What is data visualization and how can you use it in content?

Data visualization is the graphical representation of information and data, presented so that the data is easier to understand than if it were presented in its raw form.

Most people would rather look at a chart or graph than read through an Excel spreadsheet. It’s easier to digest and understand the data, draw insights, spot patterns, and identify how the data connects to other trends. In fact, it would take data experts an average of 9 hours longer to see patterns, trends, and correlations in their company’s data without data visualization, according to SAP.

Although data visualization is a powerful tool for relaying information in content, it is also an essential part of strategic planning. Enterprise companies sit on mountains of data, but sifting through them is a significant challenge. Data visualization provides a means for time-strapped decision makers to understand that data and draw insights from it.

Examples of Effective Data Visualization

Fortunately, with most data sets, basic but stylized charts and graphs are all you need to convey valuable information.

Here’s an example from HubSpot. They wanted to know the optimal number of words to have on an infographic to encourage sharing on social media. They discovered that the most popular infographics had some of the shortest word counts:

(Source: HubSpot)

While they could have discerned this information by looking at a spreadsheet, it would have taken much longer to draw this insight. With this simple visualization, not only do they have a solid understanding of how they should produce infographics in the future, they can present the information more effectively in content.

Data visualization doesn’t end with charts and graphs. New modes of visualization are emerging all the time, and they have far-reaching implications for how companies understand their customers and their own operations.

Instacart, a grocery delivery brand, wanted to identify the logistics challenges of their delivery routes in specific cities. Below is a visualization of delivery routes in San Francisco, Austin, Boston, and Miami, and the frequency in which those routes are taken by delivery drivers:

(Source: Jeremy Stanley)

They were able to dive deeper into this data and color-code which stores their shoppers were using and to which neighborhoods they were delivering those groceries, specifically. Here’s San Francisco again with color-coded routes representing drivers and the specific stores with which they interact:

(Source: Jeremy Stanley)

Obviously, this information is extremely valuable to their operations. Their business depends on timeliness and accuracy, and by identifying challenges in their deliverers’ routes and drive times, they can find new efficiencies to improve the customer experience.

Data visualization is finding its way into more disciplines, including unexpected academic areas like the humanities. Digital humanities, for example, is an academic field at the intersection of computing, digital technologies, and the traditional humanities, such as art, literature, and human history.

You may be wondering how you could possibly apply data visualization to these fields. Here’s a visualization representing individuals in the social circle of French Enlightenment figure, Voltaire and the frequency with which he corresponded with them:

(Source: Stanford University)

Maybe only academics and Voltaire fanatics would be interested in this visualization, but the fact that it can be created at all has powerful implications for what we can accomplish with visualized data — and for what we can understand about ourselves through it.

Moving forward, more and more universities, companies, and organizations will rely not only on static data visualizations but also interactive and real-time visualizations to communicate data more quickly and effectively.

How to Use Data Visualization in Content

While many of the most complex data visualizations are better left to data scientists and programmers, there’s still plenty you can do with data visualization to enhance your content, especially if you’re using survey data as a springboard.

You could summarize your survey findings through text alone, but you’d be doing your audience a disservice. Data visualizations (usually in the form of charts and graphs) provide an easy way for you to communicate your findings, especially to those readers who would otherwise only skim your content. That’s why you’re marketing to executives or decision-makers, data visualization is a must.

We recommend combining your data visualizations with callouts to highlight key data points that might be of interest:

This way, even if someone skims your report, they get the most important information first and can refer to your content later if they want to go deeper.

To learn more about how you can use survey data and data visualization to enhance your content, reach an analyst today.