How to tell a good data story
You’ve probably heard your fair share of stories over the years. While some of them are unforgettable, others seem endless—and not in a good way. That’s because all stories aren’t created equal.
While having relevant and interesting information to share is important, it’s far from the only factor that determines whether a story is “good” or “bad.” Other aspects of good stories include having a beginning, middle, and end (i.e., they’re not merely anecdotal); they have meaning; they’re thoughtfully structured and have a good ending.
Good data storytelling is similar. Wondering how to tell a story with data? Here are a few steps you can take:
1. Find the stories within your data
Two of Michelangelo's most famous quotes are, “I saw the angel in the marble and carved until I set him free,” and “Every block of stone has a statue inside it, and it is the task of the sculpture to discover it.”
While Michelangelo was talking about his artistic process, he could also have been talking about uncovering critical insights for data stories. With the right metrics and analytics, the stories worth telling already exist within your data. It’s your job to find them.
The following questions can help you uncover a narrative within your data:
Who is your target audience?
- What are their wants and needs?
- What information are they looking for?
- Which data points speak to these questions?
What are your goals?
- What information do you want to convey to your target audience?
- What actions/results are you hoping to drive?
- Which data points relate to these goals?
What is the data telling you?
- What interesting correlations or casual links have emerged?
- What do these connections mean for your target audience and organizational goals?
Sometimes, a compelling story will emerge from the data because of its obvious potential. In other cases, you must dig deeper into meaningful relationships, patterns, and themes.
2. Create and structure your narrative
How you structure the narrative is instrumental to making your data meaningful. After you’ve honed in on the story you want to tell and the data sets you’ll use to tell it, it’s time to work on your narrative.
Traditional story plot lines contain exposition, rising action, climax, falling action, and resolution. Compelling data stories also have “plots” crafted to support a satisfying audience journey. Typical elements include an introduction with a hook, background and context, a conflict or pain point, and resolution.
In other words, it’s not enough to provide useful data. You must also strategically organize that data in a way that keeps the audience engaged and the story moving forward to an actionable conclusion.
3. Leverage visuals
Earlier, we touched on the difference between data storytelling and data visualization. When integrated into data storytelling, visuals like line charts, bar charts, tables, maps, infographics, and animations can amplify your message's impact.