Data Visualization: Interpreting Uncertainty in Product Design
Data visualization helps make data engaging and easy to understand. However, creating effective visualizations is challenging for designers. Learn how to properly design data visualizations to communicate complex information to users..
We live in a world full of data. Two and a half quintillion bytes of data are created every day, and as our world becomes more and more connected, the volume of data will only continue to grow. It’s predicted that we will have163 zettabytes (163 trillion gigabytes) of data by 2025. But as the human brain has limited capabilities, it’s becoming harder and harder to comprehend all this data.
Communicating information through visual representations is a great way to make data engaging and easy to understand. Data visualization plays an essential role in everything from science and technology to healthcare and economics.
At the same time, data visualizations are one of the most complex tasks for designers, requiring designers to consider many different factors. In this article, we’ll look at the benefits that data visualization brings to product designers, and how to do it properly.
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Simply put, data visualization is creating visuals based on data. Data can be represented in various visual formats, such as charts or graphs. Designers create data visualizations to convey a message or help observers deduct insights based on the visuals.
Why visuals are so powerful
Humans receive information from five senses—sight, touch, hearing, smell, and taste. But sight provides much more information than any of the other four. About fifty percent of our brain is dedicated to visual stimuli, and images are processed by our brains faster than their textual counterparts. Specifically, visuals are powerful for four main reasons.
1. Visuals work better than text
The problem with text is that written information is harder for us to interpret. When information is provided as a text, people are less able to remember it. However, if the same information is provided as an image, the level of information retention goes up to 80 percent.
2. Visuals engage viewers
The rapid development of the internet has changed the way we consume content. When people browse websites, they don’t read—they scan. Visitors scan a page looking for headings and media content, and based on those factors, decide whether they’re willing to dig deeper into the content or not. Visuals engage users by grabbing their attention and increasing the chances that they will stay on a page.
3. Visuals add an emotional layer to data
Data is inherently quantitative, and is rarely associated with emotion and feeling. However, well-designed visuals can add an emotional layer to data. Data visualization can turn cold numbers into real stories with real weight, the kind of stories that provoke emotion.
"Data visualization can turn cold numbers into real stories with real weight, the kind of stories that provoke emotion."
4. Visuals help communicate complex concepts
Once data become visual, its impact grows stronger. Remember the old saying; a picture is worth a thousand words. Good visuals can convey a relatively complex concept in an instant.
How to use data visualization
Data visualization is a powerful tool. For one thing, data visualization can benefit product development teams by setting the direction for the design—it’s much easier to communicate ideas when other people can see what you mean.
A problem visualized is a problem halved.
One of the uses of data visualization during product development is in the user research phase. For example, it’s possible to visualize the user journey by creating a user journey map—a visual interpretation of the overall story of an individual’s relationship with the product, from that individual’s perspective.
Data visualization can provide even more value when it’s used in real products. It can help users find answers to the most important questions, such as:
Data visualization is one of the most complex design challenges, as designers have to consider a lot of factors to create a data visualization that conveys information clearly and efficiently.
Below are seven practical tips that will help you to create great data visualizations.
1. Know the audience and their goals
One of the typical mistakes that designers make when working on data visualizations is focusing too much on creating beautiful visuals, instead of concentrating on communicating the message. Data visualization is a lot more than beautiful visuals; it’s about a thorough understanding of the target audience and their needs, and finding the best way to communicate valuable information to them.
"Data visualization is a lot more than beautiful visuals; it’s about a thorough understanding of the target audience and their needs, and finding the best way to communicate valuable information to them."
It’s impossible to create useful data visualizations without knowing the context of use. Who is this visualization for, and how will they use it are two fundamental questions you need to answer before starting work on data visualization. Always begin with an understanding of the purpose of the visualization, and create a list of questions from users that your visualization will answer. What data does your user need to make a more informed decision?
Protip: The Jobs to Be Done (JTBD) framework can help you find your target audience’s goals. With JTBD, you can think of data as something that helps people accomplish tasks.