“Without data, you’re just another person with an opinion.”
— W. Edwards Deming
Even with data, however, you’re not invulnerable to subjectivity.
The best statistics can’t do a thing if you don’t know how to frame them. That’s where data storytelling comes in. Data storytelling is the art of converting numbers into narratives. It’s taking metrics like conversion rates and customer satisfaction, and explaining how they either tell a story of success (our current campaign is killing it!) or failure (that deafening roar you hear is the sound of a thousand people clicking “unsubscribe”).
But data storytelling is more than just sprinkling your story with statistics. No matter whom you’re using data to convince, be it a boss or a potential client, data alone isn’t enough. Facts and figures are inert unless your audience knows the story those figures tell and what character they play in that story. It means finding the story your data tells and finding the right way to get it across.
So how can you make sure you’re telling a story with your data, and not just slinging statistics? I’ve consulted data storytelling experts and found three general rules that’ll help you craft a tale with your business data. Just keep these three easy rules in mind, and you’ll be telling stories with you data in no time.
1. Know Your Audience
The Odyssey is a great story, but I wouldn’t tell it to someone who gets violently seasick at the mention of the ocean. You’ve got to know who you’re speaking to and tailor your story accordingly. The best story in the world won’t go over well if the audience doesn’t want to hear it.
Alexandra Samuel suggests that the storytelling process should start with a “dream story” the audience would want to read: “I like to start by imagining my dream headlines or tweets: the discoveries that I would love my data to yield.” Starting with this compelling idea it helps her determine the final draft she’ll end up with. It also helps her determine what data she’s looking for.
She credits starting with a gripping idea as a help in the research process, too, saying it “helps me figure out what kind of data is going to be relevant to my audience, and gives me a clear focus when I’m plowing through a mountain of survey results.”
Pinsight Media’s Matt Habiger agrees on the importance of knowing your audience. “You always have an idea of who your audience is before you sit down and look at the data,” he says, emphasizing the audience’s importance. “Understanding who the audience is, and having an idea of what they’re predisposed to, is a big thing when trying to craft a story.” If you’re preparing a data story for someone who thinks in terms of bottom line revenue, a data story that includes figures on your social media shares may not be effective.
However, don’t let an audience-friendly story override your data.
Hypsypops Design owner Andrea Robertson cautioned that “regardless of the data story you want to tell, make sure it’s truthful.” Sources should be “appropriate and reliable, and you shouldn’t cherry pick to get the message you hope to find.” Alex Samuel echoes this. While you should think in terms of a story that will grab your audience, honesty is key. “Think about what someone would conclude if they had access to your full data set,” she advises. If their conclusion would be different than the one your story tells, you may want to rethink that story.
2. Use Your Visuals, Don’t Let Them Use You
While illustrations are wonderful, leaning on them will leave you with a picture book: fun to look at, but without the sort of complexity that grabs the reader. Data visualization software and illustrations both can enhance a story. That said, don’t have visuals just for visuals’ sake.
“First and foremost,” says Andrea Robertson, ensure the visualization is “functional, and that it tells a story effectively, so the text and visuals complement each other.” The visuals shouldn’t distract your audience from your story. Alexandra Samuel suggests that you “use text and visuals synergistically: charts provide full context on the data you’re sharing, while text lest people understand how to interpret those charts.” While it’s tempting to use ornate visuals, restrict yourself to rare graphs that actually aid your narrative.
How do you make sure the visuals complement the story?
For one, make sure the visualization has all the necessary information on it, clearly visible. “In terms of putting the whole story out there for the reader to get, I put that on the graph itself.” The idea’s similar to what kids learn about making charts in elementary school: title the graph, and make sure information is properly labeled. “What do you want to draw readers’ interest towards?” asks Matt Habiger. “You might want to include a line of text that reiterates the visual’s main point.”
There are ways to make sure the visual is appealing, too. “I always use a clear, sans-serif font, so even on a small scale like a social media post, the reader still has a chance to see the text,” says Robertson. “Big blocks of bold color and sans-serif fonts tend to go well together.” You should also consider the right kind of chart for the situation. “The point of a bubble chart is to draw attention to something higher than expected,” adds Matt Habiger, which makes it good for instances like showing differences in retail sales.
A good example to keep in mind might be the Harry Potter books. Mary Grandpre’s illustrations that begin each chapter grab the reader’s attention with something interesting, and set the tone for the chapter. Grandpre’s illustrations suggest important or interesting happenings, but they always match the tone of the story. They also don’t distract from the story of the boy who lived.
3. “Read Like The Wolf Eats”
I was once lucky enough to see Gary Paulsen, author of Hatchet, give a lecture. When someone asked him what they had to do to become a better writer, Paulsen’s advice was simple: “Read like the wolf eats.”
The same advice works for data storytellers.
In the same way, a good storyteller can take inspiration from any text, a good data storyteller can find ideas in the ever-increasing wealth of data storytelling resources on the web and in print. “There are so many resources out there, and they’re growing by the day,” , says Andrea Robertson. “I tend to use a lot of resources online, like the D3 library of visualizations.” Robertson also recommends Stephanie Evergreen’s Evergreen Data blog, and she notes that there’s a lot of data storytelling done in the nonprofit world.
“One piece of advice I’d give is read, go to websites, go to blogs that talk about telling stories with data,” says Habiger. Habiger recommends Nathan Yau’s Flowing Data, and also says that companies like Tableau provide great data storytelling resources. Twitter’s also a resource Habiger recommends, saying that “following R or Python developers, or people who make visualization packages, can give you good information.” Keeping up with developers’ Twitter feeds will point you towards the many people working in the space.
Habiger also suggests going beyond the written word. “I don’t think there’s any substitute for statistics 1 or a lot of the basic techniques and skills that come along with analyzing data.” He cites as key basic skills “understanding how to interpret descriptive statistics and [doing] simple tables.”
More About Data Storytelling?
Have you used data storytelling in your business? Are there any data storytelling techniques you’ve used to get your point across? Let me know in the comments below!
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