Last year at Velocity, Strangeloop's VP Product, Hooman Beheshti, presented the findings from phase one of Strangeloop’s long-term research into the relationship between web performance and business benefits. The results were also published in Watching Websites. Since then, we’ve received a barrage of questions from the web performance community, which fueled phase two of our study. In this presentation, Strangeloop president Joshua Bixby offers our most recent findings.
Some of the community’s questions were:
* Who were the clients?
* How fast were the pages?
* What acceleration techniques were implemented?
* What happened to the key page components (such as JS size, payload and roundtrips) of the websites?
* How did changing key variables (page load time, payload, number of roundtrips, etc.) affect the outcome?
We’ve been collecting and analyzing data to help us answer these questions, as well as some new ones we’ve thought up along the way. Join us as we present our findings, and help us consider what areas deserve further study.
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How much was fast enough? It was anybody’s guess.
And guess they did. This is Zona’s formula for patience, the basis for the “eight second rule.” Unfortunately, things like tenacity, importance, and natural patience aren’t concrete enough for the no-nonsense folks that run web applications.
And guess they did. This is Zona’s formula for patience, the basis for the “eight second rule.” Unfortunately, things like tenacity, importance, and natural patience aren’t concrete enough for the no-nonsense folks that run web applications.
IT operators and marketers are completely different people. What convinces an IT person to fix performance doesn’t convince a marketer. They want to know how it will impact the business fundamentals.
One example of this is performance experimentation that Google’s done. Google’s a perfect lab. Not only do they have a lot of traffic, they also have computing resources to do back-end analysis of large data sets. Plus, they’re not afraid of experimentation – in fact, they insist on it. So they tried different levels of performance and watched what happened to visitors.
The results, which they presented at Velocity in May, were fascinating. There was a direct impact between delay and the number of searches a user did each day – and to make matters worse, the numbers often didn’t improve even when the delay was removed. You may think 0.7% drop isn’t significant, but for Google this represents a tremendous amount of revenue.
Microsoft’s Bing site is a good lab, too. They looked at key metrics, or KPIs, of their search site.
They showed that as performance got worse, all key metrics did, too. Not just the number of searches, but also the revenue (earned when someone clicks) and refinement of searches.
Microsoft’s Bing site is a good lab, too. They looked at key metrics, or KPIs, of their search site.
Shopzilla overhauled their entire site, dramatically reducing page load time, hardware requirements, and downtime.
They saw a significant increase in revenues
Microsoft’s Bing site is a good lab, too. They looked at key metrics, or KPIs, of their search site.
One example of this is performance experimentation that Google’s done. Google’s a perfect lab. Not only do they have a lot of traffic, they also have computing resources to do back-end analysis of large data sets. Plus, they’re not afraid of experimentation – in fact, they insist on it. So they tried different levels of performance and watched what happened to visitors.
If we want to convince marketing, we need to measure business metrics.
By tying performance and availability to Key Performance Indicators – KPIs – business and operations can finally have a conversation.
So what KPIs would we like to learn about? This is what web analytics folks work by, whether they’re running a media site, a SaaS platform, a transactional application, or a collaborative social network. It’s what the business cares about.
Strangeloop agreed to set up an experiment using their technology which would help measure this.