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A Focus on Visualizations: The Science of Color

PUBLISHED ON 9 DECEMBER, 2014

“Why should we be interested in visualization? Because the human visual system is a pattern seeker of enormous power and subtlety.”

Collin Ware, Information Visualization:

Perception for Design, Second Edition

(San Francisco: Morgan Kauffman, 2004), xxi.

Just as important as the functionality of each visualization is the color we decide to use to bring it to life. Color carries significance and power, as it affects both the quality and speed of data interpretation. Colors speak to our senses, calling our attention and creating relationships in our minds. When inviting color into your data visualizations, you should be cognizant of different color palettes and scenarios for their best use.

The way we interpret color depends on cultural influence, age, personal association, and even one’s mood. We attach values to colors based on:

• Symbolism: Symbolic colors vary by culture: for example, red is often used to represent love or passion in Western cultures, whilst Eastern cultures associate it with wealth and fortune.
• Emotional values: for example, think of age: little ones generally appreciate brighter colors, and therefore retailers whose target audience consist of children will use cheery and vivid colors on packaging and advertisements.
• Historical experiences: for example, if you once felt threatened by a fire, red and orange might have negative connotations for you throughout your life.
• Signaling conventions in society: Signal colors are hues that send our minds a message. They are part of our everyday life, just take for example how we use traffic lights to regulate our drives.

Some colors hold such strong and well established meanings that they are said to be semantically resonant colors. Applying these colors with complementary concepts has the advantage of saving your readers’ time in the interpretation of data visualizations. On average, people took a full second less to complete a single comparison task when they were looking at semantically resonant colors. This may seem insignificant, but it was about 10% of the total task time.

Although this argument is valid, it’s not typical to measure digital marketing metrics with basic color associations, such as: apples are red, blueberries are blue… So what color should we associate to Conversions? Engagements? Reach? Impressions? Clicks? Cost per Acquisition? Revenue?

There are a few different strategies we can employ to discover the right colors for your data visualizations.

First and foremost, the main question is which colors should you be using to visualize your data? Consider that some colors have soothing effects, while others are more impactful and evoke emotion. It is key to know the difference between the two.

Soft, standard colors should include hues such as soft grays, browns, oranges, greens, and blues. Tranquil colors allow users to interpret dashboards calmly while keeping an open mind. If there are too many emphasis colors the reader will get frustrated by the many signals screaming out for their attention. It is best to use emphasis colors sparingly when it is vital to draw the reader’s attention to a certain dimension.

The example below also demonstrates another important point: bright colors should be reserved to make important aspects stand out from the rest – not to be used together.

To find the perfect color harmony, its helpful to understand colors from the perspective of the color wheel. To start, consider complementary colors. Located  on opposite ends of the color scale, they create a strong contrast when used side-by-side. When placed together, complementary, like emphasis colors, should not be used in large doses, but should be reserved for occasions when you want something to stand out.

Analogous color schemes can be selected by choosing colors found next to one another on the color wheel. Analogous colors typically go together well, and are pleasing to the eye.  It is important to be sure that you have enough contrast between analogous colors to provide the clarity your reader needs to interpret the visualization.

The triadic color scheme requires careful balance. You may opt for this by using three colors that are evenly placed around the color scale. The colors tend to be quite vibrant despite the use of paler hues, so to successfully display variables with the triadic color scheme we suggest letting one color dominate and using the two others for accent.

The tetradic color scheme is comprised of four colors arranged into two complementary pairs. This is a great color scheme for showing variation, but is most effective if you allow one color to be dominant. A key to using the tetradic color scheme is to find a balance between warm and cool colors in your visualization.

Understanding the basics of impactful color schemes can help you optimize your reports. When working on your next data visualization or dashboard design, be mindful of the colors you choose. Consider the effects, emotions, and overall general readability that each color will contribute to a graph. The trick is to strike the right balance between design and interpretation optimization, in order to give your reader the most beneficial experience.

Which color combinations do you find most effectively represent your most important data visualizations?