Show, Don’t Tell – Exploring the Power of Data-Driven Storytelling

Discover how to transform raw data into compelling stories with tools like Vizzu.

Show, Don’t Tell – Exploring the Power of Data-Driven Storytelling

Hollywood is the home of modern storytelling. So, it makes sense to start with a little story about the Oscars…

Did you know that the movies winning big at the Oscars aren't always the ones audiences love most?

Okay, that mini-story doesn’t really tell you very much. You don’t get the “big picture”. Let’s try breaking it down a little more:

  • Most years, the Oscar-winning films aren't the top box office hits.
  • In 2023, "Everything Everywhere All at Once" took home a bunch of Oscars. Impressive, right? But it made way less money than "Avatar: The Way of Water". In fact, over 30 other movies that year made more money.
  • This isn't just a one-time thing. In the last 30 years, only two highest-grossing movies actually won the Best Picture Oscar ("LOTR: The Return of the King" and "Titanic").
  • It seems if you want an Oscar, being a box office smash shouldn’t be your goal.

That’s better. But there's an even more engaging way to tell the story. After all, as any storyteller knows, the key is to show, not just tell

That’s where interactive data visualizations come in.

What do we mean by that? 

Dynamic data displays can help tell the story, like this one:

Below is a video telling the same story about the Oscar winners, but using a series of interactive data visualizations instead.

We think you’ll agree that animated data visualizations are a much more effective and engaging way to communicate the story behind the data, rather than presenting it in a static way. 

Now you know what a data-driven story looks like, you’re probably wondering:

  • What makes for good data-driven storytelling?
  • How do I create one?
  • Is it difficult and do I need specialist skills?

Well, the good news is – no-code animated data visualization tools like Vizzu make it easier than ever to create beautiful-looking data stories.
And, as for the other questions, keep on reading to find out!

What is data-driven storytelling?

As humans, we’re programmed to think visually from an early age. Young children are given picture books to help them understand story elements before they learn to read.

The preference for visual stimuli continues into adulthood, shaping how we navigate the world. From road signs that use clear icons to infographics that simplify complex news, visuals are essential for quick and efficient communication.

For that reason, when you’re trying to communicate data findings, it makes sense to present it visually.

However, a static graph or chart isn’t enough on its own to tell a complete story. That’s where data-driven storytelling comes in.

Using interactive data visualizations, you turn raw data into a flowing story that sets the scene, takes people on a journey, and presents a conclusion or allows people to interpret the data themselves.

In essence, good data-driven storytelling includes the following key elements:

  • Hook: Sets the scene and generates curiosity. This can be a statement, question, a surprising statistic, or a graph or chart that raises questions in the viewer’s mind.
  • Data Visualizations: An interactive data visualization, such as a series of dynamic graphs reveals deeper insights into the opening statement.
  • The “A-Ha!” Moment: The data reveals a key insight.
  • Resolution: The audience is left to think about the revelation or a conclusion is drawn.

Let’s see how this plays out in the Oscars example above.

  • Hook:  The intro text for the video reads: “Does leading the box office wave guarantee an Oscar nod?”. This opens up a curiosity loop.
  • Data Visualizations: A series of charts shows the Oscar winner data, revealing that big grossing movies rarely win a lot of Oscars.
  • The “A-Ha!” Moment: The “A-ha” moment arrives when the video shows that only two Oscar winning movies in the last 30 years were highest-grossers. 
  • Resolution: After some more data is revealed, a conclusion is reached - “If you want a major Oscar, don’t go full blockbuster!”

Now we understand what a data-driven story looks like and why they work so well, let’s dive into how to create one.

How to tell a data story

There are six key steps to creating a good data-driven story.

Step 1: Gather and Organize Your Data

If you’re dealing with a large amount of data, you might suffer from information overload. That’s why you need to zero in on the data you’re interested in.

For example, let’s say you work for a company that wants to tell a data-driven story about customer service. You might have to gather quite a lot of data – customer feedback surveys, call center logs, and online reviews. You’ll need to find a way to sift through this large dataset to focus on key areas, such as common complaints or suggestions for improvement. Once your data is organized, you can focus on any areas that reveal insights.

