Best Colors for Graphs: Color Adoptions for Your Visualization to Make Them Persuasive

The visual design has become an essential part of business around the world. No longer is it enough to create a website or graph without a plan in mind like it was a decade or two ago. Customers and visitors have higher expectations.

By implementing the best colors for graphs in your design, you can make a great impression on your target audience, communicate your ideas more clearly, and persuade your audience with your graph or other visual aspects.

This article will discuss which colors are best to use in your graph, depending on your audience and goals. That way, you can make your digital assets more persuasive and, ultimately, build trust and boost your bottom line.

Table of Content:

• The Importance of Colors
• The Meaning of Color in Our Lives
• How to Define Thoughtful, Useful Palettes
• Things to Keep in Mind when Choosing the Best Colors for Graphs
• Do’s and Don’ts for Data Visualization Colors
• Common Data Visualization Color Palettes
• ChartExpo Examples

Let’s get started.

The Importance of Colors

Colors are essential in persuasion because they produce an emotional response in the brain due to a chemical reaction – and emotions are king in coercion. Colors can create thoughts, memories, and new associations with people, places, events, and brands. Understanding this helps you choose the best colors for graphs.

Each color is unique. For instance, red has a longer wavelength and is recognized faster by the brain. On the other hand, shorter wavelength colors such as blue tend to be more soothing and lower pulse rate and blood pressure. In the case of yellow, it is a medium wavelength color that still generates attention.

Due to the unique differences between colors, they affect how audiences perceive your graph data. If you’re looking to help your audience relax, you might opt for a soft light blue color instead of yellow, which could create anxiety.

Even the various shades or hues of colors can create different feelings, such as the difference between light red (joy, love) and dark red (anger, confidence, passion). Smart businesses leverage these color differences to influence how their customers feel — such as cafes using orange and brown colors for a relaxed, homey feeling.

However, many brands fail to properly use colors in their brand messaging, such as graphs. It would help if you mapped your brand palette to your data visualization. Data scientists and analysts don’t often focus on presenting information with brand colors or color strategy.

And even if your data team is good at incorporating brand colors, these colors aren’t often chosen with data representation and psychology in mind. To help you better understand how to choose brand palettes, let’s first discuss the meaning of different colors in different contexts.

The Meaning of Color in Our Lives

Humans can experience color in vastly different ways. Every person’s unique mix of emotion, mood, cultural, and societal context influences their associations with different colors. But some color combinations have almost universal connotations, and these are essential in understanding the best colors for graphs.

Take, for example, red and green. These colors are typically understood to have opposite meanings. One of the most prominent examples worldwide is the standard traffic light, with red, yellow, and green universally indicating “stop,” “stop, if safe to do so,” and “go,” respectively.

Red is an universal color that often represents danger, caution, or troublesome information. However, it can also mean power and confidence, such as with a sports brand.

And colors can have connotations in specific environments such as hospitals. One hospital surveyed its visitors to see the quality of service they were receiving.

Each team in the hospital had a different form and color printed to be given to those visitors who interacted with them. The data analysts took the results and created a graph using distinct colors for each team to understand it easily.

Using the best colors for graphs makes it easy for stakeholders to glean insights from data.

How to Define Thoughtful, Useful Palettes

Let’s say you’re creating a dashboard to show your Google Ads performance.

You only have two or three memorable brand colors to work with, but your chart needs to showcase individual performance for each of the 18 campaigns that your agency has.

Recycling a three-shade palette won’t be effective. One color cannot represent four different categories of ads.

Every time a team member sees the dashboard, they’ll be forced to pause and examine tiny legends or labels to get any kind of insight. That dashboard needs to be useful even for those taking a glance while walking past.

So what are your options? When deciding on the best colors for graphs, a standard method is to turn a few brand colors into many and progressively decrease saturation and darken the hues.

This quickly results in a muddy, unappealing chart. Another method is to generate an extensive array of random, non-deliberate colors. Maybe you have some tertiary brand colors that don’t get used very often or swatches that you can pull from your product’s interface.

Even if you manage to find enough distinct shades, there may not be enough contrast between them, and it’s unlikely to appear cohesive. None of these options led to high-impact data visualizations.

To deliver on-brand visualizations with lots of categories, take the time to define a 20-color brand palette. You can keep the simple, pared-down palette for more straightforward visualizations; there’s no need for a single, perfect palette that works on both a chart with two series and one with twenty.

