By: Kristin Ferguson
The design process is often treated as an art form, and your intuition usually is the way to go. Unfortunately, designers can’t magically read users’ minds. That’s why this approach may lead to a design that is out of alignment with the needs of a user. This is where the introduction of data-driven design comes in.
The approach of data-driven design helps to create a user-centric design and an overall better user experience. It enables you to make better design choices based on real evidence about the user’s behavior, attitude, and needs
However, there’s still a lot of confusion about data-driven design and a lack of understanding of why it is important.
What is a data-driven design?
Data-driven design can be defined as a decision-making part to the design process that heavily relies on collected data about customers’ behavior and attitude.
Information about how customers interact with your design acts as feedback that informs you whether your design fulfills its purpose.
What counts as data?
When people hear the word “data,” they almost instantaneously think about quantitative data, which comes in numbers.
Data is not only numbers. Qualitative data, which refers to things like feelings, opinions, and observations that can’t be expressed in numerical value, is also data.
Why should you care about data-driven design?
Trusting only your gut and not tapping into the data for real-life feedback can be a dangerous approach. It may lead to ineffective design, which in turn can result in lost revenue, wasted time and effort for redesigning, or even some harm to the brand image.
Effective use of data can increase conversions and drive your business to overall success. There are quite a few success stories on how data-driven UX methods significantly contribute to the growth of a business.
Insights
Insights are as much a part of the design as colors or drop-down menus. By bringing in data, observations, patterns, and more, we create an experience informed by quantitative insights as much as design best practices.
We view insights as ideas that incorporate multiple lenses – quantitative research, big data, qualitative research, business goals, and KPIs – and focus on what best applies to a particular challenge. For example, data might tell you that people are abandoning their shopping cart two-thirds of the way through checkout. But while that data is important for identifying an area of focus, it doesn’t hand us the solution.
At that point, adding in qualitative research can help you understand why the behavior is happening. While quantitative data (like cart abandonment) focuses the research, qualitative user observation allows you to witness the cart abandonment issue in practice. The combination of data and observation can help reveal and develop insights that address the friction points.
Resources
- https://attentioninsight.com/complete-guide-to-data-driven-design/
- https://www.bounteous.com/insights/2019/08/30/insight-driven-design/
September 18, 2021
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