Photo by Carlos Muza on Unsplash

Every designer faces hard to make design decisions throughout a project. Making the right call in these circumstances is what separates a great designer from a good one.

Yet, design decisions shouldn’t be always coming from the gut feeling of the designer. As gut feeling can result in unexpectedly good results from time to time, there is always another option if you are looking for a more stable option; using data.

Being able to present a solid reasoning of why one design is better than another would both help you sleep better at nights, and also make your team/manager/client to have better trust in your designs.

So here are 3 methods to get you started:

Conduct A/B tests

A/B tests are perfect for you if you are working on a project that already has active users which you can use as guinea pigs.

The key to a successful A/B test is to keep the scope small and to set a measurable goal before you even start running the test. First define what is a successful design, are you trying to make more people sign up for your product, then your measurable goal would be something like number of sign ups per new user. Or do you aim to keep your users longer in your website, set your goal as the average session time. You get the point.

When it comes to running your tests, make sure you do not have so many variables in place. You want to make sure that after running the test for a while you will know which of the design options you want to take. If you keep adding more tests into the mix, it might be difficult to actually figure out which of the tests is making your numbers go up.

So all this is assuming you are using some kind of analytics software to actually gather up this data from your users. If you don’t know where to begin with analytics, check out the free online courses by Google for its analytics tool.

Utilize heatmap software

I can already hear you, what if I don’t have active users yet? No worries, we’ve got you covered as well.

This one is I believe a more uncommon method, but when I saw it for the first time, it basically blew my mind. The idea is that we will evaluate two different designs with the help of a software. It is powered by machine learning and has been fed with thousands of eye tracking study data to simulate user behaviour as accurate as possible.