What is data-aware design? Data-aware design is a salient topic in UX/UI (User Experience/User Interface Design) that IT departments across the world are beginning to realize is important in increasing end-user engagement. It relates to the process by which you make decisions about the layout, color scheme and content of your digital assets and how you evaluate whether or not they were effective in reaching the intended audience and effective outcomes. The University of Michigan, a OneCampus customer, originally presented their formula for data-aware design in an informative webinar co-hosted with rSmart which was recorded.
This blog provides a brief overview of some key points.
What is data-driven design?
Data-driven design is the most granular form of the creative and investigative process. It focuses primarily on optimization and efficiencies looking to drive an increase in ‘specific areas.’ An example of data-aware design that was highlighted in the University of Michigan’s webinar “Unlocking the Secrets of Data-Aware Design on Your Campus” is conducting research on the impact of color in button performance on a website. They ultimately opting to use a red button over a blue button because it leads to a higher conversion by more than 20%.
What is data-informed design?
Data-informed design widens the focus compared to data-driven design and seeks to understand high-level user expectations and perceptions. An example of this could be trying to understand why users feel that the interface isn’t “user-friendly” by conducting interviews with end-users that attempts to understand what they wanted to accomplish but weren’t able to.
What is data-aware design?
Data-aware design provides the most flexibility for the creative and investigative processes. It allows for a complete exploration of the problem landscape and integrates aspects of both data-informed and data-driven design, allowing users to define and solve the problems that are the biggest priorities regardless of which ‘bucket’ they fit into.
There is no more or less validity to any of the above methodologies for looking at your design. When we consider data-aware design it’s important to remember that data and design go hand-in-hand, to inform each other. Data exposes problems that design can solve, and design should inform the data inquiry process to create a fulsome feedback loop that works towards improving usability for the end-user.
“Ask ‘why’ at least five times.”
Data-aware inquiry relies on keeping an open mind and considering your own bias. A method of inquiry that designers use to solve for their own bias is to “ask ‘why’ at least five times.” While this may sound overly simplistic, it will allow you and your team to delve deeper into the problem by helping you and your team reach clarity of the intent or purpose behind your design.
Use the why method to dig deeper into why you want to know something that or what you are hoping to learn or solve for. This will help you to clearly define your research questions before selecting the testing methods and metrics that will determine the success or failure of your test.
Data can validate design and demonstrate the value of your work if you are thoughtful in your process. For more information and examples of data-aware design, we recommend watching the complete webinar recording of “Unlocking the Secrets of Data-Aware Design on Your Campus” co-hosted with the University of Michigan and rSmart.
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