There has been a lot of historical work that looks at the relationship between performance and conversions, but most of it has been after the fact or relied on linear models. Google partnered with SOASTA to train a machine-learning model on a large sample of real-world performance, conversion, and bounce data. Patrick Meenan and Tammy Everts offer an overview of the resulting model, able to predict the impact of performance work and other site metrics on conversion and bounce rates. The code used to generate the model is freely available. Patrick and Tammy will explain how to make the most use of it with your own performance data.
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Patrick Meenan has been working on web performance in one form or another for the last 15 years and is currently working at Google to make Chrome and the web faster. Patrick created the popular open source WebPagetest web performance measurement tool, runs the free instance of it at WebPagetest.org, and can frequently be found in the forums helping site owners understand and improve their website performance.
Tammy Everts is director of research at SOASTA, where she gets to analyze billions of beacons’ worth of real user data in order to understand the intersection between web performance, user experience, and business metrics. Tammy has been studying how people use the internet since the olden days, when being able to center text was a big deal and you could have any color of website you wanted, as long as that color was grey. Her 20-year research journey into the heart of UX began when she rigged out her first usability test lab with a state-of-the-art Power Mac 9500. Since then, she’s also done some pretty far-out studies involving EEG headsets and facial action coding. Her book, Time Is Money: The Business Value of Web Performance, was published by O’Reilly Media in 2016. She runs the popular industry blog The Performance Beacon and cocurates (with Tim Kadlec) WPO Stats.
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