4 MIN READ
Using storytelling to deliver data-driven information
As companies collect more data, they're continually looking for ways to communicate that information to people in a way that's engaging and informative. It's something that we're not good at because it's hard to do. That's where storytelling comes in. Humans have used storytelling to entertain, but more importantly, to teach and learn. Even today, storytelling is still one of the best ways to communicate with employees and customers alike. So those who can weave a good story with data will be more successful at delivering that information to readers.
We love stories but hate numbers
Everyone can tell a good story, even a good business story. As soon as you ask people to talk about the latest report or quarterly numbers, however, they freeze up. "I hate numbers!" they say. "I'll just put the numbers up on a slide, and everyone can figure it out for themselves."
There are even some studies that say we have a love/hate relationship with numbers, but instead of freezing up in the face of business data, why not combine it with storytelling? Storytelling is easy for us, and we like to do it. By combining the two, the numbers become a simple ingredient in our stories, and they're much less intimidating.
5 ways to use data in your stories
Data-driven storytelling is all about revealing the stories hidden within your data and highlighting the story first and the data second. Here are five kinds of stories you can tell with your data.
- Explain or demonstrate trends:
Google Trends is a great example of using data to explain and demonstrate the trends going on around the world. They create visualizations, videos, and images to explain global search trends, as well as explain how they create stories around their data.
Takeaway: Figure out how to leverage your data to answer your audience's most pressing questions. Then point them towards the information that matters most to them.
- Identify the best/worst performance: Marketing teams love to do this by ranking their top performing content. Understanding what content works best and where helps them focus on the channels that provide the most value to the company and eliminate the channels that are underperforming. Customer success teams can use similar rankings to determine where their information gaps are and then fill in those gaps to help customers better. As you analyze the performance of channels, campaigns, projects, etc., you'll uncover more insights by ranking the data you have for your teams.
Takeaway: Leverage ranking lists to identify the best and worst performing channels or area of your business, then optimize resources accordingly.
- Write deeper comparison stories: Many companies use data to compare themselves to their competitors and demonstrate how they're outperforming the market. This data helps them highlight their unique differentiators and position themselves better than their competitors. When comparing data, it's important to show the whole picture to accurately uncover the reasons behind the high (or low) numbers. For example, your competitor's software adoption rates may appear higher than the industry average, but that is due to the fact that they have fewer customers than most of the industry.
Takeaway: Dig deeper into your comparison numbers to illustrate the differences between the two areas you're comparing; they'll be more meaningful to readers.
- Surprise readers with your data findings: Anyone can write a story that confirms their data; how about writing one that surprises readers? Like how the increase in MRR leads to a decrease in employee attrition rates? Or how the new health benefits plan you implemented this year increased customer NPS? You may be surprised at the stories and data you're able to combine when you're looking for the surprise angle.
Takeaway: Intrigue readers by combining unexpected data with stories and make your stories more memorable. Readers will remember it more.
- Explore relationships with multiple datasets: Finally, we come to a little relationship exploration in storytelling. Specifically, exploring the relationship between two sets of data and the story that tells. Use the story to predict outcomes, link behavior to results, or highlight areas for further research.
Takeaway: Stories can be written with more than one dataset, so explore the relationship between two or more datasets to deepen the story's impact. Readers will appreciate the different perspectives the datasets bring to the story.
We're all storytellers at heart, so give your stories more weight and proof by backing them up with the abundance of data you're already collecting. Data-driven storytelling delivers more value to readers and will help drive decision making throughout your organization.
Have you been consciously using data-driven storytelling techniques in your company? Hit the comments and let us know how it's going.