[{"data":1,"prerenderedAt":591},["ShallowReactive",2],{"legal-menu-en-legal":3,"cookie-texts-en":17,"header-menu-en-primary":32,"blog-en-core-web-vitals-website-performance-diagnosis":58,"blog-translations-map":546,"widgets-en":582,"social-links-footer-en":585},{"slug":4,"items":5},"legal",[6,12],{"id":7,"title":8,"url":9,"parent":10,"order":11},2130,"Privacy Policy","/en/privacy-policy/",0,1,{"id":13,"title":14,"url":15,"parent":10,"order":16},2131,"Cookie Policy","/en/cookie-policy/",2,{"title":18,"description":19,"btnAccept":20,"btnReject":21,"btnCustomize":22,"btnSave":23,"linkCookiesText":24,"linkPrivacyText":25,"catNecessaryName":26,"catNecessaryAlwaysLabel":27,"catNecessaryDesc":28,"catAnalyticsName":29,"catAnalyticsDesc":30,"manageBtn":31},"We use cookies","We use first-party and third-party cookies to analyse the use of the website...","Accept all","Only necessary","Customize","Save preferences","Cookie policy","Privacy policy","Necessary","Always active","Essential for the basic functioning of the website. They cannot be disabled.","Analytics","They help us understand how you interact with the website (Google Analytics). No personally identifiable data is collected.","Manage cookies",{"slug":33,"items":34},"primary",[35,39,43,48,53],{"id":36,"title":37,"url":38,"parent":10,"order":11},2200,"Services","#servicios",{"id":40,"title":41,"url":42,"parent":10,"order":16},2201,"Method","#proceso",{"id":44,"title":45,"url":46,"parent":10,"order":47},2202,"Data","#datos",3,{"id":49,"title":50,"url":51,"parent":10,"order":52},2203,"Technology","#tecnologias",4,{"id":54,"title":55,"url":56,"parent":10,"order":57},2126,"Blog","/en/blog/",5,{"id":59,"date":60,"date_gmt":61,"guid":62,"modified":60,"modified_gmt":61,"slug":64,"status":65,"type":66,"link":67,"title":68,"content":70,"excerpt":73,"author":11,"featured_media":75,"comment_status":76,"ping_status":77,"sticky":72,"template":76,"format":78,"meta":79,"categories":80,"tags":82,"destacado":87,"class_list":88,"acf":100,"yoast_head":101,"yoast_head_json":102,"_featured_image":201,"_links":204,"_embedded":246},3349,"2026-09-14T14:09:05","2026-09-14T12:09:05",{"rendered":63},"https://cms.tornem.net/core-web-vitals-website-performance-diagnosis/","core-web-vitals-website-performance-diagnosis","publish","post","https://cms.tornem.net/en/core-web-vitals-website-performance-diagnosis/",{"rendered":69},"Core Web Vitals without the hype: how to diagnose real website performance",{"rendered":71,"protected":72},"\u003Cp>You open \u003Ca href=\"https://pagespeed.web.dev/\">PageSpeed Insights\u003C/a>, analyse a website and get a yellow 72. You run the test again and get 84. You switch computers, repeat it and suddenly see 91. Then the questions start: is the website fast or slow? Does it need optimisation? Does that score affect SEO? Why is Google Search Console reporting problematic URLs when Lighthouse seems reasonably happy?\u003C/p>\n\u003Cp>The problem starts when we reduce website performance to a score. \u003Cstrong>Core Web Vitals are not an exam where the goal is to get 100. They are metrics designed to describe specific parts of the real user experience and, above all, they are a diagnostic tool.\u003C/strong>\u003C/p>\n\u003Cp>Understanding them properly lets us answer a much more useful question than “what score does my website get?”: \u003Cstrong>what is causing some users to have a poor experience, and where exactly is the bottleneck?\u003C/strong>\u003C/p>\n\u003Ch2>What Core Web Vitals actually are\u003C/h2>\n\u003Cp>There are currently three Core Web Vitals:\u003C/p>\n\u003Cul>\n\u003Cli>\u003Cstrong>LCP — Largest Contentful Paint:\u003C/strong> measures the perceived loading speed of the main content.\u003C/li>\n\u003Cli>\u003Cstrong>INP — Interaction to Next Paint:\u003C/strong> measures how responsive the page is to user interactions.\u003C/li>\n\u003Cli>\u003Cstrong>CLS — Cumulative Layout Shift:\u003C/strong> measures the visual stability of the interface.