A Meaningful Approach to Data Storytelling

By some estimates, 2.5 exabytes of data is generated every day – or about 7,500 times the entire content of the Library of Congress. Not only is this amount unfathomably large, it’s also growing exponentially, with scientists estimating that data is being consumed at a compounding annual growth rate of 23%. While this increase of data offers limitless possibilities, it does not come without its challenges: how can we make data meaningful by interpreting it into reliable, credible and, above all else, actionable insights?

Advances in artificial intelligence have enabled the automation of insights from large volumes of data, but extracting the greatest value of data requires harnessing a much older set of skills: storytelling. While the story that each set of data tells will be unique, adhering to the following overarching principles will allow you to identify and convey the most compelling narrative that your data provides:

1. Define your audience: Before you begin to craft your story, it’s important to identify the audience you will be communicating with and understand their level of familiarity with the subject. This step is essential to inform the terminology you will use to create a story that is understandable and at the correct altitude for your target audience.
2. State your purpose: There is fierce competition for attention in today’s information-rich world and engaging your audience hinges upon hooking them with a clear purpose. Start your narrative by sharing the actionable insight from the data, and then dive deeper into the support for this directive.
3. Have a clear story structure: Just as in other forms of persuasive writing, achieving impact requires a clear narrative that follows a logical structure:

• Introduction: Establish the business and industry context in a thought-provoking and intriguing way that sparks curiosity. Share the actionable purpose that is the thesis of your narrative.
• Back it up with numbers: This is where we present the relevant and significant data. This quantitative content can be in the form of graphs, tables or any visual representation that is most easily digestible by your target audience. This is the heart of your story and the place to prove your thesis.
• Conclusion and call to action: Close the story in a concise powerful way. What is the one thing your audience should understand and do after your story has concluded?

4. Make it engaging: There can be a misconception that data is boring. It’s your job to find the story that elevates numbers into a narrative that hooks your audience. This story must be compelling both visually and audibly, immersing the audience whether presented as an elevator speech or a takeaway resource. Consider the following to engage your reader or listener in your story:

• How can you use automation to generate immediate insights in real-time?
• How can you make data interactive, allowing the audience to explore and build their own stories?
• How can you personalize and adapt your story to the interests of individual users?
• How can you integrate AI and ML to identify patterns and trends?
• How can you keep your story assertive and concise, gripping your audience effectively and efficiently?

When data is shared in a narrative it’s not only more compelling – it’s more meaningful. These stories bring data to life, helping organizations to better understand and engage with their audiences.

- Mitzhajalla Ortega – CSA by Havas México.

Are you ready to implement data storytelling? Contact a member of the CSA team to learn how we can make your data meaningful.