A great way to generate this more extensive palette is to use lighter shades of your original colors in between each to stretch the palette out. Let’s use these five swatches as an example of a primary brand palette.

To grow that palette from five shades to ten, we started by duplicating the original five shades. From there, we increased the lightness and adjusted the hue to create enough contrast.

How to Avoid Misleading Data Visualization in Different Industries

When it comes to storytelling with data, the critical part to keep in mind is that each industry interprets colors somewhat differently. Not only that, but different industries tend to use a specific subset of colors and data visualization color schemes more often.

No matter what your data visualization inspiration is, it’s not about choosing the most beautiful color or going for more colors than necessary. So, instead of including too many colors, select a subset that everyone in your field knows well.

Things to Keep in Mind when Choosing the Best Colors for Graphs

Poor color choices and other inferior design choices force users to 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. Keep these factors in mind:

Your Target Audience

You need to know who your target audience is — who they are, what’s important to them, and how their specific background or culture may affect how they perceive the colors you choose. This factor is a mission-critical aspect of selecting the best colors for graphs.

For instance, in certain Asian cultures, gold and red colors represent good fortune and financial success. It may be wise to include these colors in presentations to investors or potential clients from Asian geographic areas.

Appropriateness

Certain colors are more appropriate to some industries than to others. Sometimes, colors just feel wrong to your viewer because they don’t match your expectations.

For instance, you 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.

Do’s and Don’ts for Data Visualization Colors

There is no single right way to use color. However, we can use what we know about how the mind responds to color to apply it to our data visualization and improve our results. Based on this, let’s talk about some essential dos and don’ts regarding colors:

Do Use Color to Create Associations

As with all designs used for communication, good data visualization design harnesses standard conventions and uses them as shorthand. For the same reason that UX designers always use a cart icon to indicate the button e-commerce consumers should click to complete a purchase, data visualization designers use colors to trigger associations and streamline understanding.

For example, you may use orange to represent performance, deep green to describe profit. Color palettes can also create associations in the viewer’s mind, such as the colors of a country’s flag communicating data related to that country.

Do Use a Single Color to Show Continuous Data

Be sure to use a single color in various gradients to communicate amounts or numbers of continuous data. Using one color will help viewers quickly grasp that they’re viewing increases or decreases in a single metric, such as the CTR. Otherwise, you make the viewers’ job more difficult, which can affect their attention span.

Do Use Contrasting Colors in Comparisons

When you’re comparing or contrasting two metrics, using contrasting colors will help viewers feel that you’re differentiating between the two. You might be showing the difference between the conversion rates on two campaigns, for example. In this particular case, you might use contrasting colors associated with the two different conversions of campaigns, light blue, and purple.

Do Use Color to Make Important Information Stand Out

When you are trying to highlight something important, such as data relevant for conversions of a particular campaign, a bright or saturated color can help it stand out. Marketers do this all the time with their Call-to-Action (CTA) buttons.

In terms of graphs and charts, you may choose to use gray for less-important variables and a deep red or orange for the most crucial variable, for example. Alternatively, you could use muted colors for the less-important options and a bright color for the most important ones. The key is that important variables draw the eye immediately by having a vastly different color than your data visualization elements.

Don’t Use Colors that Are Not Easily Distinguishable

We’ve all been frustrated by charts that leave us squinting to determine what numbers are relevant to what variable. You want viewers to be able to interpret data at a glance. For this reason, the best colors for data visualization are easily distinguishable.

Keep in mind that your audience will be quickly frustrated if they have to do extra work just to distinguish different data points. This response may cause resentment and backfire on you whether you are presenting life or using charts on your website.

Don’t Overload on Too Many Colors

Because the brain struggles to process many different things at once, using a limited color set in your visualizations will improve speed to insight. Just as in the famous supermarket jam experiment where 97% of shoppers were so overwhelmed by the 24 jam choices that they failed to purchase any, similar problems can arise for you.

Try to stick to seven or fewer colors in a single visualization, the maximum number of items that the brain can hold easily at one time. Only use more than this if it is absolutely necessary to represent all of the categories in your visual. Knowing the best colors for graphs is also knowing the number of colors to use in the first place.

Don’t Forget Accessibility

Everyone has different visual abilities. Some people may have difficulty distinguishing between various colors if they have a vision deficiency, such as color blindness. Be aware of common colors that fall into this category, such as red and green or black and green together.

This accessibility concern is not always avoidable. Therefore, use keys that describe the different colors and what they represent. Furthermore, using stripes or other patterns over specific colors will help differentiate them clearly, even if someone cannot see the difference between the base hues.

