Demystifying Cumulative Layout Shift with CLS Windows
As we all know, naming things is hard.
Google's Core Web Vitals are an attempt to help folks new to web performance focus on three key metrics. Not all of these metrics are easy to understand based on their names alone:
- Largest Contentful Paint (LCP) – When the largest visual element on the page renders
- First Input Delay (FID) – How quickly a page responds to a user interaction (FID will be replaced by Interaction to Next Paint in March 2024)
- Cumulative Layout Shift (CLS) – How visually stable a page is
Any time a new metric is introduced, it puts the burden on the rest of us to first unpack all the acronyms, and then explore and digest what concepts the words might refer to. This gets even trickier if the acronym stays the same, but the logic and algorithm behind the acronym changes.
In this post, we will dive deeper into Cumulative Layout Shift (CLS) and how it has quietly evolved over the years. Because CLS has been around for a while, you may already have some idea of what it represents. Before we go any further, I have a simple question for you:
How do you think Cumulative Layout Shift is measured?
Hold your answer in your head as we explore the depths of CLS. I'm interested if your assumptions were correct, and there's a poll at the bottom of this post I'd love you to answer.
Exploring performance and conversion rates just got easier
Demonstrating the impact of performance on your users – and on your business – is one of the best ways to get your company to care about the speed of your site.
Tracking goal-based metrics like conversion rate alongside performance data can give you richer and more compelling insights into how the performance of your site affects your users. This concept is not new by any means. In 2010, the Performance and Reliability team I was fortunate enough to lead at Walmartlabs shared our findings around the impact of front-end times on conversion rates. (This study and a number of other case studies tracked over the years can be found at WPOstats.)
Setting up conversion tracking in SpeedCurve RUM is fairly simple and definitely worthwhile. This post covers:
- What is a conversion?
- How to track conversions in SpeedCurve
- Using conversion data with performance data for maximum benefit
- Conversion tracking and user privacy
Farewell FID... and hello Interaction to Next Paint!
Today at Google I/O 2023, it was announced that Interaction to Next Paint (INP) is no longer an experimental metric. INP will replace First Input Delay (FID) as a Core Web Vital in March of 2024.
It's been three years since the Core Web Vitals initiative was kicked off in May 2020. In that time, we've seen people's interest in performance dramatically increase, especially in the world of SEO. It's been hugely helpful to have a simple set of three metrics – focused on loading, interactivity, and responsiveness – that everyone can understand and focus on.
During this time, SpeedCurve has stayed objective when looking at the CWV metrics. When it comes to new performance metrics, it's easy to jump on hype-fuelled bandwagons. While we definitely get excited about emerging metrics, we also approach each new metric with an analytical eye. For example, back in November 2020, we took a closer look at one of the Core Web Vitals, First Input Delay, and found that it was sort of 'meh' overall when it came to meaningfully correlating with actual user behavior.
Now that INP has arrived to dethrone FID as the responsiveness metric for Core Web Vitals, we've turned our eye to scrutinizing its effectiveness.
In this post, we'll take a closer look and attempt to answer:
- What is Interaction to next Paint?
- How does INP compare to FID?
- What is a 'good' INP result?
- Will there be differences between INP collected in RUM vs. Chrome User Experience Report (CrUX)?
- What correlation does INP have with real user behavior?
- When should you start caring about INP?
- How can you see INP for your own site in SpeedCurve?
Onward!
A Complete Guide to Performance Budgets
It's easier to make a fast website than it is to keep a website fast. If you've invested countless hours in speeding up your pages, but you're not using performance budgets to prevent regressions, you could be at risk of wasting all your efforts.
