It's well-established that data visualization is a big part of modern business. It makes patterns clearer, digestible, and more visible; it can improve information storytelling and response time to emergent trends, and it can even help businesses make use of data that was previously inert and unused.

That's why it's important for you to make the most out of your data visualization! It's not just a matter of firing up your favorite data viz software and choosing the default templates for a bar graph or heat map, letting the data speak for itself, and calling it a day. There are a variety of important factors that can influence how visualized data can be perceived by viewers. Understanding these factors is key to more successful, more effective visualization storytelling that can provide you with the results you want.

You might be thinking that these factors include basic things, like what type of chart to use for each kind of data or psychological tricks like the scaling of your X and Y axes to amplify differences between data sets. But did you know that color actually has a huge impact on how any chart, map, or graph is actually perceived?

The Psychology of Colors

Color has long been used by marketing to influence how we see the world. The impact of color is dependent on both societal conditioning and some presumably universal human perceptions.

One of the most prominent ways you'll find this in use in the real world is in the interior design language of restaurants, which make extensive use of color to manipulate the way their customers feel. For example, cafes may often use earthy colors like orange and brown on their walls, which make their customers feel at home and relaxed. Fast food restaurants often use bright reds and yellows all over the place, as they provide a sense of urgency that encourage customers to eat and run, so to speak.

Massive brands like Coke and Pepsi are well-known examples of companies that have experienced success in studying and applying the psychology of color.

Color, therefore, is important in setting the stage for how your data makes people feel about something.

Data visualization is, quite literally, a very visual marketing medium, and that means using everything available to you that can affect visual perception, including color, to better represent your data and draw attention to all the important bits. Neil Patel writes a great article on the effect color can have on your conversions, if you're interested in applying the psychology of color to improve your conversion rate.

How Color is Used in Data Visualization

You may or may not realize that color in data visualization is affecting your judgment and perception, and it can be a very subtle effect or a powerful shout that keeps you focused on it.

1. Color simplifies complex graphs

Comparing even moderate amounts of data can be a drag for anyone to look at, with all sorts of lines and heat maps introducing visual clutter that isn't immediately intuitive. By using contrasting colors, such as blue and orange for visualizations that compare two data sets, or a gradient of colors that are often considered to represent a scale (for example, green, yellow, orange, red), you can simplify things and help viewers see the big picture.

2. Color influences the feel of the overall data

Choosing the colors that make up your infographics is going to be highly dependent on how you're trying to make your viewers feel about it. Colors can convey a sense of calmness, or give a cheerful air. They may even evoke complex feelings such as sophistication, purity, and creativity. Using the right colors for the job is important to get your viewers feeling the way you want them to feel about your data.

3. Color adds depth to data

Using the same colors for everything in your visualization isn't just confusing, it's also terribly dull and uninteresting. Making use of contrasting colors, gradients, and other interesting color combinations can make your graphs jump out of presentations and grab viewers' attention, and showcase deeper meaning to everything. Want to emphasize a piece of data in your bar graph? Give it a splash of red in a sea of grey.

What Each Color Means in Data Visualization

Individual colors are often associated with some kind of feeling, though this depends on a variety of factors, including whether you're using them in isolation, or as part of a gradient or contrasting palettes. Help Scout has a psychology of color in branding graphic that acts as a great summary of what we're about to cover.

color emotion guide


Yellow is often thought to be bright and cheerful, and may also be associated with clear thought. It's also shown to encourage retention of memory, so it's a great color to use for emphasizing the main point that you want viewers to take away from your presentation. However, too much yellow may generate anxiety.


A relaxing color, green evokes peaceful images of nature and serenity. It's also a symbol of safety and may encourage decisiveness.


Anything red jumps out of a data visualization and expresses powerful emotions in an instant. It's perfect for emphasis and calling attention to data against the background.


A powerfully positive color, blue provides feelings of trust and loyalty. No wonder it's such a common color scheme in corporate settings.


Pink is a very feminine color and dampens feelings of aggression. It can help illustrate positive trends in data that you want your viewers to feel happy about.


Yet another earthy color, brown is a great choice for infographics and charts about environmental issues.


The all-important black provides a sense of solidity and authority. A bold black against less emphatic colors can illustrate a powerful perspective, while the more sparing use of black can evoke sophistication.

Remember that these are only general examples of how each color affects perception. These examples may change completely dependent on so many different factors and contexts, which include the nationalities of your viewers, the industry you're working in, and whether the colors stand alone or are part of a scale.

Tips for Improving Your Use of Color

Color can't just be thrown around haphazardly with the intent of making your viewers feel one thing or another. You risk creating a visually chaotic beast that distracts them rather than evokes the feelings you want. Here are some tips to help improve how you use color.

1. Have a wide dynamic range of colors.

When using a gradient, you want the difference between each color element in your palette to be easily distinguished. That means that they should vary enough in brightness to be distinguished effectively. This is very helpful, especially for colorblind viewers!

2. Use colors consistently across graphs.

If you have certain variables that are repeated across different data sets, you should whenever possible use the same colors for them. This makes for a sense of consistency that will make it easier for your viewers to relate to the data.

3. Use plenty of contrast.

A great range of colors is no good if your viewers can't even see them when projected. Use great contrast between background colors and text or data colors so that your visualizations are more readable. Smaller text especially deserves greater contrast against the background. On top of this, make sure that you test your presentations on a projector before you present projectors' colors may look very different from the colors on your phone or laptop screen.

4. Use appropriate colors for low and high figures.

When illustrating a gradient that indicates a scale of low too high, you want light colors to represent the low values, and darker colors to represent the high values. This is a great way of showing a heat map.

5. Use gradients whenever you can&

Gradients are amazing for comparing and contrasting data and feel amazingly natural when you read them on a graph. Having unrelated colors in such a situation can make the data more difficult to read.

6. &except when illustrating categories

A gradient almost always implies a ranking or a comparison, so if you are showing categories that aren't quite related or intended to be compared in a low-to-high scale, then use disparate colors with different hues.

Color is Key

Color in data visualization doesn't just have a small impact that can be ignored but represents one of the most important ways of getting your viewers feeling the way you want them to feel about what you're presenting. Make expert use of color to get your point across, and truly level up your data visualization game.


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