DataOct 24, 2019

3 Tips for Creating Data Visualizations With Impact

Kyler Starks

A majority of the population—65% of people—are considered visual learners, according to the William Bradford. An even more compelling figure is that we retain at least 80% of what we see. From these two findings, we can infer that visuals, and by extension data visualizations, are an enormously powerful tool to transmit a message.

In this article, I will highlight three ways that we take advantage of these statistics by making visuals more impactful, specifically as they relate to data analysis. While there are many ways to make visuals with impact, we will focus on three best practices that can be applied across any industry or job function.

1. Keep It Simple

When consuming visuals, our brain—specifically our iconic memory—can process eight to nine images at a time but only recall four to five images after the images are no longer present, according to psychologist George Spurling. This helps to bolster the case to “keep it simple,” because we will not retain all that we see. We can infer that simplicity in the number of, type of, and colors present in visuals help the audience to retain the content long enough for it to make an impact.

Here are a few key takeaways to keep your dashboard simple:

  • Clearly articulate the dashboard name and focus.

  • Limit the number of visualizations to four or five.

  • Keep colors limited so the audience can recall the significance of certain colors.

The visualization below from BoardEx gives a clear example of how simplicity can have a greater impact.

2. No Explanation Needed

Think about an elevator pitch (i.e., a short, quick summary of your role, company, or initiative). Visuals only make a first impression once, so any time spent clarifying findings can take away moments the consumer could have spent viewing the content. The elevator pitch is a great way to convey key points without over-explaining.

Being mindful of who the audience is and how they are conditioned to receive information can help reduce the need for explanation. By limiting unneeded questions, consumers have the space to truly view and question the content itself. Information should be presented in a way that answers the following questions:

  • What is the goal of the data visualization?

  • Does that data support the goal of the data visualizations?

  • Do the visuals support the goal of the data visualizations?

  • If the consumer of this data has never seen this visual before, would they understand the data visualizations?

3. Be Persuasive

As I mentioned earlier, visuals have large impacts because most of the population are considered visual learners. The way content is presented and the audience’s relation to that information goes a long way toward persuading potential action on the part of the consumers of those visualizations. According to Nigel Duckworth, persuasion occurs when the consumer understands the context because the “graphic by itself carries no power to persuade.” When we consider the audience’s response, targeted analysis that answers key questions can cause a person to ponder, question, and act on findings. Consider the following questions when creating a persuasive visual analysis:

  • What is the desired response?

  • Are we simply informing others?

  • Are we creating a call to action?

  • Are we reflecting on past behavior?

simple is better

In any situation, simplifying our message is always key. The more we understand the audience the better the visual will be received and the higher the likelihood they will be persuaded to act or change their behavior. Please feel free to reach out to me at with any questions about how to best build your data visualizations.