In this post we'll cover how to:
- Use performance budgets to fight regressions
- Understand the difference between performance budgets and performance goals
- Identify which metrics to track
- Validate your metrics to make sure they're measuring what you think they are – and to see how they correlate with your user experience and business metrics
- Determine what your budget thresholds should be
- Focus on the pages that matter most
- Get buy-in from different stakeholders in your organization
- Integrate with your CI/CD process
- Synthesize your synthetic and real user monitoring data
- Maintain your budgets
This bottom of this post also contains a collection of case studies from companies that are using performance budgets to stay fast.
Let's get started!
NEW! Lighthouse 10, Core Web Vitals updates, and Interaction to Next Paint
There is a lot of excitement in the world of web performance these days, and April has been no exception! At SpeedCurve, we've been focused on staying on top of the items that affect you the most.
Here is a look at what's new in SpeedCurve:
- Support for Lighthouse 10, including metric scoring changes as well as audits
- Updated RUM Core Web Vitals, including the much-anticipated addition of Interaction to Next Paint (INP)
All of this work driven by the community is having a big impact in our collective goal to make performance accessible for everyone.
Read on to learn more about these exciting changes!
Element Timing: One true metric to rule them all?
One of the great things about Google's Core Web Vitals is that they provide a standard way to measure our visitors’ experience. Core Web Vitals can answer questions like:
- When was the largest element displayed? Largest Contentful Paint (LCP) measures when the largest visual element (image or video) finishes rendering.
- How much did the content move around as it loads? Cumulative Layout Shift (CLS) measures the visual stability of a page.
- How responsive was the page to visitors' actions? First Input Delay (FID) measures how quickly a page responds to a user interaction, such as a click/tap or keypress.
Sensible defaults, such as Core Web Vitals, are a good start, but one pitfall of standard measures is that they can miss what’s actually most important.
The (potential) problems with Largest Contentful Paint
Largest Contentful Paint (LCP) makes the assumption that the largest visible element is the most important content from the visitors’ perspective; however, we don’t have a choice about which element it measures. LCP may not be measuring the most appropriate – or even the same – element for each page view.
The LCP element can vary for first-time vs repeat visitors
In the case of a first-time visitor, the largest element might be a consent banner. On subsequent visits to the same page, the largest element might be an image for a product or a photo that illustrates a news story.
The screenshots from What Hifi (a UK audio-visual magazine) illustrate this problem. When the consent banner is shown, then one of its paragraphs is the LCP element. When the consent banner is not shown, an article title becomes the LCP element. In other words, the LCP timestamp varies depending on which of these two experiences the visitor had!
What Hi Fi with and without the consent banner visible
Understanding the performance impact of anti-flicker snippets
Experimentation tools that use asynchronous scripts – such as Google Optimize, Adobe Target, and Visual Web Optimizer – recommend using an anti-flicker snippet to hide the page until they've finished executing. But this practice comes with some performance measurement pitfalls:
- Hiding the contents of the page can have a dramatic effect on the Web Vitals that measure visual experience, such as First Contentful Paint (FCP) and Largest Contentful Paint (LCP)
- Anti-flicker snippets can also affect Cumulative Layout Shift (CLS) and the synthetic equivalent of First Input Delay (FID), Total Blocking Time (TBT).
In this post we'll look at how anti-flicker snippets work, their impact on Web Vitals, and how to measure the delay they add to visitors' experience.
SEO and web performance: What to measure and how to optimize
Chances are, you're here because of Google's update to its search algorithm, which affects both desktop and mobile, and which includes Core Web Vitals as a ranking factor. You may also be here because you've heard about the most recent potential candidates for addition to Core Web Vitals, which were just announced at Chrome Dev Summit.
A few things are clear:
- Core Web Vitals, as a premise, are here to stay for a while.
- The metrics that comprise Web Vitals are still evolving.
- These metrics will (I think) always be in a state of evolution. That's a good thing. We need to do our best to stay up to date – not just with which metrics to track, but also with what they measure and why they're important.
If you're new to Core Web Vitals, this is a Google initiative that was launched in early 2020. Web Vitals is (currently) a set of three metrics – Largest Contentful Paint, First Input Delay, and Cumulative Layout Shift – that are intended to measure the loading, interactivity, and visual stability of a page.
