Colors speak a language louder than words and communicate with us on an emotional level. The challenge is to use the power of color effectively to communicate the message you want to send.
Data visualization is very important in business today – it makes patterns more visible, digestible and clearer. It can improve the way you tell a story and color is an important part of this. Color sets the stage for how your data makes people feel.
The meaning of colors
Colors create a chemical reaction in the brain that produces an emotional response. They trigger thoughts, memories and associations to places, people, and events.
Colors with long wavelengths, like red, have a faster recognition response in the brain. Colors with a shorter wavelength, like blue, are more soothing and can actually lower blood pressure and pulse rate. Yellow is a middle wavelength color that commands attention.
The meanings of colors affect how viewers perceive data. For example, if you want to create an awesome slide presentation, using the right colors is essential. A light blue could help your audience to relax whereas too much yellow could generate anxiety.
It is worth paying attention to some of the research done into just how different colors affect emotions. For example, even a light red and a dark red can convey very different emotions. Light red conveys love, sexuality and joy whereas dark red conveys anger, passion and confidence.
Businesses often make extensive use of color to influence the way customers feel. For example, cafes will use colors like orange and brown on the walls to make customers feel relaxed and at home. A brand like thepensters uses an effective combination of blue, white and yellow on a black background to draw attention to key features on their website.
Creating associations through color
Color lets you set the mood and helps you to tell a story. In a visualization of drone strike victims in Pakistan, Pitch Interactive uses red drops very effectively. The association of red with the color of blood makes it work.
When Professor Klaus Schulte created a visualization of how Germans have dominated the Olympic sport of Luge, he used the black, red and yellow of the German flag. The blocks of color were immediately recognizable.
Choosing your colors
Neil Patel reports that 52% of the time, poor color choice and other inferior design choices make users leave a website and never go back. In data visualization, colors have the same effect and choosing the right colors is very important. Choosing your colors depends on various factors and aesthetics, testing and science should all play a part.
Your Target Audience: You need to know who they are, what they care about and how they will be affected by the colors you choose. For example, color means different things in different cultures.
Derek Morgan, a writer at essayshark reviews, says he was surprised to discover just how different the perception is of the color yellow in different cultures. In Japan, yellow is associated with courage but in certain parts of China, it can have vulgar connotations.
Color perceptions are influenced by age, race, social class, religion and gender. Researching the cultural associations of your target audience with each color is important.
Appropriateness: Certain colors are more appropriate to some industries than to others. Sometimes, colors just feel wrong to us because they don’t match our expectations.
For instance, we don’t expect to see financial institutions using bright yellow or orange. We don’t expect to see landscaping companies using these colors either.
Financial institutions often use the color blue because it communicates stability and authority, values customers expect from those who handle their money. Red may be suitable for a dating service whereas green is usually associated with nature and the environment.
Improve data visualization by using color
You can’t just throw color in haphazardly as you may end up distracting viewers rather than evoking the feelings you want. You need to use color carefully in ways that get your point across.
Influence overall feel and give depth: Using the right colors is important to get your viewers feeling how you want them to feel about your data. Colors can create a cheerful mood or convey a sense of calmness. They can evoke feelings of creativity, purity or sophistication.
Make important elements stand out: Using the same colors for everything is not only dull and uninteresting but is also confusing to viewers. Color helps you to highlight the most important aspects of your message and simplify complex graphs.
By using contrasting colors, such as blue and orange, if you’re comparing two data sets, you can simplify data and help viewers to see the big picture. Using gray for less important chart elements can make highlight colors stand out more.
Steve Baldwin, a graphic designer at AssignmentGeek says that he uses contrasting colors to make his data jump out and grab attention. For example, if he wants to emphasize a piece of data in a bar graph, he will make it bright red in a sea of gray.
Create contrast: Using a great range of colors is no good if viewers can’t read the data. You want to make sure that viewers are able to read your data on their screens, even if you use light colors like gray.
This is especially important for text as the smaller it is, the higher the contrast to the background needs to be for it to be readable.
Avoid using bright colors for backgrounds. Consider giving small lines a high contrast in hue or brightness so they are easy to distinguish. Testing a presentation on a projector before giving a presentation is important because the colors may look quite different from those on your laptop screen or phone.
Use colors consistently: If you have certain variables that you repeat across different sets of data, you should use the same colors where possible. A sense of consistency helps viewers to relate.
Use gradients when you can: Gradients offer a great way to compare and contrast data and feel natural when viewers see them. If a gradient indicates a scale of low to high, light colors should represent the low values and darker colors, the high values. This is intuitive for the audience.
Having unrelated colors can make data more difficult to read. If you’re unsure about using gradients but want to try your hand, you could try using the ColorBrewer palettes.
The Bottom Line
Using color strategically is more than just choosing what looks good to you. You should never select colors because you think they are trendy or cool or they’re the colors you always favor.
You need to choose them carefully by understanding the meaning behind them, taking your audience into consideration and knowing what’s appropriate for your brand. The value of picking the right colors for your data visualization should never be underestimated.
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