Performance & Security

Core Web Vitals, fixed at the cause.

We find out why your pages feel slow or jumpy for real visitors. Then we fix the cause and track the real data until the change shows.

What is Core Web Vitals optimization?

Core Web Vitals optimization brings three measures of real visits into the good range. LCP (how fast the main content appears) should be within 2.5 seconds. INP (how fast a tap gets a response) should be 200 milliseconds or less. CLS (how much the layout jumps) should be 0.1 or less. ASquared Creatives fixes each cause and re-checks.

A schematic of what each Core Web Vital watches, one frame each: the largest element to appear (LCP), the response to an interaction such as applying a filter (INP), and space reserved for an image so content holds its position while the page loads (CLS). It names the metrics only. It is not a screenshot, it measures no page, and it contains no real data.
01/WHAT YOU GET

What you get.

  • Real visitor data per page type, where available
  • Each failing measure traced to its cause
  • A fix list ordered by pages affected
  • Fixes made in code, templates or settings
  • A speed budget checked before every release
  • Search Console validation tracked for 28 days

A good fit for

  • Sites flagged poor or needing improvement in Search Console
  • Teams with good lab scores but failing real-visitor data
  • Sites where tags slow down taps or the layout jumps
02/HOW IT WORKS

How the work runs.

  1. Read the field data

    We start with Search Console and PageSpeed Insights to see which measure fails for real visitors.

  2. Attribute

    We split each failing measure into its parts to find exactly what is slow.

  3. Reproduce in the lab

    We recreate the problem in Chrome developer tools, so a fix can be tested in minutes.

  4. Fix the cause

    We change what causes it: image sizing, fonts, scripts, server response or the page template.

  5. Verify and gate

    We test each fix before release and add a speed check, so later changes cannot quietly undo it.

  6. Confirm in the field

    We watch real visitor data until it moves, because only that shows what visitors experience.

03/PROBLEMS

What we fix.

  • Problem

    The main content shows up late

    What we do

    We load the main image early and at the right size, and remove files that hold it back.

  • Problem

    Taps and clicks feel slow

    What we do

    We split, defer or remove the heavy scripts, including third-party tags, that delay each tap.

  • Problem

    The page jumps while it loads

    What we do

    We reserve space for images and embeds, and match fallback fonts to the size of the real font.

04/COMPARISON

Field data or lab data: which answers what?

PageSpeed Insights reports both. Field data decides whether a page passes; lab data explains why and tests a fix.
QuestionField dataLab data
Where it comes fromReal visits in Chrome browsers.One simulated load on one device and network.
Time it coversThe previous 28 days of visits.Only the moment the test runs.
Decides pass or failYes. Search Console and the assessment use it.No. Lighthouse gives a diagnostic score only.
Best used forChoosing what to fix, and confirming a fix worked.Finding the cause, and testing a change before release.
05/QUESTIONS

Frequently asked questions

Do Core Web Vitals affect Google rankings?

Core Web Vitals are used by Google ranking systems, but there is no single signal, and Google Search still seeks to show the most relevant content even when page experience is sub-par. Good results in the Search Console report do not guarantee top rankings. The stronger reason to fix them is what they describe: pages that load, respond and hold still.

Can you guarantee that my pages will pass?

No. A passing assessment depends on field data from real visitors, their devices and networks, and on pages having enough traffic to be measured at all. What we commit to is diagnosis from that data, fixes aimed at the causes it shows, verification in the lab, and monitoring until the field data reflects the change.

How long until Search Console shows the improvement?

Weeks rather than days. Field data covers the previous 28 days of visits, so a fix is only fully reflected once four weeks of visits have happened after it shipped. When validation is requested in the Search Console Core Web Vitals report, Google runs a 28-day monitoring session before reporting whether the issue is fixed.

Do third-party scripts affect Core Web Vitals?

They can. Tag managers, chat widgets, review embeds and advertising scripts run on the same main thread as the site, so their long tasks can delay interactions and hold back rendering, and elements they inject can shift the layout. Each script is reviewed for what it costs and whether it should stay, be deferred or be removed.

