This is the first in a series of posts documenting my personal use of Mouse Eye Tracking to understand user behavior on the PicNet website.

Website analytics and visualisation is growing day by day and if you’ve been keeping up with the trends, you’ll undoubtedly know about Google’s eye tracking tests and their ad positioning guidelines. The hotter the colour, the more mouse activity:

The key point here is that these are guidelines only. Google even admits that saying:

While this heat map is useful as a positioning guideline, we strongly recommend putting your users first when deciding on ad location. Think about their behavior on different pages, and what will be most useful and visible to them. You’ll find that the most optimal ad position isn’t always what you expect on certain pages.(Source)

For those that don’t know, we’ve recently developed Mouse Eye Tracking – a visual analytics web app designed to solve the above issue of finding optimal ad positioning and understanding user behavior. Basically, it tracks visitor behavior and outputs this data as heat maps and click maps.  

I have to admit, when the concept of Mouse Eye Tracking was first proposed to me, I was unsure whether it would be useful or popular, until I read Google’s statement above, the last part in particular struck me – User behavior isn’t “always what you expect.”

If you check out the Mouse Eye Tracking homepage, we have a demo running with live data from the PicNet website. The screenshots below are from our products page which has recorded 131 sessions, a decent sample size to draw conclusions from.

Heat Map (Mouse Movement and Mouse Click)

Heat Map (Mouse Click Only)

When I designed this page, I tried to make it as easy as possible for users to get to the individual products by placing a large, clickable banner.

It’s in prime ‘real estate’ and if we’re to believe general usability heuristics, this area is where the most click activity should occur. Additionally, I made the banner huge so that users would be able to click on it easily. In fact, I’d say that users have to put in effort to avoid clicking it.

Funnily enough, that’s exactly what users are doing. The first heat map shows mouse activity over the banner, but when I compare that to the click map, it appears no one is clicking on the banner, passing it up to click on the product links below in the description – despite the fact that both the banner and the product links go to the same place.

So there you have it. Sometimes user behavior isn’t what you think. I’m not going to change the design because users are still finding their way to the content and I still feel that the banner images provide powerful imagery that communicate the essence of what the products are about – So from a marketing and branding perspective, they’re important. But this is just another example of how Mouse Eye Tracking can help you understand user behavior which is the first step towards (in the words of Google) – “putting your users first.”