There has been a lot of historical work to look at the relationship between performance and conversions, but most of it has been after the fact or relied on linear models. Recently, 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 and answer questions like:
The code used to generate the model is freely available. Patrick and Tammy demonstrate how to make the most use of it with your own performance data.
Patrick Meenan is a software engineer at Facebook, where he’s helping make the web faster. Patrick has been working on web performance in one form or another for the last 25 years. Previously, he worked at Cloudflare and 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 chief experience officer at SpeedCurve, where she helps companies understand how visitors use their websites, and a cochair of O’Reilly Fluent. Tammy has spent the past two decades studying how people use the web. Since 2009, she’s focused on the intersection between web performance, user experience, and business metrics. Her book, Time Is Money: The Business Value of Web Performance, from O’Reilly, is a distillation of much of this research. She also cocurates (with Tim Kadlec) WPO Stats, a collection of performance case studies.
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