Data-driven design involves basing our digital design decisions on data collected through performance analyses of previous designs. In this sense, data-driven design puts the designer's intuition in the background, giving more importance to both qualitative and quantitative data.
Data-driven design is a very interesting way to approach design work, as it increases the chances that the design will be effective, better capturing the user's attention and increasing conversion possibilities. By relying on the experience of previous designs, data-driven design selects the best design practices and eliminates those that perform poorly.
If you're a data-driven company that bases all its actions on data or a designer who wants to put this way of working into practice, in this article we'll tell you how you can implement data-driven design in the best possible way and give you some tools that can be useful along the way.
To carry out a data-driven design, it's very important to establish what you want to achieve with that design before anything else. More conversions? More interactions? Increase brand awareness or improve your brand image? Improve user experience?
Clarifying goals from the start will help you know which previous data to base your design on, as the type of design that works best for achieving more conversions may be totally different from what works to enhance brand image.
In data-driven design, it's essential to measure the performance of each design once it's launched to the public to expand the database. Therefore, you'll also need to choose beforehand the metrics we're going to focus on.
In this process of analyzing design performance, experts use different tools depending on what they want to investigate. We'll talk more about these and the metrics later, indicating which ones are the most interesting.
You can stop measuring the data your design generates when the campaign it's integrated into has ended, but if it's going to be long-term, you can establish when it's time to analyze performance. Typically, it's recommended to start analyzing design performance when it has generated enough data to draw significant and weighty conclusions.
In any case, it's important that you store all the data and analyses you perform in an organized way so they can serve as a guide for future designs.
In data-driven design, it's very important to have a flexible mindset and one of continuous improvement. Although designs are based on data and previous empirical experience, the collected data is not set in stone.
By this, we mean that the data used to create a specific design may no longer be useful when it's found that other practices are more efficient due to subsequent analyses.
It's key in data-driven design to keep our data updated, which is why constant data analysis of each design is so crucial to avoid becoming obsolete.
As it's crucial in data-driven design to collect different types of data of the best possible quality, we want to recommend some tools that we consider very interesting for this purpose. However, the last one we recommend has a different purpose, but we wanted to mention it because of its great utility.
Google Analytics and Adobe Analytics are two of the most recommendable tools for analyzing the amount of traffic coming to a website or ecommerce, as well as how they arrive at the site.
If you're just starting out or looking for a simpler analysis, I recommend using Google Analytics, as Adobe can develop more advanced analyses.
These tools are possibly the most interesting in data-driven design, as they allow us to know how the design affects the way users move around the website and how it can be improved.
Heat maps are the most used tool in this sense, as they indicate with intense colors the areas with the most clicks and the longest viewing time. Hotjar is a heat map tool that can help you know how users behave on your website, although there are many more like Heat-map or Crazyegg.
These types of tools allow designers to create interactive models of user interfaces in order to facilitate visualization of the result before starting to build the definitive design and invest time and money.
In interface design and prototyping tools, you can test different ideas and make simulations. Among the most recommended tools in this area are Adobe XD, Sketch, and Figma.
Data-driven design is very focused on improving user experience. Therefore, the most important metrics are related to this area. Some of the most important are: