How to Pick the Design Style for Data Visualizations - dummies

How to Pick the Design Style for Data Visualizations

By Lillian Pierson

To choose the most appropriate design style for your data visualization, you must first consider your audience and then decide how you want them to respond to your visualization.

If you’re looking to entice your audience into taking a deeper, more analytical dive into the visualization, employ a design style that induces a calculating and exacting response in its viewers. But if you want your data visualization to fuel your audience’s passion, use an emotionally compelling design style instead.

Analytical types might say that the only purpose for a data visualization is to convey numbers and facts through charts and graphs — no beauty or design is needed. But more artistic folks may insist that they have to feel something in order to really understand it. Truth be told, a good data visualization is neither artless and dry nor completely abstract in its artistry. Rather, its beauty and design lie somewhere on the spectrum between these two extremes.

Using design to induce a calculating, exacting response

If you’re designing a data visualization for corporate types, engineers, scientists, or organizational decision makers, then keep your design simple and sleek, using the data showcasing or data storytelling visualization. To induce a logical, calculating feel in your audience, include a lot of bar charts, scatter plots, and line charts. Color choices here should be rather traditional and conservative. The look and feel should scream “corporate chic.”


Visualizations of this style are meant to quickly and clearly communicate what’s happening in the data — direct, concise, and to the point. The best data visualizations of this style convey an elegant look and feel.

Using design to elicit a strong emotional response

If you’re designing a data visualization to influence or persuade people, then incorporate design artistry that invokes an emotional response in your target audience. These visualizations usually fall under the data art category, but an extremely creative data storytelling piece could also inspire this sort of strong emotional response.

Emotionally provocative data visualizations often support the stance of one side of a social, political, or environmental issue. These data visualizations include fluid, artistic design elements that flow and meander. Additionally, rich, dramatic color choices can influence the emotions of the viewer. This style of data visualization leaves a lot of room for artistic creativity and experimentation.


It’s important to keep artistic elements relevant — and to know when they’re likely to detract from the impression you want to make. This is particularly true when you’re designing for analytical types.