Data and Design. While the alliteration is undeniable, the two words often seem to be opposed to each other. That doesn’t need to be the case, though. Your design can vastly improve with the right application of data. But how do we do that? Let’s take a look.
What do we mean by “data”?
It’s important to start with this question because it can often mean different things to different people.
While some take it to refer to hard numbers, statistics and quantitative data only, others choose a broader definition and include results from qualitative research and customer feedback.
The latter works better for two reasons:
- Qualitative data struggles to receive the same kind of attention and importance as hard numbers.
- It does a much better job of explaining user behaviours and motivation, which is needed to really address issues spotted through analytics.
Quantitative and qualitative data complement each other. While analytics can show you what’s happening, it doesn’t answer why it’s happening. Qualitative data from research and customer feedback fills in those blanks.
Quantitative or analytic data involves tracking how users interact with a product. This can include metrics such as the number of clicks on a button, the amount of time spent on a page or step in a journey, and the number of users who complete a specific task. By analysing this data, product teams identify patterns and trends in user behaviour and use this information to improve the design of their products.
The most common way you can employ quantitative testing is by the use of “A/B testing” which involves deploying slightly different variants of a solution to different audiences for a certain amount of time. Usage metrics from both audiences are tracked and analysed to understand which variant performed better. The one that did better is then usually deployed to all audiences. Companies like Google are famous for A/B testing even tiny parts of their interface like different shades of UI colours to get maximum impact out of their designs.
Note of caution – This is not to be confused with testing different solutions in usability testing. That’s a qualitative research method aimed at figuring out typical issues faced by target users. A/B testing comes in much later, towards the end of the workflow and usually needs the support of engineers and data analysts.
The results of A/B testing tell you what’s happening. Qualitative research and data answer the “why”.