\u003C/li>\n\u003C/ul>\n\u003Cp>The current thresholds for a good experience are:\u003C/p>\n\u003Ctable>\n\u003Cthead>\n\u003Ctr>\n\u003Cth>Metric\u003C/th>\n\u003Cth>Good\u003C/th>\n\u003Cth>Needs improvement\u003C/th>\n\u003Cth>Poor\u003C/th>\n\u003C/tr>\n\u003C/thead>\n\u003Ctbody>\n\u003Ctr>\n\u003Ctd>\u003Cstrong>LCP\u003C/strong>\u003C/td>\n\u003Ctd>≤ 2.5 s\u003C/td>\n\u003Ctd>2.5–4 s\u003C/td>\n\u003Ctd>> 4 s\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>\u003Cstrong>INP\u003C/strong>\u003C/td>\n\u003Ctd>≤ 200 ms\u003C/td>\n\u003Ctd>200–500 ms\u003C/td>\n\u003Ctd>> 500 ms\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>\u003Cstrong>CLS\u003C/strong>\u003C/td>\n\u003Ctd>≤ 0.1\u003C/td>\n\u003Ctd>0.1–0.25\u003C/td>\n\u003Ctd>> 0.25\u003C/td>\n\u003C/tr>\n\u003C/tbody>\n\u003C/table>\n\u003Cp>There is an important detail, though: the goal is not to hit those values once on our own laptop. The assessment is designed around the experience of most users and uses the \u003Ca href=\"https://web.dev/articles/vitals\">\u003Cstrong>75th percentile\u003C/strong>\u003C/a> as its reference. In other words, roughly three out of every four user experiences should fall within the threshold considered good.\u003C/p>\n\u003Cp>That completely changes how performance should be diagnosed.\u003C/p>\n\u003Ch2>The first mistake: obsessing over the PageSpeed score\u003C/h2>\n\u003Cp>PageSpeed Insights provides a lot of useful information, but the Lighthouse score displayed so prominently tends to attract nearly all the attention. It should not.\u003C/p>\n\u003Cp>A website can achieve an excellent score in a laboratory run while still delivering a mediocre experience to a significant proportion of real users. The opposite can also happen. The reason is simple: \u003Cstrong>lab data and production data are not measuring exactly the same thing\u003C/strong>.\u003C/p>\n\u003Cp>A lab test runs under controlled conditions: a simulated device, defined network conditions and a specific page load. Real users, however, arrive with fast phones and low-end phones, Wi-Fi, fibre or poor mobile connections, browsers in different states, cold or warm caches, extensions, long sessions and completely different ways of interacting with the interface.\u003C/p>\n\u003Cp>That is why, before optimising anything, we need to understand what type of data we are looking at.\u003C/p>\n\u003Ch2>Lab data and field data are not interchangeable\u003C/h2>\n\u003Cp>This distinction is probably one of the most important ideas for interpreting Core Web Vitals correctly.\u003C/p>\n\u003Ch3>Lab data\u003C/h3>\n\u003Cp>Tools such as Lighthouse let us reproduce a page under controlled conditions and are especially useful for detecting render-blocking resources, analysing JavaScript, studying image loading, finding long tasks, comparing changes during development and preventing regressions before deployment.\u003C/p>\n\u003Cp>But a laboratory test is a \u003Cstrong>specific simulation\u003C/strong>, not the accumulated experience of your users.\u003C/p>\n\u003Ch3>Field data\u003C/h3>\n\u003Cp>Field data comes from real users. Google uses sources including the \u003Ca href=\"https://developer.chrome.com/docs/crux\">Chrome User Experience Report (CrUX)\u003C/a> to feed tools such as PageSpeed Insights and the Core Web Vitals report in Search Console.\u003C/p>\n\u003Cp>This data reflects situations that an isolated test can struggle to reproduce: slow devices, real network conditions, users who stay on a page for a long time, interactions that happen several seconds after load, personalised or third-party content, and behaviours that only appear in production.\u003C/p>\n\u003Cp>From this we can derive a useful rule of thumb: \u003Cstrong>field data helps identify the problem, while lab data helps investigate it.\u003C/strong> Mixing the two up easily leads to unnecessary optimisation work.\u003C/p>\n\u003Ch2>LCP: it is not always “the image is too large”\u003C/h2>\n\u003Cp>\u003Cstrong>Largest Contentful Paint\u003C/strong> measures how long it takes for the largest content element initially visible to the user to appear. It may be a hero image, a large text block, a background image or certain video elements.\u003C/p>\n\u003Cp>A slow LCP often creates the feeling that the page takes too long to become genuinely available, but reducing the diagnosis to “compress the image” is far too simplistic. Poor LCP can originate in several different phases.