What is data storytelling and how does it work (examples)

This article aims to demystify the concept of data storytelling, explaining why it is more than just charts and graphs, because understanding data is essential, but making it recognizable and actionable is often a bigger challenge .

What is a Data Storytelling?

Unpacking the term data storytelling reveals it as an art form that combines quantitative information with narrative context to engage audiences in a compelling way. It’s more than just numbers and charts; it includes a rich mix of data analytics, domain knowledge and effective communication.

Understand data storytelling and visualization

While data visualizations serve as valuable tools in the storytelling process, they should not be confused with the story itself. These visual aids reinforce the narrative, but are not a substitute for the analytical depth and context that completes a data story. Data storytelling synthesizes visual elements with sector-specific insights and expert communication to provide a holistic understanding of the subject matter.

Consider the example of tracking sales fluctuations for a specific product. While data visualizations can clearly show upward or downward trends, a well-crafted data story will dig deeper. It can illuminate how a recent marketing blitz boosted sales, or how supply chain issues acted as a bottleneck, limiting product availability. This broader narrative turns a mere data point into actionable intelligence, answering not only the ‘what’, but also the ‘why’ and ‘how’, making it invaluable for decision-making.

How does data storytelling work?

Data storytelling is a trifecta of key components: raw data, visual representations and the overarching narrative:

Data: Let’s say your analysis shows that a particular type of renewable energy source, such as solar power, is generated most efficiently in coastal areas. Another finding could be that peak production coincides with the tourism season. Visualizations: After the data is collected, visual tools come into focus. These could be heat maps showing solar hotspots or seasonal trend lines plotting energy production against tourist numbers. This visualization acts as a bridge between complex data and audience understanding. Narrative: The narrative is the soul of your data story. This is where you introduce the issue—for example, the importance of efficiently locating renewable energy sources—and then outline your data-backed findings. The story should culminate in a specific call to action, perhaps prompting local governments to consider these factors in their renewable energy planning.

Each of these elements is an important chapter in the larger book that is your data story, working in harmony to create a resonant, impactful message for your audience.

How to do data storytelling?

Creating a compelling data story goes beyond just throwing some charts and graphs into a presentation. It is a calculated process that requires a synthesis of raw data, analytical insight and narrative flair. So how does one begin this journey to create a narrative that is not only compelling, but also informative and actionable?

Data Storytelling Techniques Step by Step

Data storytelling is not a skill developed overnight. Like any other form of storytelling, it involves multiple components and steps that contribute to the final masterpiece. Here’s a more detailed look at some steps to creating a compelling data story:

Step 1: Know your audience inside out

First, you need to be intimately familiar with your target audience. Why? Because effective data storytelling is not one-size-fits-all. What are the pain points or challenges your audience faces? Why would your findings resonate with them? By addressing these questions, you can pinpoint the aspects of your data that will really engage your listeners or readers.

Step 2: Weave an intriguing narrative

The narrative is the backbone of your data storytelling business. You don’t just spit out numbers, but build a plot that leads your audience to a well-defined outcome. So how to work on this?

Start by establishing the background: Explain why you decided to dive into this particular data set and what pressing issue or curiosity you aimed to solve.

Transition to your discoveries: What did your deep dive reveal? Highlight the key insights that have the most direct impact on the problem or question you started with. It’s about sifting through your data haystack to reveal the ‘golden needles’.

Conclude with action steps: Armed with these revelations, what should your audience do next? Provide clear, data-backed recommendations that lead to measurable results.

Step 3: Refine your data visualizations

Chances are you’ve already developed some form of data visualization during your analysis. Now is the time to refine them. Are they successfully highlighting the most critical data points? If so, focus on arranging them in an order that enhances your narrative flow. If not, go back to the drawing board and conjure up new visuals that can do your ‘golden needles’ justice.

By following these steps, you not only make your data understandable, but also infuse it with meaning and actionable insights, making your data storytelling efforts not only digestible, but indispensable.

Step 4: Lay out a familiar story arc

To make your data story resonate, consider using a storytelling structure that your audience is already comfortable with. It includes an introduction to set the stage, a build-up that incrementally raises the stakes or complexities, a climax that delivers the crucial data insight, followed by a resolution that ties up loose ends. Using a familiar narrative framework helps your audience effortlessly navigate through the data points and fully grasp the meaning and implications of what the data reveals.

Step 5: Take your story public

Once you have a compelling narrative backed by solid data and visuals, it’s time to get it out into the world. A presentation deck is often the medium to share your data story. This allows you to summarize every aspect of your narrative, from initial context to final conclusions, in a way that is both visually appealing and easily digestible.

Step 6: Refine for accuracy and clarity

The last step in data storytelling is often the most overlooked: editing for brevity and clarity. Your data story should be compelling and straightforward. This means cutting out any extraneous information or decorative language that doesn’t serve the central story. Blaise Pascal once said, “If I had more time, I would have written a shorter letter.” This sentiment also applies to data stories; Refining your narrative down to its most essential elements will ensure your audience stays engaged and walks away with the most important takeaways.

Why is data storytelling important?

The importance of data storytelling lies in its ability to contextualize and simplify complex data, making it accessible and understandable to a wide audience. Unlike dry statistics or raw data, storytelling weaves these elements into a narrative that illustrates not only what the data is, but also why it matters. This creates a deeper emotional connection and engagement, which brings out the implications of the data in a more impactful way.

Data storytelling accommodates multiple learning preferences, from auditory to visual to kinesthetic, enhancing its reach and effectiveness. Whether through a narrated presentation for those who learn best by listening, or through charts and graphs for visual learners, a well-crafted data story can adapt its medium to best engage its audience.

By using a mix of these elements, data storytelling ensures that its message resonates across a diverse set of listeners or viewers, making the data not only informative, but also compelling and memorable.

5 data storytelling examples you should check out

Let’s explore a curated selection of some of the best examples of data storytelling.

Chris Williams: Grill Universe

The eternal debate surrounding the optimum type of fried potato is explored here in a humorous way. The project uses visuals to demonstrate how different ratios of fried to unbaked surfaces significantly affect the gastronomic experience.

Check it out!

Periscope: American gun deaths

The focus of this visualization is the “stolen years” attributable to gun deaths. It excels at evoking an emotional response, masterfully unfolding the data in stages to deeply engage the viewer.

Check it out!

Krisztina Szucs: Animated sports results

Rather than traditional narratives, these are bubbly, animated data vignettes that depict the dynamics of various sports competitions. Szucs uses a variety of visualization styles to suit different scoring methods, while capturing the essence and excitement of each event better than any conventional box score can.

Check it out!

Kayla Brewer: Cicadas, a data story

This data story offers an educational adventure about the appearance of Cicada ‘Brood X’, which is popularly described as “little flybois make big noise.” The project shows how a public dataset can become a compelling data exploration using the Juicebox platform.

Check it out!

Jonathan Harris: We feel good

This early pioneer in data storytelling is an interactive platform that scans the web at 10-minute intervals to collect expressions of human feelings from blogs. It then presents the data in various visually striking formats. It has been a source of inspiration for many in the data visualization field.

Check it out!

Databases are the unsung heroes of AI

Why it matters

Data storytelling is far from a nice-to-have skill; it is a necessity in today’s data-driven world. It’s about making complex data easy to understand, relevant and actionable. As we’ve shown, the impact of a well-crafted data story goes beyond mere understanding—it influences decisions. The examples provided highlight the wide range of applications and the potential to make your data not only understandable, but also impactful.