[ Updated Mar 8, 2023 ]
There’s a lot of talk about the importance of data in marketing but what is data without presentation? Just a bunch of numbers.
Whether you’re presenting data to internal stakeholders, analyzing it to aid decision-making, or even communicating data to your customers — what’s important is presenting it in a manner that’s easy to digest and understand.
How can marketers use data visualization to engage audiences?
As marketers, we regularly deal with a lot of data, and data visualization helps us communicate that data more effectively. It uses visual elements to tell a story within the data while making it more engaging and easily accessible.
Marketers can use data visualization to:
- Make content such as blog posts, social media posts, ebooks, reports, and presentations more engaging
- Identify trends, patterns, and outliers
- Reinforce an argument or opinion
- Make informed decisions
Let’s take a look at how you can present data visually to engage your audience and communicate effectively.
1. Establish the key objective
We can all agree that there is no dearth of data today. However, the challenge lies in turning that data into actionable insight.
Before you start visualizing any data, ask yourself three questions:
- What do you want to achieve through the visualization?
- Who is your audience?
- Which data points are relevant to your audience?
The idea is to keep the data visualization focused on a specific objective as opposed to overcrowding it and confusing the reader.
Take a look at this simple pie chart by HubSpot. The goal behind this post is to show how sales leaders don’t have enough time to do their actual jobs — and it succeeds in clearly conveying that message.
Similarly, it’s important to keep your audience in mind and take into account data points that are relevant to them.
Let’s say you’re presenting a report on your Facebook ad campaign performance to the senior management.
Avoid reporting vanity metrics such as reach and likes. Instead, stick to presenting actionable metrics such as leads generated, return on ad spend, and website traffic.
2. Choose the right data visualization
Now that you know the story you want to tell, you need to pick a data visualization that will help you communicate that information in the best possible manner.
There are different types of data visualizations, and each has a specific purpose:
- Infographics: to give an overview of a topic
- Charts: to compare, show change or reveal relationships
- Diagrams: to map out processes, connect ideas and identify root causes
- Maps: to display geographically located data
Selecting the wrong visualization misleads the reader, causes confusion, and spreads misinformation. For example, you can use a bubble chart and pie chart to present the same data but they might communicate two completely different things.
Look at this visualization.
What does it tell you? Chances are, nothing because reading it is such a tedious task. It would have been a better idea to use a table to present this data instead.
Here’s a cheat sheet to help you pick the right chart for your data.
3. Add context
The data visualization you create needs to be functional in its communication. It needs to strengthen your narrative and give meaning to the data you present.
This is why it’s imperative to contextualize your data visualization. Doing this adds clarity, enables readers to derive value from it, and understand it better.
Here’s an example of a chart with no context. It makes you wonder what the creator is trying to say, doesn’t it?
Simple additions such as labeling the axes and inserting a legend would have made it a lot clearer.
On the other hand, look at this bar chart. It is well-labeled and highlights the percentages for added clarity. One glance at it is enough to understand the key message.
Here are some ways to add context to your visualizations:
- Provide color keys or a graph legend
- Label the axes
- Use annotations to highlight important points
- Add a title
- Use colors wisely
4. Incorporate colors and bold fonts
Colors and fonts have a larger purpose than just lending to the design. Using colors strategically can help you:
- Emphasize points
- Illustrate progression
- Categorize information
- Distinguish between data points
Choose a single color (with gradient variations) to show continuous data and contrasting colors when you’re making comparisons. You can also use a bold color to highlight a specific data point.
Similarly, make sure you use bold fonts to make the text on the visualization easy to read. Don’t go beyond three font types in one visualization as that can end up distracting the reader.
Here’s an example of an infographic that is functional and visually appealing because it uses colors and fonts wisely.
5. Remove clutter
You might be tempted to beautify your data visualization or make it look fancier but stop right there. Before adding any design element, ask yourself if it’s adding any value.
Data visualization pioneer Edward Tufte refers to all the unnecessary “decoration” as chartjunk.
He says, “The best designs are intriguing and curiosity-provoking, drawing the viewer into the wonder of the data. But no information, no sense of discovery, no wonder, no substance is generated by chartjunk.”
Here’s an example of a cluttered data visualization. The 3D effect adds no value to the chart. All it does is make it difficult to comprehend.
So, avoid using too many colors, decorative fonts, irrelevant icons, and any other elements that tend to distract the reader.
Remember: the idea is to make your data visualization as simple and easy to read as possible.
6. Avoid data distortion
In your attempt to design an effective data visualization, it’s important to ensure you don’t distort data and falsely present it.
From the type of chart and sizing to the colors and shapes you use — every aspect needs to be closely looked at to present your data accurately.
Here’s an example of a misleading COVID-19 graph. As you can see, the number of days between each date is inconsistent on the x-axis while the y-axis starts from 0 to 5,000, and then jumps to 20,000.
Here are some ways to avoid distorting data:
- Add labels to offer clarity
- Clean your data and keep the data visualization simple
- Use a chart maker to create the right kind of visualization for your data
- Start the vertical axis at 0
- Don’t manipulate the x-axis and y-axis
- Follow visualization conventions (eg. using light colors for lighter density and dark shades for higher density, etc.)
Data visualization for marketers: the key takeaway
As marketers, you can use data visualization to improve communication and boost your content marketing efforts. These six tactics will help you create visualizations that are not only pleasing to the eye but also communicate information effectively.
Editor’s note: By far the easiest way for marketers to visualize data is with Google Data Studio, which is a free dashboard building tool. If you want to pull data from popular marketing and sales platforms like Facebook, LinkedIn, HubSpot, Salesforce, and many more, you can start your free trial of Supermetrics for Data Studio today.
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