metrics

UPDATED: Everything you wanted to know about web performance but were afraid to ask

As mentioned when I first posted this popular entry, my plan is to keep this one-stop shop for performance stats up-to-date as new data is released. Here’s a summary of what’s been added:

A user who has to endure an 8-second download delay spends only 1% of her total viewing time looking at the featured promotional space on a landing page. In contrast, a user who receives instantaneous page rendering spends 20% of viewing time within the promotional area. [Source: Jakob Nielsen]

Between 37 to 49% of users who experience performance issues when completing a transaction will either abandon the site or switch to a competitor. Of these, 77% will share their experiences with others. [Source: Sean Power, Metrics 101]

Users have faulty perceptions of time. For example, the average person will perceive the amount of time it takes a page to load as being about 15% slower than the actual load time. And later, in recalling their memory of how long it took for the page to load, they will remember it took about 35% longer than it actually did. [Source: Stoyan Stefanov, Psychology of Performance]

  • A site that loads in 3 seconds experiences 22% fewer page views and a 50% higher bounce rate than a site that loads in 1 second. Impact on conversions: -22%.
  • A site that loads in 5 seconds experiences 35% fewer page views and a 105% higher bounce rate. Impact on conversions: -38%.
  • A site that loads in 10 seconds experiences 46% fewer page views and a 135% higher bounce rate. Impact on conversions: -42%. [Source: Strangeloop]

You can read the post in its entirety here.

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The 16 Best Graphs of Velocity 2010: A snapshot of the current web performance landscape

While at Velocity last week, I took in so many sessions and workshops, by the end it felt like data was shooting out my eyeballs. Fortunately, my brain was saved from short-circuiting by the fact that many of the slide decks have been published online for a more leisurely, synapse-friendly review.

In the past week, I’ve spent a fair bit of time going through the presentations and started collecting my favorite performance graphs and charts. It occurred to me that, taken all together, these provide a pretty nifty snapshot of the current state of web performance. Let’s take a quick tour together:

Site Speed and User Behavior

I’ll start with a couple of graphs I created for the 90-Minute Optimization Life Cycle workshop, which I co-presented with Strangeloop‘s VP Product, Hooman Beheshti:

With both of these graphs, you can see the dramatic relationship between landing page speed, bounce rate and pages viewed per visit. But the drama really comes into play in the performance bottom line, conversion:

Hooman and I weren’t the only ones providing solid data on user behavior. Many of our colleagues came with compelling data of their own.

In his presentation Performance Testing: Putting Cloud Customers Back in the Driver’s Seat, Imad Mouline presented this great graph showing that speeding up a page by just 4 seconds decreases abandonment by a whopping 25%:

The Impact of Web Performance on Page Abandonment

User Expectations

These next two graphs demonstrate two important things to remember about web users. First, as Yahoo’s Stoyan Stefanov demonstrated in his Psychology of Performance presentation, for most of us there’s a distinct difference between perceived speed and actual speed. When it comes to web performance, this difference works against us:

Actual versus Perceived Time

But as Lenny Rachitsky showed in his The Upside of Downtime session, even when users’ perception of speed and responsiveness works against you, you can still earn their trust and respect in a crisis, so long as you’re willing to be honest and communicative:

So How Does User Experience Affect Business Metrics?

There were a handful of messages that were threaded throughout many of the presentations and discussions at Velocity. The relationship between performance and the bottom line was one of them. In his excellent Metrics 101 workshop, Sean Power presented some visuals that hammered these points home.

In the short term, Sean used these next two graphs to show the prohibitive costs of downtime, even if your site is unavailable for just one hour:

The real cost of downtime

The real cost of downtime: detail

Over the slightly longer term – a one-week period – Sean shows that as latency increases, conversion rates drop:

Impact of increasing latency on conversion rates

In this next graph, Sean shows the long-term effects of poor performance, which can take years. We can see that a poorly performing website suffers not one but two waves of abandonment, as users spread the word of their poor experience and drive other users away from the site.