\u003C/p>\n\u003Ch3>1. The server takes too long to respond\u003C/h3>\n\u003Cp>Before displaying content, the browser needs to receive the initial document. A high TTFB can delay everything that follows, so the investigation may need to cover the backend, dynamic page generation, caching, CDN behaviour, redirects or infrastructure.\u003C/p>\n\u003Ch3>2. The browser discovers the LCP resource too late\u003C/h3>\n\u003Cp>Imagine a hero image that can only be discovered after CSS has been downloaded or JavaScript has executed. The image itself may be lightweight and still begin downloading far too late.\u003C/p>\n\u003Cp>That is a \u003Cstrong>prioritisation\u003C/strong> problem, not necessarily a file-size problem.\u003C/p>\n\u003Ch3>3. The resource takes too long to download\u003C/h3>\n\u003Cp>This is where factors such as an unnecessarily large file, an unsuitable format, dimensions larger than required, a slow server or a poorly configured CDN come into play.\u003C/p>\n\u003Ch3>4. The resource is available but takes too long to render\u003C/h3>\n\u003Cp>The image may already have been downloaded and still fail to appear because the browser is busy processing CSS, JavaScript or rendering work.\u003C/p>\n\u003Cp>A good LCP diagnosis should therefore separate, where relevant: \u003Cstrong>TTFB → resource load delay → download → render delay.\u003C/strong>\u003C/p>\n\u003Cp>The right question is not simply “how do I lower LCP?” but \u003Cstrong>“which part of LCP is costing us time?”\u003C/strong>\u003C/p>\n\u003Ch2>INP: when the website loads quickly but responds slowly\u003C/h2>\n\u003Cp>A website can appear fast when it loads and still become frustrating as soon as you start using it. You click the menu and it takes a moment to open, select an option and nothing seems to happen for a fraction of a second, type into a search box and the interface lags behind, or add something to the basket and cannot immediately tell whether the click worked.\u003C/p>\n\u003Cp>That is the territory of \u003Ca href=\"https://web.dev/articles/inp\">\u003Cstrong>Interaction to Next Paint\u003C/strong>\u003C/a>.\u003C/p>\n\u003Cp>INP analyses the latency of interactions throughout the lifetime of the page and aims to represent how consistently responsive the interface feels. It is not limited to the first click after loading, which matters because a page can load perfectly well and then degrade afterwards.\u003C/p>\n\u003Cp>Common causes include excessively long JavaScript tasks, too much work on the main thread, expensive event listeners, unnecessary rendering, an excessively large DOM, third-party scripts, synchronous calculations or heavy hydration in certain applications.\u003C/p>\n\u003Ch3>Lighthouse cannot measure your users’ real INP\u003C/h3>\n\u003Cp>Lighthouse performs an automated page load without a real user interacting throughout the session. It therefore cannot measure INP in the same way that field data can.\u003C/p>\n\u003Cp>In the lab, other signals such as \u003Cstrong>Total Blocking Time (TBT)\u003C/strong> are used to identify problems that may ultimately affect INP. But TBT and INP are not the same metric: a good TBT can be a useful clue, while real INP still requires real user interactions.\u003C/p>\n\u003Ch2>CLS: a website that moves around also feels slow\u003C/h2>\n\u003Cp>\u003Ca href=\"https://web.dev/articles/cls\">\u003Cstrong>Cumulative Layout Shift\u003C/strong>\u003C/a> measures unexpected movement of visible elements. You have almost certainly experienced it: you are about to click a button and another element suddenly appears above it; you are reading a paragraph and half the page jumps down; you try to open a link and end up clicking an advert because the content moved.\u003C/p>\n\u003Cp>This type of experience is not about waiting three seconds for a page to load, but it has a great deal to do with perceived performance.\u003C/p>\n\u003Cp>Typical causes include images without reserved space, videos or iframes without dimensions, banners added after load, dynamic advertising, third-party widgets, fonts that significantly alter text dimensions, or content inserted by JavaScript ahead of elements that are already visible.\u003C/p>\n\u003Cp>In this case, optimisation often comes down to something very concrete: \u003Cstrong>give the layout stability before the content arrives.