Lab data vs field data
Lab data from Lighthouse doesn't match field data because lab tests use controlled conditions, while field data comes from real users with varied devices and internet speeds. Lighthouse or reshepe speed insights are lab-based tools that run tests in a set environment. Field data, on the other hand, comes from actual visitors to a website.
We use both types of data to get a full picture of website performance. Lab data helps us spot issues and test fixes. Field data shows us how the site works for real people. By looking at both, we can make websites faster and better for everyone.
Lab data and field data offer different approaches to measuring website performance. Each method has its own strengths and limitations.
reshepe speed insights is a lab-based tool that runs tests in a controlled environment. It simulates page loads under specific conditions.
Field data, on the other hand, comes from actual visitors to a website. It provides a more accurate representation of how a website performs under real-world conditions. We can measure real-world performance using reshepe web vitals, which is a tool that measures key metrics like Largest Contentful Paint (LCP), First Contentful Paint (FCP), Interaction to Next Paint (INP), Cumulative Layout Shift (CLS), and Time to First Byte (TTFB) out of the box.
We can think of lab data as a snapshot, while field data is more like a long-term study. Both help us understand website performance, but in different ways
Comparative Advantages
Lab data shines in its ability to provide on-demand testing. We can run it anytime to check how changes affect performance
It offers detailed insights into specific elements slowing down a page. This makes it great for debugging and optimization
Meanwhile, field data's strength lies in its real-world nature. It shows how a site performs across various devices and network conditions. This gives us a more accurate picture of the user experience
Accuracy and Relevance
Field data is often seen as more accurate. It reflects actual user experiences rather than simulated conditions.
Meanwhile, Lighthouse data is highly relevant for developers. It helps pinpoint specific issues and test fixes quickly.
Core Web Vitals can show different results in lab versus field data. For example, Largest Contentful Paint might be worse in Lighthouse tests than in real-world usage
These differences highlight why we need both types of data. They each provide valuable insights that help us improve website performance.
Understanding Core Web Vitals
Core Web Vitals are key metrics that measure a website's user experience. These metrics focus on loading speed, interactivity, and visual stability. We'll explore the three main Core Web Vitals and how they impact website performance.
Largest Contentful Paint (LCP)
LCP measures how quickly the main content of a web page loads. It's a key indicator of loading performance. A good LCP score is 2.5 seconds or less.
LCP looks at the largest element visible in the viewport. This could be an image, video, or block of text. Faster LCP times mean users can see and interact with content sooner.
Keep in mind that lab data often shows worse LCP scores than field data. This is because lab tests may use different network conditions than real users experience
First Input Delay (FID)
FID measures how quickly a website responds to user interactions. It's crucial for a good user experience. A low FID score means the site feels responsive and snappy.
FID is calculated from the time a user first interacts with a page to when the browser can respond. Good FID scores are under 100 milliseconds.
Keep in mind that FID is only measured in the field, as it requires real user interactions. Lab tests can't accurately simulate this metric.
Cumulative Layout Shift (CLS)
CLS measures visual stability. It quantifies how much unexpected layout shift occurs during the entire lifespan of a page. A good CLS score is 0.1 or less.
Layout shifts can be frustrating for users. They happen when elements move around after initially loading.:
Time to First Byte (TTFB)
TTFB measures how quickly a website loads. It's a crucial metric for user experience. A low TTFB score means the site loads quickly and smoothly.
TTFB is calculated from the time a page starts to load to when the browser can respond. Good TTFB scores are under 100 milliseconds.
First Contentful Paint (FCP)
FCP marks the time when the browser renders the first bit of content from the DOM. This could be text, images, SVGs, or even canvas elements.
A fast FCP helps users feel that the page is loading quickly. It's an important metric for perceived performance.
Lab data often shows worse FCP scores than field data. This is because lab tests may use different network conditions than real users