As designers, we know that data is key to understanding user behavior. It is powerful information that increases the effectiveness of our work when it’s leveraged in the right places. Data can also be problematic if it is misinterpreted or teams become over-reliant on it. We must understand it’s advantages without allowing it to dictate our decisions, and to do this we need to balance data with intuition.
Where Data Exceeds
Data is great at a lot of things, specifically the things that humans aren’t as good at seeing. Here’s a few common ways we leverage data to help inform our design decisions:
User testing is a fundamental part of the design process. Whether it’s usability test, card sorting, click test, or any other exercise, we leverage this data to validate the effectiveness of our design decisions. Data from user testing helps us validate design decisions and anticipate potential issues or bottlenecks so that we can then optimize our designs.
Analytics are a key ingredient that gives us a benchmark for our design decisions. Not only do they allow us to identify how users actually interact with a product, but they allow us to identify patterns of behavior and issues that users might be having. This data can then be used to inform our decisions while we iterate on a design in order to address bottlenecks or simply validate what’s there is working.
It’s part of our job as designers to know best practices. Not only should we understand why they exists in the first place, but also when and how to use them. Proven methods or techniques are considered a best practice only after consistent validation of results, and these results come from data.
Where Data Fails
While data excels in certain areas, it falls short in others. Here’s a few downsides when relying too much on data:
Data doesn’t tell the whole story
Data can provide us with helpful insight, but it can’t tell the whole story. As a simple example, let’s say your analytics indicate that users are dropping off on your product’s website before signing up. The data shows that they scroll halfway down the page and then back up to the top before leaving, but we need them to scroll to the bottom in order to find the sign-up form. Based on the analytics data avialable, we decide to move the sign-up form higher up on the page, and we walk away feeling confident that the problem is solved.
Soon it’s discovered that users are still not signing-up, despite seeing the sign-up form. It turns out the problem is actually how the product’s features are described, which lacks a clear value proposition for users. This simple example demonstrates how data can fail to tell us the whole story. In this case, it’s the message that’s being communicated — not the placement of the sign-up form.
Data is interpretive
While data is inherently non-subjective, there are a number of ways it can be manipulated. Firstly, the way user tests are constructed or conducted has the potential to skew the results. Secondly, how we interpret data can be skewed by our own subjective bias. Misinterpreted data can quickly lead to us solving problems that don’t exist or creating new ones unknowingly.
Data can become an obstacle
There’s a fine line between using the insight that comes from data to inform our design decisions, and data dictating our design decisions. An over-emphasis on data can become an obstacle in two ways: 1) it can be interpreted too literally, or 2) stifle change altogether. Both of these result in data being treated as a mandate, instead of using it as a tool that informs our decisions. When everything must be validated with data, there’s little room left for intuition to guide designers to more innovative solutions.
Finding the Balance
The ability to synthesize information and make informed design decisions is a fundamental part of our job as designers. We must consider nuance and the human element in tandem with data—things like emotion, appropriateness, and accessibility must all be part of our design solutions.
When teams regard data as the ultimate deciding factor, they eliminate the power that intuition has to make these connections. Instead of treating data as a mandate, we must leverage it as the basis for more design iteration.
By identifying the ‘why’ with user behavior and then using our intuition to guide us, we can make better design decisions that account for the nuance of human factors that data cannot see. We should utilize data as a tool for guidance without allowing it to dictate our approach.