Do we need to rebuild the site to pass Core Web Vitals?

Not as a first step. Many causes sit in images, fonts, scripts, templates or server response and can be fixed in place. A rebuild becomes the honest recommendation only when the platform itself ships more work than tuning can remove, and in that case the measurements from this work shape the new build.

06/THE FULL DETAIL

The full detail.

Short answers are above. Open a panel below for the specifics: how we decide, what is included and the deeper questions.

Is this the right choice?

  • Choose Core Web Vitals optimization when field data fails.

    If Search Console or PageSpeed Insights field data shows URLs as poor or needing improvement, the problem is measurable, and this is the work that addresses it.

  • Choose technical SEO when pages are missing from the index.

    A slow page can still be indexed and ranked. When pages are not being indexed at all, crawling and rendering come first, and speed work follows.

  • Choose a rebuild when the platform itself is the bottleneck.

    When a theme or framework ships more JavaScript than any tuning can remove, website redesign and modernization is the honest answer, informed by these measurements.

Why do PageSpeed Insights and Search Console disagree?

PageSpeed Insights shows two different things: field data from the Chrome User Experience Report and a Lighthouse lab test run once on a simulated device. Search Console uses the same field data but groups similar URLs together. A high lab score beside failing field data means real visits differ from the test in device, network, cache state or interaction.

PageSpeed Insights passes the Core Web Vitals assessment when the 75th percentile of all three metrics is good over the previous 28-day collection period. Lighthouse produces a separate score weighted across five lab metrics, so a perfect Lighthouse score does not mean the field assessment passes.

Search Console groups URLs that look similar and reports each group by its poorest metric. Pages with too little traffic may have no field data of their own, because the Chrome User Experience Report only includes pages that are publicly discoverable and sufficiently popular, and Search Console then reports them within a broader origin group.

What slows Largest Contentful Paint down?

Largest Contentful Paint is slowed in one or more of four parts: the server responds late, the browser discovers the LCP resource late, the resource takes long to download, or rendering is delayed after it arrives. As a rough guide, most of the time should go to server response and download, with discovery and render delay kept small.

  • Time to First Byte: the server, redirects and caching.
  • Resource load delay: an LCP image found late, for example only in CSS or JavaScript.
  • Resource load duration: file size, image format and delivery distance.
  • Element render delay: render-blocking CSS, JavaScript or fonts after the file arrives.

Is the LCP element always an image?

No. Largest Contentful Paint measures when the largest image or text block in the viewport renders, so the element can be a heading or a paragraph, in which case the work is server response, render-blocking resources and font loading rather than image compression. Identifying the element comes before optimizing anything.

What makes Interaction to Next Paint slow?

Interaction to Next Paint is slow when the main thread is busy. Each interaction has three phases: input delay while earlier tasks finish, processing time for the event handlers, and presentation delay before the next frame is painted. Any task longer than 50 milliseconds counts as a long task, and long tasks hold interactions back.

INP observes the latency of clicks, taps and key presses throughout a visit and, for most pages, reports the interaction with the worst latency, so one heavy handler on one control can fail the metric for the whole page. On pages with many interactions, the calculation ignores one of the highest for every 50. Hovering, zooming and scrolling are not counted. Good is 200 milliseconds or less, and anything above 500 milliseconds is poor.

Common fixes include splitting the work in event handlers into separate tasks, doing as little work in each handler as possible, deferring work that is not needed before the next frame, and keeping the DOM small so rendering after an update stays quick. Third-party tags are part of the review, because their tasks run on the same main thread as the site.

What causes layout shift, and how is it prevented?

Layout shift happens when visible content moves after it has painted without the visitor causing it. The most common causes are images, ads, embeds and iframes without dimensions, dynamically injected content, and web fonts that render at a different size from their fallback. Reserving space and adjusting fallback font metrics are among the standard fixes.