Common Data Visualization Color Palettes

You don’t always need to reinvent the wheel to achieve quality color combinations. Certain color palettes are based on standard conventions that your organization may find useful as a starting point or even an exact template.

Qualitative

Qualitative palettes are useful because they use the best practices discussed above mainly by ensuring each color is unique and distinct. This is ideal when variables are unrelated to one another or when there is a lack of subcategories.

For instance, creating a graph showing various business Key Performance Indicators (KPIs) such as sales, marketing, and customer service data will benefit from qualitative palettes. Each section represents a unique business process and team, which is quickly identifiable by the various colors (such as red, blue, and yellow).

Sequential

Sequential palettes are essentially the opposite of a qualitative palette. They use a single color but with varying saturation levels. Sequential palettes are handy for representing a single metric over time, such as money.

You can use them to show how much your revenue has changed year-to-year, for instance. You can choose a green color representing your average revenue over five years, with lower and higher revenue amounts being lighter and darker shades of that green, as an example.

Diverging

A diverging palette is a spectrum from left to right. One on end, you have one color, and on the other end, a different color, with the middle being a neutral color that is a mix of the two. Diverging palettes are useful for showing where a variable sits on that spectrum, such as your customer happiness based on recent surveys.

Making Visualizations More Accessible With a 3rd Party Tool

There are several issues you might run into when attempting to visualize various data points for your organization. If you have just one or two (or otherwise limited) brand colors, you might have trouble making your visuals easily scan able.

For example, using just a few colors can distinguish adjacent visuals on a graph, but not for comparisons with thin overlapping lines. Ideally, your graph will be easily viewable regardless of the proximity or shape of your elements.

A useful feature from a third-party tool is comparing the values of your different sizes and proximities to ensure they contrast adequately. A tool like ChartExpo can achieve this by testing the differences of colors between line charts, overlaps, and legends.

Another situation where a tool like ChartExpo helps is creating charts on dark backgrounds since they are usually built on lighter backgrounds. ChartExpo helps you by giving you the feature to make changes to lightness and saturation. This helps average viewers and especially those with visual impairments.

Another useful feature of ChartExpo is that you do not need any coding expertise to create basic to complex visualizations which makes it one of the best no code data visualization tool. You can create all visualizations in few clicks due to which it is very easy to use.

ChartExpo Examples

Let’s take a look at various graphs produced using ChartExpo. This outline will give you a better idea of how this tool can work with your current workflow or speed up your process while making your visuals more effective.

Donut Chart

Let’s say you want to represent impressions for different keywords for your client. You can make a donut chart in ChartExpo for this. Let’s say you want to change the colors to show impressions of keyword 1 with purple, keyword 2 with teal, keyword 3 with pale green, and keyword 4 with blush.

You can achieve the color change with the following steps:

1. Click on: Edit Chart.

2. Click on the pencil sign > box > color box, and you can choose whatever color you want.

3. Click Apply.

4. Once done editing, click on save.

5. Now, click add chart to sheet or click on export.

Just like that, with a few simple steps, you can edit your colors to meet your brand guidelines and other best practices. You can add the chart to a current sheet or choose to export the file to be added to another program, saving your team a lot of time and hassle.

Dayparting Chart

Another example of ChartExpo library is creating a dayparting chart. Let’s say you have a Google Ads campaign, and you want to know which day and time is costing your company the most money. That way, you can manage your campaign according to this data to be more efficient when spending your budget.

Let’s say your current chart is blue, like the image below.  However, blue might not press upon your team how important and potentially dangerous it is to spend too much on advertising. Therefore, you want to change your chart to a more appropriate color like red.

You can achieve this color change with the following steps:

1. 1. Click on: edit chart.

2. Click on pencil sign > bars > start color and end color. Click apply all and click save.

3. Either click on add chart to sheet or export to put your chart to use.

And just like that, you’ve completely changed the colors of your chart. Using a third-party tool like ChartExpo is an excellent way to be more efficient as a team. That way, you can reduce overhead costs and deliver better value for your clients.

Wrap Up

Vision is one of the only five senses, other than sound, that can communicate data through either a presentation or online. This makes it crucial to displaying and analyzing data, whether in-house or to your customers.

Color is a critical component of the visual sense, and you need to choose the best colors for graphs and other business tools to convey information. By understanding how color affects your audience and using the tips above, you can be more precise, persuasive, and successful when presenting visuals to your market.