurable technical problems that are confirmed ranking inputs.

Our PageSpeed score is already above 90. Why are we still failing field data?

Lab scores and field data measure different things under different conditions. A high PageSpeed score reflects performance under ideal test conditions. Field data reflects what UK users on real devices and variable connections are experiencing. Common reasons for the gap include large images that perform well on a fast connection but slowly on 4G, JavaScript that performs well on a modern test device but slowly on mid-range mobile hardware, and third-party scripts that behave differently in production than in a sandboxed test.

How long does it take to see improvements in field data after fixes are implemented?

CrUX field data is based on a 28-day rolling window of real user visits. This means improvements in field data typically appear within four to six weeks of implementation, depending on traffic volume. Low-traffic sites take longer to update because fewer data points are collected. Google Search Console's Core Web Vitals report uses the same 28-day window. We document lab score improvements immediately after implementation and track field data over the following weeks.

Do you fix Core Web Vitals on any CMS or tech stack?

We have worked on WordPress, Shopify, Webflow, custom React and Next.js builds, and several enterprise CMS platforms. The underlying fixes, image encoding, CDN configuration, JavaScript loading strategy, and font optimisation, apply across platforms. Some platforms impose constraints on what can be changed without a rebuild. We identify those constraints in the audit stage and scope the implementation accordingly.

/ Our team

The people behind the work.

Not a black box. Real specialists you can call, with their names on the work.

About us
Hawrry Bhattarai

Hawrry Bhattarai

Google Ads Expert

LinkedIn

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If Your Core Web Vitals Are Failing in Field Data, You Are Competing at a Disadvantage

Google has been using Core Web Vitals as a ranking input since 2021. UK businesses with failing LCP, CLS, or INP field data are at a measurable disadvantage in organic search, and losing mobile visitors to slow load times before those visitors have a chance to convert. Ignited Nepal starts with a field data audit, not a lab report. We find what is actually failing for real UK users before recommending what to fix.

Ignited Nepal is a Growth Engineering Company based in Nepal, working with businesses that need technical performance to match their growth goals.
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