Core Elements of Compelling Data Visualization

Shantanu DixitOctober 21, 2014

A picture is worth a thousand words, so the maxim goes. And when it comes to influencing business decisions, it couldn’t be truer: a clearly presented, persuasive data visualization can drive action. Done right, compelling graphics can even close deals for you.

But getting to that point — deploying graphics carefully built on rich data sets — takes planning and expertise. What are the core elements of successful data visualization? Here, a look at what powerful data visualization entails.

A solid foundation

First, it’s crucial to understand the foundation of good data visualization: the quality of the data itself. As a rule of thumb, solid data sets have metadata, or information about the data, such as what it is, where it was collected, when, how, and by whom. Having this information increases the opportunity to play with, interpret, and gain insights from the data.

Second, your analysis of your data — and the insights you uncover from it — must be relevant to your audience. What insights are they looking to gain, and what is the purpose for which the information is being examined? Your data must also be original — and not the product of another company in a similar line of work, or a purchased set from a marketing firm.

If your data fails any of these criteria, then no visualization can make it valuable. Consider using it for something else.

Understand the audience

An audience of experts will have different expectations than a general audience. So: who is in the audience, and how will they read and interpret the information? Can you assume the reader has shorthand knowledge of the relevant terminology and concepts, or do you need to spell out the basics? Misunderstanding the audience is the easiest way to lose your reader. Conversely, knowing your audience well is the best way to reel them in from the start.

It’s also important to consider how the audience might use the information. How might they take action based on what you’ve taught them? For instance, an exploratory visualization should leave viewers with questions to pursue, while an educational or conformational visualization should not.

Set up a clear framework

To ensure that everyone viewing the visualization is on common ground, you have to set up a clear framework. This means clearly defining the semantics and syntax under which the data information is designed to be interpreted.

Semantics pertain to the meaning of the words and graphics used. Syntax involves the structure of the communication. For example, when using an icon, the element should bear resemblance to the thing it represents, with size, color, and position all communicating meaning to the viewer.

Lines and bars are simple, geometric figures that are integral to many data visualizations. Lines connect, suggesting a relationship. Bars, on the other hand, contain and separate. In studies, when people have been asked to interpret an unlabeled line or bar graph, they overwhelmingly interpret lines as trends and bars as discrete relations — even when conflicting with the nature of the underlying data.

It’s also key to ensure that your data is clean and you understand its nuances. Does the data set have outliers? How is it distributed? Where does your data have holes? Are you making pre-judgments about the data? Real-world data is often complex; is often of diverse types and from a variety of sources; and is not always reliable. Getting to know your data will help you select and appropriately use a framework.

Tell a story

Few forms of communication are as persuasive as a compelling narrative. To this end, the visualization needs to tell a story to your audience.

Stories package information into a structure that is easily remembered. This can be an important aid to decision making in collaborative scenarios, wherein an analyst may not be the same person as the decision maker. The narrative, or the story, can help information travel through the decision chain in a positive way.

Ultimately, the goal is to enable the viewer to observe, understand, and make sense of the information. Design that prioritizes storytelling can significantly affect end-user interpretation. Good designers know not just how to pick the right graph and data range, but how to be a compelling storyteller through the visualization.

Are you looking to boost the power of your data visualizations? InfoCepts works with companies every day to improve methods for data presentation and delivery. Contact us to start the conversation.