When Google talks, people listen. I talk with a lot of companies and I can attest that, since Web Vitals were announced, they've shot to the top of many people's list of things to care about. But Google's prioritization of page speed in search ranking isn't new, even for mobile. As far back as 2013, Google announced that pages that load slowly on mobile devices would be penalized in mobile search.
Keep reading to find out:
- How much does web performance matter when it comes to SEO?
- Which performance metrics should you focus on for SEO?
- What can you do to make your pages faster for SEO purposes?
- What are some of the common issues that can hurt your Web Vitals?
- How can you track performance for SEO?
UPDATE: Bookmark and compare synthetic tests
One of the huge benefits of tracking web performance over time is the ability to see trends and compare metrics. Last year we added new functionality that makes it easy for you to bookmark and compare different synthetic tests in your test history. We recently added some additional enhancements to make comparing tests even easier.
With the 'Compare' feature, you can generate side-by-side comparisons that let you not only spot regressions, but easily identify what caused them:
- Compare the same page at different points in time
- Compare two versions of the same page – for example, one with ads and one without
- Understand which metrics got better or worse
- Identify which common requests got bigger/smaller or slower/faster
- Spot any new or unique requests – such as JavaScript and images – and see their impact on performance
Along the way, we've also made it much more intuitive for you to drill down into your detailed synthetic test results. Let's take a look...
NEW: Lighthouse v8 support!
After Google's announcement about Lighthouse 8 this past month, we have updated our test agents. We've gotten a lot of questions about what has changed and the impact on your performance metrics, so here's a summary.
Web Performance for Product Managers
I love conversations about performance, and I'm fortunate enough to have them a lot. The audience varies. A lot of the time it’s a front-end developer or head of engineering, but more and more I’m finding myself in great conversations with product leaders. As great as these discussions can be, I often walk away feeling like there was a better way to streamline the conversation while still conveying my passion for bringing fellow PMs into the world of webperf. I hope this post can serve that purpose and cover a few of the fundamental areas of web performance that I’ve found to be most useful while honing the craft of product management.
So, whether you are a PM or not, if you're new to performance I've put together a few concepts and guidelines you can refer to in order to ramp up quickly. This post covers:
- What makes a page slow?
- How is performance measured?
- What do the different metrics mean?
- Understanding percentiles and how to use them
- How to communicate performance to different stakeholders
Let's get started...
An Opinionated Guide to Performance Budgets
Performance budgets are one of those ideas that everyone gets behind conceptually, but then are challenged to put into practice – and for very good reason. Web pages are unbelievably complex, and there are hundreds of different metrics available to track. If you're just getting started with performance budgets – or if you've been using them for a while and want to validate your work – this post is for you.
What is a performance budget?
A performance budget is a threshold that you apply to the metrics you care about the most. You can then configure your monitoring tools to send you alerts – or even break the build, if you're testing in your staging environment – when your budgets are violated.
Understanding the basic premise of performance budgets is pretty easy. The tricky part comes when you try to put them into practice. This is when you run into three important questions:
- Which metrics should you focus on?
- What should your budget thresholds be?
- How do you stay on top of your budgets?
Depending on whom you ask, you could get very different answers to these questions. Here are mine.
New! Vitals Dashboard
Getting up to speed on Core Web Vitals seems to be at the top of everyone's to-do list these days. Just in time for the holidays, we are happy to bring you our new Vitals dashboard to help you get a huge jumpstart.
We love to visualize performance data (in case you haven't heard). We love it even more when we can be true to one of our biggest motivations at SpeedCurve: leveraging both RUM and Synthetic data to help you take action on what matters most.
First Input Delay: How vital is it?
We’ve been pretty vocal about Core Web Vitals since Google announced this initiative last spring. We love the idea of having a lean, shared set of metrics that we can all rally around – not to mention having a broader conversation about web performance that includes teams throughout an organization.