Many organizations use data analysis tools, such as Microsoft Power BI or Tableau to streamline this stage. However, these tools are expensive and difficult to learn. Fortunately, data visualization tools like Vizzu offer more accessible data analysis for smaller businesses or individuals, as well as features to turn the analysis into engaging interactive charts and graphs.

Step 2: Find the Narrative

Next, you’ll look for trends, patterns, and insights within the data that could form a compelling story. 

For instance, sticking with the customer service example, you might uncover a recurring issue that negatively affects customer satisfaction, e.g. long wait times. Maybe you also find data that shows a sales dip since wait times have grown longer. Telling this story could drive positive strategic changes in the company.

Step 3: Draft the Narrative

Once you have uncovered some data insights, you need to write a script that connects your visuals into a seamless story, one with a beginning, middle, and end.

In our example scenario, this could look something like this:

  • Hook: Set the scene with your main findings, such as the issue of long wait times negatively impacting customer satisfaction and sales. 
  • Data Visualizations: Interactive data visualizations, exploring how and why wait times have increased
  • The “A-Ha!” Moment: Correlating these trends with dips in sales and customer feedback.
  • Resolution: Discuss potential solutions or actions taken by the company to address these issues.

Step 4: Add Interactive Elements 

Now you’ve written the story and have all the data ready, you can use tools to create the interactive data visualizations. Vizzu is a good example of an easy-to-use tool that lets you create animated charts and graphs that tell the story in a smooth, flowing way. It helps to bring your data storytelling skills to life.

In the customer service example, you could use Vizzu to create an animated graph that starts with a graph of customer satisfaction ratings over time. Then, it could zoom into the section that shows a dip. This could then morph into another graph showing longer wait times at the same time. This way, you’re showing the audience insights from the data, rather than telling them.

Step 5: Test and Refine

Once you have the first draft of your data story ready, it’s time to get a fresh pair of eyes on it. Share your story with colleagues or a limited test audience and ask for honest feedback. Based on the comments, you can polish your visuals and refine your story, aiming for clarity and accuracy.

Step 6: Share Your Story 

This is where your hard work pays off. Publish your data-driven story where your audience can see it— whether that’s your company blog, in a report or presentation, or through social media channels.
The goal is to share the insights you've discovered, spark conversations, and perhaps inspire action based on the compelling data storytelling. This is especially important in business. By the way, if you find this content interesting, you might also want to check our article about the importance of storytelling in business.

Data-driven storytelling examples 

Example 1 – Super Bowl Ads: From $40k to $7 million per 30 seconds

The data-driven story starts with a hook statement – “Over 18 years, ad price rose to $500k”. Then, a series of animated interactive data visualizations show how ad prices have grown steadily over the years, correlating it with the growing number of television viewers. Finally, the video concludes with “The inflation-adjusted cost to reach one viewer increased fourfold”.
This tells a neat data story with a clear beginning, middle and end, giving the viewer plenty to think about along the way.

Example 2 – How did COVID-19 affect growth forecasts?

On a more serious note, this video tells the data story of how COVID-19 affected economic growth across the globe. It starts by setting the scene with data visualizations of 2019 growth forecasts compared with 2020. 

The animation then shows a map with different size dots to compare the amount of GDP loss in US dollars, first by country, then by continent.

The final section concludes the story with some stark statistics, telling us that the total lost GDP worldwide was $6,378 billion, equivalent to more than $800 per person on Earth.

Example 3 –How much do cocoa bean farmers get from a $1 chocolate bar?

This hypnotizing interactive data visualization (check other interactive data visualization examples) cleverly breaks down all the costs that go into producing a $1 chocolate bar. It tells the story through sections of a pie chart, without any additional narration. The story concludes with a definitive figure to resolve the opening question.

Create compelling data-driven stories the easy way with Vizzu 

Vizzu is an easy-to-use, no-code tool for visual data-driven storytelling. You simply plug in your data and the built-in data visualization generator will suggest the best charts. You can select from a wide range of animation and effects to craft the narrative-driven impact you want.

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