March, 2010


31
Mar 10

Firefox & Page Load Speed – Part I

With our last experiment, we found that a simplified download page drove conversions up 2.3%. We hypothesized that much of this improvement was due to improved page load speed. Today, we’ll test this theory — answering not just whether speed matters, but also how much it matters.

Specifically, we want to know: for each second improvement in page load speed, by how much does our conversion rate improve?

Let’s begin by answering a simpler question: was there a difference in page load speed between visitors who downloaded Firefox and visitors who didn’t? We could compare average page load times, but that metric only tells part of the story and can be heavily skewed by outliers. Instead, let’s look at the distribution of page load speed of these two groups (1 = visitors who downloaded, 0 = visitors who did not download):

The difference is surprisingly large. Half of the downloaders loaded our landing page in under 2.10 seconds. For non-downloaders, that figure was 3.67 seconds — 75% slower. Furthermore, a quarter of non-downloaders waited over 7 seconds for our page to load!

Now that we’ve confirmed a difference exists, let’s estimate by how much page load speed improves conversions. To do so, I ran a simple logistic regression, controlling for the experimental variations.

We found that a 1 second increase in page load time decreases conversions by 2.7%! Assuming our model is correctly specified, we have massive room from improvement and can easily increase our conversion rate by 5 – 10%.

We must be careful, however, not to reach too far with our conclusions. There are two factors which complicate our analysis.

First, page load speed does not precisely measure what we care about. What’s important isn’t whether the page fully loads, but rather how quickly our main calls to action appear. Nonetheless, page load time serves as a strong proxy for visible content.

Second, our model suffers from omitted variable bias. We may imagine, for example, that visitors with faster Internet connections are naturally more inclined to download Firefox. In this case, it’s not page load speed that explains the higher conversion rate, but rather an unknown variable that’s correlated with both page load speed and download conversions.

Correlation is not the same thing as causation, but as Tufte said, it’s a darn good hint! And we can verify this hint by running a second experiment.

With the help of Ryan Doherty and Frederic Wenzel, we have already built an optimized version of the IE download page. By randomly assigning users to either this faster variation or the slower control, we will learn whether speed itself drove a higher conversion rate. Look for a discussion of our results later this week.


31
Mar 10

Mozilla’s Q1 2010 Analyst Report – State of the Internet

Today we released the first ever Mozilla Quarterly Analyst Report, focusing on the State of the Internet.  This is the start of something new… in addition to metrics related discussions on this blog and across the broader community, we wanted to create a somewhat standardized, ongoing report capturing the state of the internet as seen through Mozilla’s eyes.  You should expect to see this report released at the end of each calendar quarter.

Download Report (pdf)

Why do this?  Mozilla is in unique position.  We’re a global community with more than 350 million people around the world using the Firefox Web browser.  While we are careful to ensure the data we collect and metrics we track are fairly limited, we feel compelled to share and evangelize the little wisdom we’re able to extract from our numbers.

The structure we’ve laid out includes two general sections – (1) high-level metrics related to Firefox market share and adoption that you should expect to see with each report, and (2) interesting facts and insights that will be rotated in each report.

Some key insights from this report include:

  • Looking across several sources of market share data, Firefox’s worldwide share appears close to 30%.
  • Usage/Adoption of Firefox this quarter grew most dramatically in Russia.
  • Where do people get the earliest start to their day?  Hawaii, Wyoming, and Maine.  And the latest start?  New York.
  • People in South America and Antarctica are passionate about personalizing their browser.
  • In one usage study, we found one person having more than 600 tabs open at one time.  (This last insight comes from Test Pilot, Mozilla Labs’ platform for opt-in participation in studies and experiments.)

We are seeking input and feedback, so if you have any thoughts, please let us know.


26
Mar 10

Firefox’s Adoption Funnel

We’ve done a bit of work over the past couple years trying to understand and improve Firefox’s conversion and adoption funnel.  The Firefox “funnel” encompasses several aspects of a person’s experience with Firefox, including – (1) finding firefox.com or mozilla.com, (2) downloading Firefox, (3) installing Firefox, (4) and using Firefox for the very first time.

Despite all of our efforts, there are always more improvements for us to strive towards.  For example, the Metrics team has started taking notice of one area that has seemingly been a blind spot in the past:

  • What happens to people in the moments between landing on firefox.com and seeing the download button?  (Blake will soon outline more specificity around this question.)
  • And what happens to people in the moments between clicking the download button and actually completing the download process (i.e., getting the full file)?

We’ll plan to discuss these questions and user experiences in much greater detail in follow-up posts.  The key takeaway for now is that we believe there are additional “funnel” improvements to be made – improvements that can easily translate into millions of additional happy new users of Firefox.

(image attributable to http://www.flickr.com/photos/ivanteage/ under a creative commons license.)


22
Mar 10

Addition by Subtraction

With our first multivariate test, we set out to answer a simple question: which design elements drive downloads on the IE landing page? We didn’t know which elements were most effective, but expected each would help persuade visitors to ditch IE.

Our results are surprising! But before I share them, let me briefly describe our experiment design.

