21st-Century Storytelling: How Data Tells Stories

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Visual storytelling is an incredible approach to telling a story: it uses visual communication to craft a narrative that explains a concept and evokes an emotional response. It often combines illustration with compelling, carefully crafted text, and it’s a familiar strategy across platforms these days. (To learn more about visual storytelling, check out an SXSW 2018 chat with Killer CEO Amy Balliett, filmed for our video series on all things visual, The Visual Minute.)

But we can also use numbers and data visualization to tell stories. Numbers have inherent meaning that we can learn to interpret. If you’re not already using numbers and data in the same way you use language to craft stories, your content might be falling far short of its potential to educate and engage.

The Science of Storytelling

By taking a more holistic approach to communication — through words, numbers, and visuals — we can learn how to tell stories in a unique way. Whether visualizations are lending meaning to large troves of complex data or simply accentuating a number to give it further meaning, leveraging figures combined with visuals can create these engaging stories.

This isn’t to say that visuals cannot stand on their own. In plenty of cases, they can and do. But no matter how you look at it, our brains benefit from storytelling by helping us understand various complexities of life. In fact, researchers have found that the brain hardly makes a distinction between living an experience and reading about an experience. In both cases, the same areas of the brain receive stimulation.

The Science of Visual Storytelling

visual learners graph

At the same time, our brains also have preference for visuals. Some 65% of us are visual learners. Additionally, compared to text alone, text paired with images improves comprehension by an average of 89%. So, once again, it’s that comprehensive approach to communication that produces results. When it comes to visual data, we aren’t just designing charts and graphs for the sake of it, but because our understanding of that data increases when we see it visualized.

In the age of big data, visual data offers obvious benefits, such as deeper insights and more precision, to many users across industries. But with that territory comes data overload. While modern-day processors can compile raw data, it’s not often understood what that data even means until it is later reordered or presented in digestible way. The data always has meaning — it’s just that we can’t comprehend it unless it’s presented efficiently.

Visual Aid Comprehension Graphs

For example, three groups of economists ran into a similar issue when presented with the same question regarding a dataset. One group was given the data and the standard statistical analysis of the data. In theory, all of the tools needed to answer the question were there, yet 72% of these professional economists got the answer wrong.

Another group was given the same data and statistical analysis, but was also provided with a chart. With the introduction of this visual aid, 61% still got the answer wrong.

Finally, a third group had the raw data and analysis removed, and were only given the chart. They had to simply guess. Of this group, many of who claimed the chart was insufficient, only 3% failed. That’s a 97% success rate — pretty impressive for just one chart.

Developing an Effective Narrative

So the effectiveness and utility of visual data is clear. What many data visualizations lack, however, is a story.

Consider the standard narrative arc. After the exposition comes the rising action, which is a series of separate yet cohesive events presented logically and fluently that lead to a conclusion.

There is little reason why your visual data cannot follow that same story arc. The key to finding a good narrative is to know the ending. What is your conclusion? Everything that precedes it needs to guide the reader toward that conclusion in one way or another — always in a logical and fluent way. If you find yourself attached to a specific data point but notice that it doesn’t necessarily fit within the context of the rest of your story, remove it. Save it for another story.

Choosing the Proper Visuals for Your Data’s Story

The way we choose to visualize data can tell a story. Take something seemingly mundane like a personal budget. We might be used to seeing that sort of data in a spreadsheet, which is good for organization, but not for telling a story. However, if we relocate that same data to a Sankey diagram, something happens. We get a snapshot of a person’s year. Here’s how one web designer from Boston spent his year:

Sankey Graph

 

A Sankey diagram is just one way a visual can turn data into a story. That same data might tell a story differently through an interactive infographic, a timeline, or a motion graphic. In choosing your direction, consider these two questions:

  1. What is my conclusion?
  2. Who is my audience?

If you keep these two concepts as the driving force behind your data’s story, you’ll always have a strong foundation.

Do you have a favorite way to visualize your data? Let us know in the comments.

Tim Sheehan

Author Tim Sheehan

Tim Sheehan is a Senior Content Editor for Killer Infographics. He was born and raised in a small town in Pennsylvania, where he also studied English and Philosophy at the local university. Tim’s career in writing began in New York City, just a couple hours from where he grew up in PA. In New York, he spent time developing a broad editorial skill set, from content marketing to copyediting to breaking news. Tim’s never-stop-learning attitude allows him to approach the unique needs of Killer’s clients with the adaptability needed to reach diverse audiences. He believes in the importance of communication and understanding what drives audiences.

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