Transcript from the "Chrome User Experience Exercise" Lesson
>> So when we think about these three kinds of data, it's important to think about the signal and the noise as in what is the value that you're getting from this data? And then how noisy is it? So lab data, is obviously very low signal. It's a general idea of how well your computer would perform or how well your site performs in the best possible circumstances.
[00:00:25] There's no noise I mean, it's here's the data, right what you think it is, but the data is not as valuable as it would be otherwise. Synthetic data is a little bit more, it's also measuring a real network. How a server really happens. And it's measuring it continuously over time.
[00:00:42] Every minute it's trying to do it again. And so it's much more valuable than live data. There's a little bit more noise, because their machine might not work quite perfectly every time, it might go offline, their network might go down or whatever. Field data has considerably more signal, because it is what real users the real people that you care about,that data can come back to you.
[00:01:06] But as I said, there's a lot of noise in it as well. There's a lot of people who will visit your site. There's a lot of bots that will visit your site, that will send you data that does not matter and that you don't care about and that you wish wasn't in your data that you have sieve through.
[00:01:22] And so there's a trade off here between how much noise you want to deal with, how much confidence you want you need in your data. Now we can get some of this data. Some of this data is published through some means that you might be surprised by. So we're gonna do another exercise here, and this one should be faster.
[00:01:44] There is a data source called the chrome user experience report. Now, unbeknownst to many of us, Chrome has been capturing these real user experience reports from you and pulling it back to Google for years, the browser itself has been gathering it for all the websites and pulling it back and publishing this data publicly monthly.
[00:02:09] You can see how well every site on the, well, the top million sites on the internet performed for the real users that hit them according to Chrome. Now, this data is sometimes kind of hard to work with, there's a bunch of advanced tools, but fortunately, there is a website that has made this super easy.
[00:02:29] So in this exercise, we're going to page three, or example three on our sheet. And there is a link on the bottom cruxcompare.netlif.app. This is a site that exposes that Chrome user data and allows us to see what it actually is. So what I want you to do is I want you to to go into each of these of those four websites and enter the URLs in.
[00:02:59] Which we can probably just just do together here for the first one, but I want you to have experience using this. And it's going to produce from the last month of data, which is what this particular website is publishing, what the scores are for all of the core metrics.
[00:03:15] What I want you to do is I want you to capture this number up here, which is the piece, or the 75th percentile number and we'll talk about what that means specifically in a minute.