We focused on the 4 boxes highlighted in red. To test how each element contributes to Firefox downloads, we created 16 variations of this page, each containing a different set of elements. Note: rather than removing the entire footer, we simplified the footer, keeping the Privacy Policy, Legal Notices, and Report Trademark Abuse links.

Below, you can see 3 of the 16 page variations. Which do you think performed best?

The title tipped it off, but only one element positively impacted the download conversion rate–the download stats box. The main features box, the deep footer, and the switching tips all drove conversions down.

The simplest variation (far right image) performed the best, increasing the download conversion rate by 2.3%, at the 99% confidence interval. This improvement translates to 1.7 million additional Firefox downloads per year!

Next up, we will run similar tests on our non-IE download page and on our localized pages. If we hit the same 2.3% conversion improvement across these pages, we’ll drive 5.4 million additional downloads per year! And, if just 25% of those downloads convert into daily users, we’ll have added as many users as we have in all of Argentina.

We’ll also explore why the simpler variation performed better. One hypotheses is that more users converted because the page loaded faster. Another is that Take a Tour and Reasons to Switch elements are more visible and more persuasive. Have other ideas? Please leave them in the comments!


19
Mar 10

Menu Item Usage Study: Part II

In the last post, we presented the most and least commonly used menu items. We noted that a problem with analyzing aggregated data is the potential for outliers to skew our results. Today, to identify these outliers, we will move from looking at aggregate counts to examining how these counts are distributed.

The table below presents key statistics on the distribution of clicks for each menu item (mouse only). For example, it shows that the median user clicked “User Bookmark Item” 6 times during the course of the study, or equivalently, 50% of users clicked this menu item 6 times or less. Note: each distribution includes only those users who clicked the menu item at least once (if we included all users, even those that never clicked the menu item, many of the Q1 and median numbers would be 0, and the table would not be as informative).

As expected, many of the most commonly used items are heavily skewed with means much higher than the median. “User Bookmark Item”, “Back”, and “New tab” are three of the most heavily skewed menu items; for instance, the mean of “Back” is 10x the median.

Some outliers are more influential than others. For example, the max observation of “Bookmark this Page” makes up 28% of the total count for this menu item. Accounting for outliers and for the shape of the distribution helps present a more complete picture of the most and least commonly used items.

Now that we’ve discussed basic frequency counts and the distribution of these counts, we can move on to more interesting approaches to our questions. In the next post, we will examine the number of unique commands each user uses and determine whether menu interactions follow the 80/20 rule, where relatively few features account for nearly all the product interactions. In the future we will address the question of how long users spend exploring the menu bar before selecting each particular menu item.


17
Mar 10

Firefox 3.6 Upgrade Offer – An Early Success

Late last week, Mozilla pushed a Firefox 3.6 upgrade offer to people on older versions of Firefox.  Here was the actual offer:

What has been the impact in just a few short days?

Looking at the chart below, you’ll notice that the percentage of all Firefox users on Firefox 3.6 increased dramatically in recent days.  Late last week, the percentage of users on 3.6 stood at roughly 23%, and as of yesterday that number had climbed to 43% (btw, that 20% pick up translates to roughly 75 million total people who made the switch — that’s huge!).  Past major update offers have generally converted in the ballpark of 10% to 20% of users, so this most recent push has definitely had a substantial impact.

And below is one further way to interpret these recent numbers.  Looking at the launches of Firefox 3, Firefox 3.5, and Firefox 3.6, we considered how quickly each latest & greatest grabbed usage share from its predecessor.  You’ll notice that the shapes of the 3.0 and 3.6 curves (blue and green) look almost identical… the only difference being the timing of the first offer/advertisement being pushed (note: there was an issue with our early 3.5 update offers, hence the red curve seems to be missing the same upward spike).


15
Mar 10

Menu Item Usage Study: Part I

For the last few days the Test Pilot team at Mozilla Labs has been running a test to explore usage of the Firefox menu bar. Ever since Mosaic 1.0 web browsers have had a standard menu bar–one that has always followed the design of a standard desktop publishing application, containing top level commands like File and Edit, even those these commands are not necessarily relevant to a web browser.

In order to streamline the Firefox user interface, and to match the overall interactive design of Windows 7, the Firefox UX team is exploring collapsing the menu bar into a single “application button” when Firefox is running on a modern version of Windows.

This menu item usage study will help guide the UX team as they create a fully optimized design by answering 3 questions.

  • Which menu items are the most commonly used?
  • Which menu items are the least commonly used?
  • How long do users spend exploring the menu bar contents before selecting each particular menu item?

In this post, we will discuss some preliminary findings regarding the first 2 of these 3 questions. Look for further analysis and a discussion of the 3rd question in our next post!

Experiment Results
The most obvious way to determine the most and least commonly used menu items is to simply aggregate the total number of menu item clicks for all users.

This graph shows just that, presenting each menu item’s relative use for all UI methods (both mouse and keyboard shortcuts). Even from this simple analysis, we can see some justification for a condensed toolbar as many of the items are used very infrequently compared to the other menu items. For example, the menu items from “Page Setup” to “Character Encoding/UTF-16″ each make up less than 0.01% of the total menu bar clicks.

