2. Key and Terms
PS is end-reports on the user experience of a page on both mobile and desktop devices, and provides
suggestions on how that page may be improved.
3. Important Point
PS provides both lab and field data about a page. Lab data is useful for debugging issues, as it is collected in a
controlled environment. However, it may not capture real-world bottlenecks. Field data is useful for capturing
true, real-world user experience - but has a more limited set of metrics.
Field Data
Lab Data
4. Field Data
Real-user experience data in PSI is powered by the Chrome User Experience Report (CrUX) dataset. PSI
reports real users' First Contentful Paint (FCP), First Input Delay (FID), Largest Contentful Paint (LCP),
Cumulative Layout Shift (CLS), and Interaction to Next Paint (INP) experiences over the previous 28-day
collection period. PSI also reports experiences for the experimental metric Time to First Byte (TTFB).
PSI sets the following thresholds in alignment with the Web Vitals initiative
5. Lab Data
PSI uses Lighthouse to analyze the given URL in a simulated environment for the Performance, Accessibility,
Best Practices, and SEO categories. It provides detailed resources management that used by a page when
window-load-time.
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Key points:
1. This is show how long it takes for a webpage to be full
rendered. It purely depends on page size and
resources management. It exclude external facor like
connection and server execute time.
2. It shows all the proccess that need to be done when
page load time.
3. It show every category’s time.
6. Is Web Core Vitals dictate load time of a web page?
Basically yes. Based on what web dev by google, the web vitals play a big role to measure how much a
good website is in terms of speed. But in the modern web app, user experience is the main concern
where sometimes it cost the key-metrix values. There are 2 metrix to dictate a good website;
Performance score (from pagedev), and page load time (from gtmetrix or similar tool). Let’s take a look
at at some examples of modern/popularwebsite Indonesia.
shopee.co.id tiket.com tokopedia.com
7. FAQs
Why improving lab data score is not directly affect the page load time?
Answer:
Variability in performance measurement is introduced via a number of channels with different levels of impact.
Several common sources of metric variability are local network availability, client hardware availability, and
client resource contention.
Resources management is also a big part to measure how performancer can affect the page load time. Lets take
a look at current examples:
8. FAQs
This is how third-party resources affect the
performance of page load. This is based on the
client side, it means measured by user’s browser.
However; user’s location, user’s network and
user’s device will dictate the time needed by
every resources to be loaded. Example; maybe
iPhone 14 will have less time GTM loaded since
it has more processor to rendered Main-Thread
resource over than iPhone 11.
9. FAQs
Is removing unused resources will improve page load time?
Answer:
Yes, definitely. Unused resources will still takes time to be loaded into a page while maybe it is not used by the
page itself. Let’s took an example:
Based on above resources management, Web vital core metrics shows how much script resources used and
unused when a specific page loaded. However; to know exactly which coded that need to be removed is
impossible by Web Vitals core metrix unless it removed when develop the scripts. And also Web vital score can
not dictate how much it will reduce page load time since it “Time” is affected by so many factors.
10. FAQs
What device and network conditions does Lighthouse use to simulate a page load?
Answer:
Currently, Lighthouse simulates the page load conditions of a mid-tier device (Moto G4) device on a mobile
network for mobile, and an emulated-desktop with a wired connection for desktop. PageSpeed also runs in a
Google datacenter that can vary based on network conditions, you can check the location that the test was by
looking at the Lighthouse Report's environment block:
11. FAQs
Why do the field data and lab data sometimes contradict each other?
Answer:
The field data is a historical report about how a particular URL has performed, and represents anonymized
performance data from users in the real-world on a variety of devices and network conditions. The lab data is
based on a simulated load of a page on a single device and fixed set of network conditions. As a result, the values
may differ. See Why lab and field data can be different (and what to do about it) for more info.