\u003C/strong>\u003C/p>\n\u003Ch2>How to diagnose Core Web Vitals without optimising blindly\u003C/h2>\n\u003Cp>A serious diagnosis should follow a clear order.\u003C/p>\n\u003Ch3>1. Start with real-world data\u003C/h3>\n\u003Cp>First establish which Core Web Vital is failing, whether the problem affects mobile, desktop or both, which set of URLs is affected, whether enough field data is available and whether the problem is persistent or temporary.\u003C/p>\n\u003Cp>Search Console and PageSpeed Insights are good starting points. Do not start digging through the code looking for something to optimise yet: first identify \u003Cstrong>which experience is actually failing\u003C/strong>.\u003C/p>\n\u003Ch3>2. Look for patterns across pages\u003C/h3>\n\u003Cp>If twenty URLs show a similar LCP and they all share the same template, you probably do not have twenty different problems. You have a template problem.\u003C/p>\n\u003Cp>This is particularly useful for ecommerce sites, blogs, product pages, directories, multilingual websites and applications with reusable layouts. Grouping pages before investigating can save a huge amount of work.\u003C/p>\n\u003Ch3>3. Reproduce the problem in the lab\u003C/h3>\n\u003Cp>Once you know what you are looking for, DevTools, Lighthouse and the Performance panel become genuinely useful.\u003C/p>\n\u003Cp>You are no longer asking “what can I optimise?” You are asking something much more precise: \u003Cstrong>“why does this template have a high LCP on mobile?”\u003C/strong> or \u003Cstrong>“which task blocks the next frame when the user opens this menu?”\u003C/strong>\u003C/p>\n\u003Cp>That change in question is the difference between measuring and diagnosing.\u003C/p>\n\u003Ch3>4. Identify the cause, not the symptom\u003C/h3>\n\u003Cp>An automated recommendation might say “reduce unused JavaScript”. That may be correct, but it still does not explain what is causing the problem.\u003C/p>\n\u003Cp>You could have 300 KB of unnecessary JavaScript and find that removing it barely changes the Core Web Vital that is actually failing. Performance optimisation is not about completing a checklist of suggestions; it is about finding which resource, task or architectural decision is driving the problematic metric.\u003C/p>\n\u003Ch3>5. Fix one cause and measure again\u003C/h3>\n\u003Cp>Optimisations should be tied to a hypothesis.\u003C/p>\n\u003Cp>For example: the hero is discovered late because it is loaded as a background image from a secondary CSS file. The intervention would be to expose the resource earlier to the browser and adjust its priority. The expected result would be a reduction in the delay before the LCP resource begins downloading.\u003C/p>\n\u003Cp>That is far more useful than installing three optimisation plugins and celebrating a nine-point PageSpeed improvement without knowing why.\u003C/p>\n\u003Ch2>Do not chase a 100 in Lighthouse\u003C/h2>\n\u003Cp>A score of 100 can be satisfying, but it should not be the goal of the project. Beyond a certain point, chasing a perfect score can mean spending many hours on changes that users will barely notice.\u003C/p>\n\u003Cp>It can even lead to poor decisions: removing useful functionality, lazy-loading everything without judgement, delaying scripts that the interface genuinely needs, unnecessarily complicating the architecture or introducing hacks designed specifically to satisfy an audit.\u003C/p>\n\u003Cp>The real goal should be different: \u003Cstrong>users should experience a fast, stable and responsive website consistently.\u003C/strong>\u003C/p>\n\u003Cp>The metrics exist to help us assess that. Not the other way around.\u003C/p>\n\u003Ch2>Do not optimise only the homepage either\u003C/h2>\n\u003Cp>Another common mistake is to analyse only the homepage. A website may have a highly optimised front page while still containing slow product pages, category pages with too much JavaScript, blog posts with huge images, forms with poor INP or layouts that generate CLS.\u003C/p>\n\u003Cp>Users do not experience “the website” as a single URL. They experience individual pages.\u003C/p>\n\u003Cp>That is why it makes more sense to diagnose \u003Cstrong>templates, page types and user journeys\u003C/strong>, rather than an isolated snapshot of the homepage.