While looking at the total number of item clicks can be informative, since menu bars are designed for mouse use, it is more relevant to look at item usage for just the mouse UI method (excluding keyboard shortcuts).

Examining the data in this way presents a slightly different picture: the top 5 most commonly used menu items are now “User Bookmark Item”, “Copy”, “Paste”, “Add-Ons”, and “Back”. In addition to “Add-Ons”, “Options” and “Bookmark This Page” are newly part of the top 10, replacing “Find”, “Open Location”, and “Find Again”.

Again these changes simply result from eliminating keyboard shortcut clicks and help us distinguish between mouse driven menu items and keyboard driven items. For example, by comparing the mouse UI chart (right) with the original all UI chart (left) we can clearly see that “New Tab” and “Close Tab” are predominately driven by keyboard shortcuts (as expected) and may not be the two most critical items to a mouse oriented toolbar (as suggested by the original chart).

Another interesting approach to these questions is to group the items by menu and visualize the data in this form (again, data is just for Mouse UI).

This visualization presents information on two levels: the area of the circles are proportional to the total number of clicks for the menu group as a whole, and the slices correspond to the share of clicks for each item within the menu group. Bookmarks and Edit are by far the most utilized menus, representing over 70% of total clicks.

The high use of the bookmarks menu is somewhat surprising; an obvious problem of looking at aggregated data like this is the potential for outliers to skew the data. It will be interesting to delve into this issue more in depth and determine if the Bookmark menu (and other menus and menu items) is genuinely an important menu group for all users, or if the high usage is driven by a set of relatively few users who interact with the Bookmark menu extremely frequently.

Wrap Up
Next time we will take our analysis further and move from answering questions about the frequency of item usage to examining how long users spend exploring the menu bar before selecting each particular menu item.

Thanks again to the Test Pilot Team and to all Test Pilot users for providing us with the data. Remember more information on Test Pilot studies can be found here. Anyone interested can also download data samples for this and other Test Pilot Studies from the website!


2
Mar 10

Website Optimization Update

While it’s seemingly been quiet on the website optimization front, we’ve been very busy behind the scenes. Over the last few months, Laura Mesa has coordinated the design of 5 A/B tests that we’re now in the process of implementing (3 on the First Run page and 2 on the IE download page).

Additionally, we’ve expanded the scope of our testing efforts. Look for tests to go live on support.mozilla.com and addons.mozilla.org this week!

In the remainder of today’s post, I’ll discuss a few experiment results and share our website optimizations plans.

Experiment Results
Getting Started
In this test, the Marketing team wanted to determine how adding Firefox tips and tricks to the Getting Started page would affect user behavior.

Unfortunately, after running an A/B test, we didn’t see any improvement in visits per user, pageviews per visit, average time per visits, or bounce rate. For the most part, the differences were minor. The only statistically significant decrease (at the 99% confidence interval) was in visits per user.


First Run Design #1
In the first of 3 A/B tests on the First Run page (bottom image), 6.3% more users interacted with the page and total interactions increased 82.4%. The early results are encouraging, but we need to run the test longer to achieve statistical significance.

Note that the design with more interactions per user isn’t necessarily better. Our final analysis will focus on specific outcomes (i.e. Personas installed and clicks on the “stay connected” buttons).


StumbleUpon Promotion
For this test, we hypothesized that promoting a specific Add-on would be more effective than promoting Add-ons generally. Currently, both the experimental variation and control promotions have a .7% click through rate.

Surveys
In addition to running tests, we used our (highly recommended) website optimization tool to run two simple surveys. With the first, we learned that 47.8% of users open new empty tabs from the new tab button, 30.4% open from the file menu, and 21.8% open from a keyboard shortcut.

With the second, we learned that 46.9% of First Run visitors are first time users, 8.5% used Firefox for under 1 year, and 44.6% used Firefox for over 1 year. The response rate for both surveys exceeded 15%.

Have an idea for a survey you’d like to run on mozilla.com? Let us know in the comments!

Upcoming Tests
Two Additional First Run Designs
We will launch 2 additional A/B tests on the First Run page. Both use tab oriented designs.

IE download page
We will test at least 4 new designs for the the IE download page. We are still in the design phase, but expect to push the first experiments live next week.

IE Multivariate Test
In addition to testing entirely new designs, we want to understand which current design elements are most effective. Accordingly, we will run a multivariate test, switching in and out 4 page elements. Look for a blog post discussing the results soon.

AMO Landing Page
In our first addons.mozilla.org test, we will measure how the featured Add-ons promotion affects bounce rate and Add-ons installed per visit.

SUMO Landing Page
The SUMO team wants to know whether we should reword article titles as questions. Our first SUMO test will do just that.

In addition to running these tests, we plan to test the download confirmation page and run 3 A/B tests on the Update page.

Many thanks go out to Laura, John Slater, Steven Garrity, Royal Order, and everyone else involved in this process! Next up, I’ll suggest a streamlined process for proposing and running tests.