Data Storytelling: How to Effectively Tell a Story with Data
When you hear the term “data analysis,” what comes to mind? You might think of going through spreadsheets, using algorithms, and doing math—all the “hard skills” of data analysis. However, hard skills are not enough without their soft skill counterparts. It's not enough to just analyze data; you need to communicate the story it tells clearly and compellingly—a skill known as data storytelling.
According to the Bureau of Labor Statistics, the need for research analysts is predicted to increase by 25 percent from 2020 to 2030, which is much faster than the average for all industries. Many companies are now listing data storytelling as a necessary skill in analyst job descriptions, while others are hiring data storytellers to enhance their existing analytics teams’ capabilities. Having the ability to both analyze data and convey its insights can make you a more attractive candidate.
Here’s a primer on the key components of data storytelling, why storytelling is an impactful communication tool, and how to craft a compelling narrative of your own.
What Is Data Storytelling?
Data storytelling is the ability to effectively communicate insights from a dataset using narratives and visualizations. It can be used to put data insights into context for and inspire action from your audience.
There are three key components to data storytelling:
Data: Thorough analysis of accurate, complete data serves as the foundation of your data story. Analyzing data using descriptive, diagnostic, predictive, and prescriptive analysis can enable you to understand its full picture.
Narrative: A verbal or written narrative, also called a storyline, is used to communicate insights gleaned from data, the context surrounding it, and actions you recommend and aim to inspire in your audience.
Visualizations: Visual representations of your data and narrative can be useful for communicating its story clearly and memorably. These can be charts, graphs, diagrams, pictures, or videos.
Data storytelling can be used internally (for instance, to communicate the need for product improvements based on user data) or externally (for instance, to create a compelling case for buying your product to potential customers).
The Psychological Power of Storytelling
Humans have told stories since the Cro-Magnon era to communicate with others for survival and record accounts of daily life. While storytelling methods have come a long way since the days of cave paintings, its psychological power holds true tens of thousands of years later.
The brain’s preference for stories over pure data stems from the fact that it takes in so much information every day and needs to determine what’s important to process and remember and what can be discarded.
When someone hears a story, multiple parts of the brain are engaged, including:
Wernicke’s area, which controls language comprehension
The amygdala, which processes emotional response
Mirror neurons, which play a role in empathizing with others
When multiple areas of the brain are engaged, the hippocampus—which stores short-term memories—is more likely to convert the experience of hearing a story into a long-term memory.
Rather than presenting your team with a spreadsheet of data and rattling off numbers, consider how you can engage multiple parts of their brains. Using data storytelling, you can evoke an emotional response on a neural level that can help your points be remembered and acted upon.
How to Craft a Compelling Data Narrative
Data storytelling uses the same narrative elements as any story you’ve read or heard before: characters, setting, conflict, and resolution.
To help illustrate this, imagine you’re a data analyst and just discovered your company’s recent decline in sales has been driven by customers of all genders between the ages of 14 and 23. You find that the drop was caused by a viral social media post highlighting your company’s negative impact on the environment, and craft a narrative using the four key story elements:
Characters: The players and stakeholders include customers between the ages of 14 and 23, environmentally conscious consumers, and your internal team. This doesn’t need to be part of your presentation, but you should define the key players for yourself beforehand.
Setting: Set the scene by explaining there’s been a recent drop in sales driven by customers of all genders ages 14 to 23. Use a data visualization to show the decline across audience types and highlight the largest drop in young users.
Conflict: Describe the root issue: A viral social media post highlighted your company’s negative impact on the environment and caused tens of thousands of young customers to stop using your product. Incorporate research , about how consumers are more environmentally conscious than ever and how sustainably-marketed products can potentially drive more revenue than their unsustainable counterparts. Remind the team of your company’s current unsustainable manufacturing practices to clarify why customers stopped purchasing your product. Use visualizations here, too.
Resolution: Propose your solution. Based on this data, you present a long-term goal to pivot to sustainable manufacturing practices. You also center marketing and public relations efforts on making this pivot visible across all audience segments. Use visualizations that show the investment required for sustainable manufacturing practices can pay off in the form of earning customers from the growing environmentally conscious market segment.
If there isn’t a conflict in your data story—for instance, if the data showed your current marketing campaign was driving traffic and exceeding your goal—you can skip that element and go straight to recommending that the current course of action be maintained.
Whatever story the data tells, you can communicate it effectively by formatting your narrative with these elements and walking your audience through each piece with the help of visualizations.