par 
Philip Tellis, édition 2023
When measuring web performance, we often try to get a single number that we can trend over time. This may be the median page load time, hero image time, page speed score, or core web vitals score. But is it really that simple?
Users seldom visit just a single page on a site, so how do we account for varying performance across multiple pages? How do we tell which page’s performance impacts the overall user experience? How do various cognitive biases affect the user’s perception of our site’s performance?
As developers and data analysts, we have our own biases that affect how we look at the data and which problems we end up trying to solve. Often our measurements themselves may be affected by our confirmation bias.
This talk is targeted at individuals who want to understand the business impact of their site’s performance, and how biases in data can affect that.
In this talk, we’ll go into different biases that may affect user perception as well as our ability to measure that perception, and ways in which to identify if our data exhibits these patterns.
Philip Tellis leads the mPulse Data Science team at Akamai. He is the author of the boomerang JavaScript library for collecting RUM data and now spends most of his time distilling the data that’s been collected into interesting stories. Philip wears many hats (both literally and figuratively) and is comfortable with interfaces ranging from CSS to POSIX. His current interest in human behaviour is outside this comfort zone.