Long-term impact of poor performance on user behavior

What Are the Causes of Slow Performance?

There’s no single answer to this question, of course. I’ve addressed this elsewhere (along with some pretty decent graphs, if I do say so). Here are two more to add to the mix.

In the same Metrics 101 workshop, Sean showed this awesome diagram, which pretty much sums up the dialog between a browser and a data center during a typical page request:

Dialog between browser and data center

Further complicating this dialog are the calls to to third-party content providers, such as ads and widgets. Google did a survey of a number of sites, testing their page load time with and without popular third-party widgets. They documented the results on this chart in their session Don’t Let Third Parties Slow You Down:

The Impact of Third-Party Content on Page Load Times

What About the Mobile Web?

In my brief keynote at Velocity, I talked about mobile web use and the fact that, at this point, pretty much all we know is that we don’t know much, but we’d better figure things out quickly because the mobile web is a tidal wave that has not yet even begun to crest. Maximiliano Firtman, in his Mobile Web High Performance session, provided a couple of graphs that illustrate this:

Mobile web use vs the regular internet

Mobile web: market share vs usage

(If anyone out there has some solid data on performance and the mobile web, I’m keeping notes for a future post. Drop me a line in the comments or email me at joshua@webperformancetoday.com.)

And finally, the last pair of graphs…

Practical Planning for Performance

In the last part of his Metrics 101 workshop, Sean offered a realistic step-by-step plan for dev/ops folks to measure performance and outcomes in their organization. He said that if you create only one graph for your site, it should be one that looks like this, which shows the direct impact of page load time on conversions:

Sample graph: The relationship between web page load time and conversions

And because even the most optimized site still goes down from time to time, Lenny shared this excellent, common-sense plan for communicating with your users:

Upside of Downtime: Communication Plan

Have I missed any of your favorite presentations and visuals? Let me know in the comments.

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Performance Impact, Part Two: More findings from the front lines of website acceleration

Here’s the slide deck from my Velocity presentation earlier today, where I presented case studies showing the relationship between site speed and business metrics. For those of you who want to get straight to the side-by-side performance videos, I’ve posted these as separate links below.

Side-by-side performance videos:

As always, if you have any questions, please don’t hesitate to contact me at joshua@webperformancetoday.com.

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The Performance Metrics Project: Would you participate?

Today at Velocity (1:00pm in Ballroom AB), I’ll be presenting important data that Strangeloop has gathered from our customers. It shows some interesting trends that correlate performance and key business metrics.

Here’s a sneak peek at one of my slides:

Web Performance Optimization: How landing page speed affects conversion rate

Customers who use our device or our service can easily opt-in to supply their performance and metrics data to help us gather exactly this kind of information. Most do, which is incredibly generous of them.

The cool thing is that it’s easy for anyone to contribute data, not just Strangeloop customers. All you have to do is insert some Javascript code into your page, the same way you do for things like Google Analytics.

Which leads me to my question:

Would you consider participating in an open project wherein contributors shared their performance and metrics data in order to gather and analyze realtime data from real websites? Would your organization? Is such a project even worthwhile? I’m keen on this idea, and I’m working to garner universal support within Strangeloop. However, opening this kind of data-gathering up to a broader audience will take time and effort. In your opinion, is it worth it?

Please give me your feedback and level of interest in the comments or by email: joshua@webperformancetoday.com.

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The 90-Minute Optimization Life Cycle: “Faster by default” before our eyes?

Thanks to everyone who came out to Hooman’s and my workshop today at Velocity, and thanks especially for your patience with the fire drill that interrupted us – and for actually coming back to the room after it was over. Keeners!

As promised, here’s our complete slide deck, which shows in detail how we optimized our surprise guinea pig: the Velocity home page.*

I welcome your questions. You can reach me at joshua@webperformancetoday.com.

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