People love heatmaps.
They’re a great way to show how much various UI elements are used in relation to each other, and are much easier to read at a glance than a table of click- counts would be. They can also reveal hidden patterns of usage based on the locations of elements, let us know if we’re focusing our efforts on the correct elements, and tell us how effective our communication about new features is. Because they’re so useful, one of the things I am doing in my new role is setting up the framework to provide our UX team with automatically updating heatmaps for both Desktop and Android Firefox.
Unfortunately, we can’t just wave our wands and have a heatmap magically appear. Creating them takes work, and one of the most tedious processes is figuring out where each element starts and stops. Even worse, we need to repeat the process for each platform we’re planning on displaying. This is one of the primary reasons we haven’t run a heatmap study since 2012.
In order to not spend all my time generating the heatmaps, I had to reduce the effort involved in producing these visualizations.
Being a programmer, my first inclination was to write a program to calculate them, and that sort of worked for the first version of the heatmap, but there were some difficulties. To collect locations for all the elements, we had to display all the elements.
Customize mode (as shown above) was an obvious choice since it shows everything you could click on almost by definition, but it led people to think that we weren’t showing which elements were being clicked the most, but instead which elements people customized the most. So that was out.
Next we tried putting everything in the toolbar, or the menu, but those were a little too cluttered even without leaving room for labels, and too wide (or too tall, in the case of the menu).
Similarly, I couldn’t fit everything into the menu panel either. The only solution was to resort to some Photoshop-trickery to fit all the buttons in, but that ended up breaking the script I was using to locate the various elements in the UI.
Since I couldn’t automatically figure out where everything was, I figured we might as well use a nicely-laid out, partially generated image, and calculate the positions (mostly-)manually.
I had foreseen the need for different positions for the widgets when the project started, and so I put the widget locations in their own file from the start. This meant that I could update them without changing the code, which made it a little nicer to see what’s changed between versions, but still required me to reload the whole page every time I changed a position or size, which would just have taken way too long. I needed something that could give me much more immediate feedback.
Fortunately, I had recently finished watching a series of videos from Ian Johnson (@enjalot on twitter) where he used a tool he made called Tributary to do some rapid prototyping of data visualization code. It seemed like a good fit for the quick moving around of elements I was trying to do, and so I copied a bunch of the code and data in, and got to work moving things around.
I did encounter a few problems: Tributary wasn’t functional in Firefox Nightly (but I could use Chrome as a workaround) and occasionally sometimes trying to move the cursor would change the value slider instead. Even with these glitches it only took me an hour or two to get from set-up to having all the numbers for the final result! And the best part is that since it's all open source, you can take a look at the final result, or fork it yourself!