Content

For data storytelling, start with the story

Numbers are not words, but they can tell a story. That is the starting point for “data storytelling.” Digital marketers have to craft narratives that tell their target audiences everything they want to know about a product or service.

In her keynote at MarTech, Nancy Duarte spoke about the importance of turning data into stories. Here we take a deeper dive into the art of doing so. And yes, just know this up front: turning numbers into words is an art as much as a science

Data, Meet Narrative

All the experts we talked to agreed on one general point: start with the story, then find the data. “You are using digital assets or channels to tell a story that is emotionally gripping,” said Bill Ross, founder of Linchpin SEO.

“Great storytelling is how you build context with data (facts) so people care,” added Robert Rose, founder and Chief Troublemaker at the Content Advisory. “Data by itself is meaningless.” Data has to act as the supporting structure of the story, much like the girders in a building. Data is not the story itself, he pointed out.

Taking the concept one step further is Amy Balliett, founder and CEO of Killer Visual Strategies, a Material Company. The story must be tied into a strong visual image, which helps create meaning for the narrative.  More on that later.

Watch Nancy Duarte’s keynote here.

Where to Begin? Where to Go?

Yes, good old-fashioned writing and editing are the building blocks of data storytelling, no different from the techniques used to produce this article . But some differences in technique are telling.

Ross laid out the fundamentals: understand the client, so you know what story they want to tell. Start with the end goal, so you know what you are going to say. Use the data that supports that “end narrative.”

“Follow Pixar’s advice. Start with the end in mind,” Rose added. No matter if the project is a blog post or a white paper, “I write the last paragraph first, so I know where I am going.”  

Killer’s Balliett noted the resemblance between the data story and the three-act play. Say the data story’s goal is selling a baby swaddler to new moms. The introduction (Act 1), lays out the “problem” — getting the baby to fall asleep. The storyteller can dig through the science and offer up data to point out the problem. In Act 2, the storyteller brings up the product that will solve the problem — the baby swaddler — and how it is relevant to solving the problem. Act 3 is the call to action — buy this product.

Focus, Focus, Focus

This is the hard part. The temptation to say everything is strong, but all that detail will drown the message. How do you bring your message into focus, ignoring the marginal periphery?

Here Balliett parts company with some of her peers. Narrative is half the effort in data storytelling, while good visual graphics act as a story multiplier. “We are driven by visuals. We have to focus on paring down the text as much as possible,” she said.

Balliett pointed out that a typical online audience will read only 20% of a story that runs at least 600 words or greater. Here she cited the “BuzzFeed” effect, where stories are broken up into blocks of 100 to 200 words, each block separated by a picture, with the story driven by headlines of 10 words or less.

“The brain takes four to eight seconds to register text. It takes one-tenth of a second to recognize data visualization.” Balliett continued. For millennials and Generation Z, that attention span averages five seconds, she added. And this generation is digitally native, accustomed to receiving data from more than one screen at the same time.

For Ross, data storytelling is still about writing a concise narrative. If the story clocks in at 20 minutes, knock it down to 10, Ross said. “Make sure the narrative flows properly,” he said, and take out any bits that don’t contribute to the story.

There are also off-ramps and forks in the road of that narrative as well. Here Ross flags the opportunity to put in “sub-narratives”, providing more data that answers questions that are raised by the main story. While one would think this distracting, Ross notes that this increases reader engagement. The data is still telling the story, only in side-bars that bring the reader back to the main story.

For Rose, structuring the data story also provides focus. One screenwriting technique offers a useful template: tell the same story in one paragraph, then one page, then 10 pages, then in a 30-page brief, and then the 120-page screenplay. Applied to data storytelling, that means telling the same story in a 5,000-word white paper for specialists, or a 500-word version for the generic client.

Client feedback will also affect length. Rose recalls one project where clients thought the 500-word blog post was too shallow. So the team upped their game, producing daily blogs running 1,000-1,500 words. Now feedback showed this was too much information. “Over the next three to five months, we evolved an editing strategy.” he said, so the longer pieces were produced only once or twice a week.

The Twist Ending (Spoiler Alert)

So where will data storytelling go next?

“I think getting caught up in the next big thing is not the way to go,” Ross said. “There has got to be a solid foundation with content that tells a narrative,” he said. “It has got to be crafted.”

That includes images, but again, one can’t just throw stock photos at a story and expect them to stick. “The image has a purpose in itself to tell a story,” Ross said.

Balliett was more skeptical about the future of text in data storytelling. The trend was “using as little text as possible,” she said. “ At the start of ‘09, I thought this would die. I thought the written word would win in the end. But we are moving more towards visual communication.”

People will be judging books by their covers, Balliett said, so every brand should be putting the best cover on their metaphorical book to get people to crack it open.

For Rose, the future looks more mixed. The Web may have started as an extension of print, but creative people are “pushing the medium to what it is good at–interaction.” he said. “Technology has evolved to make those efforts easier for content creators and consumers.”

That means consumers will “experience” the data story, not merely read it. Marketers will be pushing this envelope through advances in interaction, Rose said.

So do not be surprised two years from now when you read a follow-up article on this piece. It may speak to you in a podcast, show the data through a series of interactive graphics, or even toss in a short video or two. 

But the article won’t be a pile of words on a printable page.


About The Author

William Terdoslavich is a freelance writer with a long background covering information technology. Prior to writing for MarTech Today, he covered digital marketing for DMN. A seasoned generalist, William covered employment in the IT industry for Insights.Dice.com, big data for Information Week, and software-as-a-service for SaaSintheEnterprise.com. He also worked as a features editor for Mobile Computing and Communication, as well as feature section editor for CRN, where he had to deal with 20 to 30 different tech topics over the course of an editorial year. Ironically, it is the human factor that draws William into writing about technology. No matter how much people try to organize and control information, it never quite works out the way they want to.

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Channel: Martech: Content – MarTech Today

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