Using Google Sitespeed and PageSpeed Products to Debug, Improve, Measure, and Iterate.

Matt Atterbury (Google Inc), Mustafa Tikir (Google)
Sponsored Ballroom E
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Google Analytics Site Speed

Site Speed in Google Analytics help measure and visualize the speed of pages in your web sites. These reports also help you look at your web site’s speed in context of other web analytics data. With the collection of Site Speed reports in Google Analytics, you can measure page load time and a set of network and server latencies for a sample of pageviews on your website pages. Moreover, you can measure the execution speed and/or load time of any discrete hit, event, or user interaction that you want to track in a finer grain. Site speed data is collected from visits to the enrolled websites from the browsers that support the HTML5 Navigation Timing interface or have the Google Toolbar installed.

In this talk, we first present how you can start measuring your website’s performance using Google Analytics and Site Speed. Next, we present a general overview on the types and content of Site Speed Reports in Google Analytics for visualization of speed data.


mod_pagespeed is an open-source Apache module, released in 2010. It automatically applies Page Speed rules and best practices to sites as they are being served, dynamically optimizing images and other resources in the background and dramatically improving site performance. As the module has matured, it has grown beyond simple image optimizations and combining CSS files. We’ll describe many of the new techniques used in mod_pagespeed, such as lazy-loading images, flattening CSS imports, and deferring Javascript. Their impact on web site performance will be analyzed in the context of videos, traditional metrics such as Page Load Time, and new metrics such as’s Speed Index .

This session is sponsored by Google

Photo of Matt Atterbury

Matt Atterbury

Google Inc

Matt Atterbury is a Software Engineer on Google’s Pagespeed Automatic team in Cambridge, MA, which is dedicated to making the web faster for everyone. When not coding, Matt is probably on his bike.

Photo of Mustafa Tikir

Mustafa Tikir


Mustafa M Tikir received his PhD degree at the University of Maryland, College Park. He received his BS degree at the Middle East Technical University, Ankara. His PhD research was on automatic performance tuning of HPC applications at runtime using online profiling data. Following PhD, he has worked at San Diego Supercomputer Center as a researcher to bring scientific rigor to the prediction and understanding of factors affecting the performance of current and projected HPC platforms. In 2010, he has joined Google as a member of the Make The Web Faster team. He has been working on measuring user perceived latency for websites and applications. He is primarily interested in performance measurement, modeling and tuning of applications.


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