Data-Driven Storytelling: Our 7 Best Tips
07/01/2019 by Jaime D’Agord Data Communication
Once your data analysis is complete, the next step is reporting the findings. In recent years, more analysts have been using data-driven storytelling to bring their data to life and influence their audience. When crafting a data story, it is easy to get lost in the details.
Here are the best tips for creating a compelling data story with success. Use these tips from our Think Like a Data Storyteller workshop or check out this sharky data story to improve your data stories.
Our brains want stories, not statistics. Researchers asked students to present a one-minute persuasive pitch to their class members. Each talk included an average of 2.5 statistics.
Only one of those pitches included a story.
Then the researchers asked the students to write down every idea they remembered. Only 5% of the students remembered a statistic; 63% of the students recalled the story. Think about that – the story was what the listeners retained.
Researchers think it is because stories engage our emotions. They make a more significant impression in our brain; thus, we recall the stories easier. We interpret the data better when it is presented as a story.
When telling a data-driven story, try to limit statistics to the vital few. Any statistics you use should be stunning and contribute to the narrative. Consider the ones that will have the most impact. It may be a single statistic that moves your audience.
Not all audiences are created equal, and not all have the same goals. A salesperson would see the business differently than the customer support manager. While both have a common purpose for serving the customer, each would seek a different path to success.
Data analysts may target a broad audience by creating a single set of slides that covers all the bases. It is easy to do when working with internal data and a busy schedule. When this happens, the experts get bored, while the general audience gets confused. In both cases, the audience misses the point, and no one knows what you expect them to do.
You must interpret the data for them.
When preparing your data story, obsess about the audience. Think about who is in the audience, what they know about the topic, and what concerns they have. Your ability to communicate data that addresses their questions and explains what actions should follow is key. Action is the result you want.
For a data story to move an audience to action, the idea must be simple. Countless times, data-driven storytellers present many messages, which ends in a convoluted presentation. The storyteller tries to answer every possible question instead of focusing the discussion on a single point. The audience becomes confused and even discouraged about the takeaway.
In 1854, Dr. John Snow told a data story with a simple message, “We can stop the cholera epidemic by turning off the contaminated Broad Street water pump.” Not only is this a simple message, but it is also an actionable message. Government officials knew what to do and why.
He had lots of data that he needed to communicate. But he kept the message simple.
Keep your message simple and focused. Think to yourself, “What is the one thing I want the audience to do differently after viewing my data story?” Craft your message around that element.
Storytellers allow their biases to creep in. Our predisposition about our message may tempt us to cherry-pick the data to get the result we want. Take for example The Muddled Link Between Booze and Cancer article where the r says previous studies suggesting alcohol was healthy showed selection bias.
The original data combined healthy drinkers with sick quitters. The author describes the group as “some of the groups of non-drinkers that were compared to moderate drinkers were groups of former alcoholics or people who were too sick to continue drinking, so they were generally sicker than the healthier moderate drinkers.” The result was that the researchers and data produced the wrong conclusion.
It’s better to suffer through the criticism of a trusted colleague than present a failed data story.
When crafting a data story, ensure that you are using proper statistical techniques. Have others review your findings and be ready to defend why you omitted or included data.
People want to know about other people. If you consider the extraordinary stories, all are about how someone dealt with adversity.
Tony Soprano fought his inner demons and insecurities. Katniss Everdeen used sheer determination to triumph in The Hunger Games.
You can think of other characters who have overcome difficulties. We are drawn into their battles.
We like to watch their transformation.
Stories help us understand how life changes and why it changes. These stories serve to teach the listener how to face tough decisions and the best actions to take.
While your data story may lack the drama of a mob boss, you should still seek ways to connect with your audience. Rarely are people moved by statistics.
Most people make an emotional decision and later rationalize it with facts. It would be best if you used this emotional connection to establish empathy in your audience. To build this empathy, think how the data involves a human. Good storytelling is about people, not statistics.
When data has an unexpected result, it’s exciting for the audience. Freakonomics is a popular podcast hosted by well-known data journalists Steven Levitt and Steven Dubner. These journalists do an excellent job finding unanticipated answers in data. [And their headlines easily grab attention on social media!]
In one study, they presented a challenging idea. Do low-level drug dealers make less money than if they worked at a fast-food restaurant?
Most people believe that dealing drugs leads to a fancy lifestyle.
This fact is an unexpected reveal. In each podcast, they tell a story with a compelling narrative.
If your data doesn’t even produce an “AHA!” from you, you may be chasing the wrong narrative.
If you are not well-versed in how to present data, your message may get lost. The improper data visualization technique will muddle your message. You might liken it to talking to someone speaking two languages at once. You will only understand the one you know.
Before you create a data story, make sure you understand how to interpret the variables. You must study data visualization techniques. If your skillset is weak, consider working with a professional. A data visualization specialist can guide you toward a successful data presentation.
Consider the stories that the late Professor Hans Rosling relates in his TED Talks. Even in this data story called The Joy of Stats, he reduces 120 numbers into a simple message.
Most consider a bubble chart as challenging to understand, but Rosling makes it simple. You can deliver a powerful story too — with the right visualization resources.
Storytelling is a powerful way to present data when used correctly. By keeping the message focused, considering the audience, and using a convincing narrative, data storytellers move audiences toward their conclusions.
You can do this.
Use the Email Signup form (on the top right) to get the Zencos Insight updates. We talk about topics of interest to data professionals. You can unsubscribe at any time, and we never share your email address.