  • Explicit width and height, or an aspect ratio, on every image, video and iframe.
  • Reserved space for embeds, ads and banners before they load.
  • No content inserted above what the visitor is already reading.
  • Fallback fonts adjusted with size-adjust and ascent and descent overrides.
  • Animations that use transform and opacity instead of layout properties.

Does a layout shift right after a click count against CLS?

Not when it follows closely. Layout shifts within 500 milliseconds of a user input are flagged so they can be excluded from the calculation, because the visitor asked the page to change. Shifts caused by content arriving late, with no interaction, are what the metric counts.

Which Core Web Vitals problem should be fixed first?

Fix the metric that fails on the page types with the most traffic first, starting with causes that affect every page built from the same template. A fix in a shared template, font setup or tag manager reaches every URL built on it, while a fix on a single page reaches only that page.

Within a failing page type, the work is ordered by how directly each cause moves the 75th percentile: for LCP, the part of the timing that takes longest; for INP, the slowest interactions visitors actually use; for CLS, the largest shifts.

Work that improves a lab score without touching the failing field metric is postponed, however easy it looks.

Everything included

  • Core Web Vitals optimization
  • Largest Contentful Paint diagnosis
  • Interaction to Next Paint diagnosis
  • Cumulative Layout Shift elimination
  • Field and lab measurement

How a Core Web Vitals problem gets fixed.

Every fix follows the same four steps, from field data back to field data. Skipping the first step is how a team spends weeks improving a lab score while the metric that fails stays exactly where it was.

  1. 01

    Field data

    Search Console and PageSpeed Insights show which metric fails, on which page type, for real visitors.

  2. 02

    Attribution

    The failing metric is split into its parts to find the element, request or script responsible.

  3. 03

    Lab reproduction

    The cause is reproduced in DevTools on a throttled profile, so a fix can be tested quickly.

  4. 04

    Fix and field re-check

    The fix ships, Search Console validation starts, and field data confirms the change over 28 days.

A simplified model of the diagnostic sequence. Pages with too little traffic may have no field data at all, in which case diagnosis relies on lab data, and a passing result is never guaranteed.

Why it matters

  • Work aimed at the metric that fails

    Field data shows which metric fails on which page type, so effort goes to the real problem instead of a lab score.

  • Causes fixed, not symptoms

    Attribution names the element, request or script responsible, so the fix holds instead of trading one metric against another.

  • Pages that load, respond and hold still

    Content appears sooner, controls answer sooner and nothing jumps under a finger or a cursor, which is exactly what the three metrics describe.

  • Results that survive the next release

    A budget and a release check catch regressions before they reach visitors, rather than after the field data drops again.

Where it applies

  • A marketing site with a slow hero

    The largest element is a hero image discovered late. Loading it early, sizing it correctly and removing render-blocking work brings LCP forward.

  • A store with heavy third-party tags

    Tag managers, review widgets and chat scripts create long tasks. Deferring, removing or rescheduling them is what moves INP.

  • A content site with shifting layouts

    Embeds and web fonts push text down after paint. Reserved space and adjusted fallback font metrics remove the shift.

Technology and approach

  • Field data from the Chrome User Experience Report, read through Search Console and PageSpeed Insights, is the measure of success; lab tools find and test causes.
  • A Lighthouse page load involves no user input, so it cannot measure Interaction to Next Paint; responsiveness is investigated through Total Blocking Time in the lab and real interactions in DevTools.
  • The LCP element is identified before anything is optimized, because it can be a heading or a block of text rather than the image a team expects.
  • Images carry explicit width and height and modern formats such as WebP or AVIF, and only the LCP image is loaded with priority, never lazily.
  • Web fonts are self-hosted, preloaded where they are critical, and paired with fallback faces whose metrics are adjusted to the real font.
  • Server response is its own subject: as a rough guide, most sites should aim for a Time to First Byte of 0.8 seconds or less, and TTFB is not a Core Web Vital.
07/RELATED

Related services

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