For many site owners, the increased focus on Core Web Vitals is driven by the fact that Google will be including them as a factor in search ranking in May 2021. Other folks are more interested in distilling the extremely large barrel of performance metrics into an easily digested trinity of guidelines to follow in order to provide a delightful user experience.
We’ve had some time to evaluate and explore these metrics, and we're committed to transparently discussing their pros and cons.
The purpose of this post is to explore First Input Delay (FID). This metric is unique among the three Web Vitals in that it is can only be measured using real user monitoring (RUM), while the other two (Largest Contentful Paint and Cumulative Layout Shift) can be measured using both RUM and synthetic monitoring.
In this post we'll cover:
- What is FID?
- What does FID look like across the web?
- The importance of measuring user interactions
- How JavaScript affects user behavior
- Suggestions for how you can look at FID in relation to your other key metrics
Let's dig in!
Cumulative Layout Shift: What it measures, when it works (and doesn't), and how to use it
Back in May, we shared that SpeedCurve supports Google's Core Web Vitals in both our synthetic monitoring and real user monitoring tools. Two of the Web Vitals – Largest Contentful Paint (LCP) and First Input Delay (FID) – were actually available in SpeedCurve for quite a while prior to the announcement. The newcomer to the scene was Cumulative Layout Shift (CLS), and, not surprisingly, it's the metric that's gotten the most questions.
A few of the questions I've been asked (or asked myself) about Cumulative Layout Shift:
- What does CLS measure?
- How is it calculated?
- What does it mean in terms of actual user experience?
- Does it correlate to user behaviour or business metrics in any measurable way?
- What are the (inevitable) gotchas?
- Ultimately, how much should we care about CLS?
Six months in, I've had a chance to gather and look at a lot of data, talk with customers, and learn from our friends in the performance community. Here's what I've learned so far.
Visualizing Layout Shifts
One of the big challenges with Google's new Cumulative Layout Shift (CLS) metric is understanding which elements actually moved on the page, when they moved, and by how much. To help with debugging your CLS scores, we've added a new visualization to SpeedCurve that shows each layout shift and how each individual shift adds up to the final cumulative metric.
For each layout shift, we show you the filmstrip frame right before and right after the shift. We then draw a red box around the elements that moved, highlighting exactly which elements caused the shift. The Layout Shift Score for each shift also helps you understand the impact of that shift and how it adds to the cumulative score.
Fast badging for better UX
Is your site fast? Adding to a string of recent announcements including Lighthouse v6 and Core Web Vitals, Google has introduced Fast page labelling in Chrome 85 for Android. If you are curious about what this means for your site and how you can get in front of it, read on!
NEW: Lighthouse v6 support!
Lighthouse v6 has arrived! The much-anticipated update to Lighthouse is now available to SpeedCurvers as part of our latest test agent updates. Keep reading to find out what this means and how it may affect your performance metrics.
Tracking Web Vitals for a better user experience
Google recently announced an initiative called 'Web Vitals', which focuses on three performance metrics they consider essential for improving the user experience:
- Largest Contentful Paint (LCP)
- First Input Delay (FID)
- Cumulative Layout Shift (CLS)
With the exception of FID, all of these metrics are available in both RUM and Synthetic. FID requires a real user for calculation and therefore is only available in RUM. In place of FID for Synthetic, we recommend tracking JS Long Tasks or Total Blocking Time as an alternative CPU metric.
User Timing Level 3: Set a value!
The Chrome team has snuck a fundamental change to how user timing marks work into Chrome 78. For many years now, our own Steve Souders has championed user timing, and he has always believed you should be able to set a value for a user timing mark or measure.
With User Timing Level 3, now you can! Level 3 lets you explicit set a startTime whereas previously you could only pass in the name of a mark.
performance.mark("name", {startTime: 1000})
