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Data Driven UI/UX for a successful game
What do you really know about data driven UI/UX? As the vast majority of consumers would tell you, design is a huge part of any app rankings. And when talking about design, people don’t just mean the aesthetically pleasing shapes and colors.
Design nowadays means everything from beautiful shapes and colors all the way to perfectly situated buttons and menus that will make the user experience (UX) perfectly smooth and satisfactory, which is the ultimate goal behind an app’s design.
So design is not just a form of art as many people think, it is also based on the analysis of hard data that has been reliably gathered from users.
The situation might get a bit more complicated when discussing data, but we will not go into too many technical details for the sake of simplicity.
Suffice it to say that user data is the “science” behind your design. Data can, and should, be gathered using different methods; these include app analytics of a previous version of your app, user interviews and surveys, A/B and multivariate testing, and contextual inquiries.
We have five tips for data driven UI/UX based on our own experience with it. We applied data driven UI/UX on our game VIP Baloot, a game that proved successful in France and Bulgaria, but we didn’t have the same luck with it in the MENA region when we first published it in Arabic but without changing much.
However, this changed when we redesigned it using data driven UI/UX.
Designers don’t always know what’s best. This is very important to keep in mind when you’re redesigning your app. Whether you are creating a completely new app from scratch or simply adding a feature, you need to make sure you are getting validation of what you are doing, which is what user research is all about.
So make sure your users are included, albeit indirectly, in your design decisions.
Basically, A/B testing compares two, three, or four distinct designs with one another (it’s then called A/B/C/D), while multivariate testing compares numerous features and combinations. These two types are not opposites per se; they just offer different methods depending on what you have, so you should choose the one closer to your need.
Just keep in mind that you should test all of your design versions at the same time and for similar users. There are many different metrics you can put to assess each version, but for our need, we used conversion rate, and the one that had a better conversion rate was the winner.
In order to be truly user-oriented, you should apply an outside-in design approach, which means taking design and business decisions as if you were a user rather than an organization. Evidently, this focuses on the user’s needs rather than your own.
This might seem too charitable for some, but it ensures a great experience for the user, which translates to more active users and a better conversion rate.
Make sure you are following your user story, then adapt, redesign, and restructure your UI based on what you deem more important for the user, and on what would make the whole UX smoother and more natural.
You should not focus on finding an answer to the “quality vs. quantity” conundrum, because both of them are important factors and should be taken into consideration. Remember that you can establish your validation on quantitative and qualitative data to get a clear idea of what you have.
These two types of data can be shown through surveys, stats, numbers, and graphs, so make sure to utilize all of these means.
These were our best approaches to data driven UI/UX redesign, but it’s important to mention that you should always survey your users after you change something to assess your decision. So good luck and happy redesigning.