\u003C/p>\n\u003Ch2>Core Web Vitals and SEO: important, but not magic\u003C/h2>\n\u003Cp>\u003Ca href=\"https://developers.google.com/search/docs/appearance/core-web-vitals\">Google recommends achieving good Core Web Vitals\u003C/a> both for user experience and for success in Search, and these signals form part of the broader set of page-experience considerations.\u003C/p>\n\u003Cp>That does not mean reducing LCP from 2.8 to 2.4 seconds will automatically move a website ten positions higher in Google.\u003C/p>\n\u003Cp>A fast page does not replace relevant content, solid information architecture, correct indexing, authority, search-intent alignment or properly implemented technical SEO.\u003C/p>\n\u003Cp>Core Web Vitals should not be treated as an SEO trick either. They are first and foremost a useful way to detect poor experiences, and fixing a poor experience is already a good reason to work on them.\u003C/p>\n\u003Ch2>So when is it worth intervening?\u003C/h2>\n\u003Cp>When real-world data shows a consistent problem, when an entire template is affecting a meaningful proportion of users, when interactions feel sluggish, when content jumps around, when the main content takes too long to appear or when a recent regression has made previously healthy metrics worse.\u003C/p>\n\u003Cp>What makes much less sense is spending hours optimising a metric that is already green just to make a circle change from 97 to 100.\u003C/p>\n\u003Ch2>Measuring performance is easy. Diagnosing it is different.\u003C/h2>\n\u003Cp>Today, anyone can enter a URL into PageSpeed Insights and receive a list of recommendations. The difficult part starts afterwards.\u003C/p>\n\u003Cp>You need to distinguish symptoms from causes, lab data from production data, individual URLs from template patterns, meaningful optimisation from cosmetic changes, and technical metrics from the real user experience.\u003C/p>\n\u003Cp>That is where Core Web Vitals stop being three acronyms and start becoming genuinely useful.\u003C/p>\n\u003Cp>\u003Cstrong>Good optimisation does not begin by trying to achieve better numbers. It begins by understanding why those numbers are poor.\u003C/strong>\u003C/p>\n\u003Cp>And when the diagnosis is correct, you often do not need twenty changes. You need the two or three changes that actually matter.\u003C/p>\n\u003Ch2>Does your website have Core Web Vitals problems and you do not know where they come from?\u003C/h2>\n\u003Cp>At Tornem, we build and optimise web projects by analysing the problem at implementation level, not simply by looking at an automated score.\u003C/p>\n\u003Cp>If Search Console reports Core Web Vitals problems, PageSpeed gives contradictory results or a website simply does not respond as it should, \u003Ca href=\"https://tornem.net/en/#contacto\">we can investigate what is happening and prioritise the improvements that will genuinely make a difference\u003C/a>.\u003C/p>\n\u003Cp>Because making a website faster is not about chasing a 100. It is about understanding \u003Cstrong>what is slowing the experience down and fixing it in the right place\u003C/strong>.\u003C/p>\n",false,{"rendered":74,"protected":72},"\u003Cp>A poor Core Web Vital is not fixed by chasing a 100 in PageSpeed. Learn how to interpret LCP, INP and CLS, find the real cause and decide what is actually worth optimising.\u003C/p>\n",3353,"","open","standard",{"_acf_changed":72,"inline_featured_image":72,"footnotes":76},[81],101,[83,84,85,86],283,122,260,155,[],[89,66,90,91,92,93,94,95,96,97,98,99],"post-3349","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-web-development","tag-core-web-vitals-en","tag-user-experience","tag-web-development","tag-web-performance",[],"\u003C!-- This site is optimized with the Yoast SEO plugin v28.4 - https://yoast.com/product/yoast-seo-wordpress/ -->\n\u003Ctitle>Core Web Vitals: how to diagnose your website | Tornem\u003C/title>\n\u003Cmeta name=\"description\" content=\"Learn how to diagnose Core Web Vitals properly: LCP, INP and CLS, real-user data versus lab tests, and how to prioritise improvements without optimising blindly.\" />\n\u003Cmeta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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