Data facilitates understanding. Storytelling facilitates emotion. Learn how you can bring these two worlds together to better enlighten and engage your audience.

Roald Dahl's Matilda laughs while reading a book.

In today’s increasingly connected world data is everywhere. Developments in both consumer and business technology mean that huge sums of data are being collected every day. In fact, in a report entitled “Data Age 2025,” the International Data Corporation predicts that by 2025 the average connected individual will interact with a connected device every 18 seconds. That’s almost 4,800 times a day!

This proliferation of data has provided marketers with an incredible opportunity. More specifically, the opportunity to use information such as demographic, engagement and purchase information to develop, implement, and report on more informed marketing strategies. What’s more, they can incorporate this data into their external messaging to better communicate their brand and offering to potential and current customers.

However, with this opportunity also comes a challenge: how to successfully leverage all this data. This is a challenge recognized by Google’s Chief Economist, Dr Hal R. Varian. As he explains,“the ability to take data – to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it – that’s going to be a hugely important skill in the next decades.”

Given this challenge, how can marketers ensure that they are getting the most out of the data available to them?

The Main Character: Data Storytelling

Enter data storytelling. More than just data visualization, data storytelling is a structured approach to communicating data insights that relies on a compelling narrative to provide meaning and context to data.

It works by facilitating both understanding and an emotional response. More specifically, the data creates understanding, while the addition of narrative generates an emotional response, and consequently, a personal connection.

Examples of data storytelling include Airbnb’s 2015 “Happy New Year” video and Spotify’s “How Students Listen 2017.” Both are great examples of how companies and brands can utilize narrative as a way to provide context to the wealth of data at their fingertips.

Why Marketers Should Have Literary Aspirations

Roald Dahl's Matilda looks at the camera while saying Oh Yes, I love to Read

As demonstrated by the above examples, the combination of data and narrative can certainly make for an entertaining experience for viewers/readers. However, the benefits of data storytelling go far beyond this. The use of narrative has been shown to be more memorable, persuasive, and engaging than data on its own.

What’s more, narrative has a beneficial effect on decision making. This is due to the fact that decision making is not a purely rational process. If it was, I’d probably be quite a bit richer, fitter and more knowledgeable… Instead, emotion also has a role to play. In fact, studies have shown that emotion is actually integral to decision making. Not only does it help us evaluate alternatives, but it also helps us arrive at timely decisions.

Therefore, narrative provides marketers with a powerful tool. Whether they are presenting data for external (i.e brand awareness) or internal (i.e reporting) purposes, narrative can be used to elicit powerful emotional responses, and consequently influence decision making.

4 Components of a Data Story Worth Telling

When crafting a data story, marketers need to consider four key aspects: data, narrative, visualizations, and audience.

First, data. Because it creates understanding and lends credibility, it is critical that the data used in a data story is unbiased and comes from a trustworthy source. It should not be manipulated or misrepresented in a way that can lead to misintepretation.

Second, narrative. The first question marketers should ask themselves is “Is there a story to tell?” Sometimes the data does not support a narrative; in these cases there is no point in trying to make it into something it is not. If the data does support a narrative, marketers need to ask “Is this story relevant and engaging and does it provide value to my audience?”

Third, visualizations. In order to ensure that data is not misrepresented or misinterpreted and that it is easily comprehended by the audience, extra attention should be paid to the way in which data is visualized. The blog Storytelling with Data is a great resource for those looking for tips on how to generate clear and concise visualizations that support a narrative.

Lastly, audience. When creating a data story, marketers need to consider who their audience is and the depth of information they already have. For example, a data story detailing the performance of a marketing campaign should look very different depending on whether it is presented to the C-Suite or to the Director of Marketing.

The Villain: Data Complexity

Ms. Trunchbull spins a child around by the braids while Matilda looks on in shock.

Every hero has it’s villain. In the case of data storytelling a common antagonist is data complexity. For if the increased availability of data provides marketers with an incredible opportunity, it also provides them with a significant challenge: how to surface the data that matters most?

In order to overcome this challenge, marketers need to take a focused approach to the process of creating a data story. Starting with a clear purpose and specific questions in mind will make marketers much more effective in uncovering insights and underlying narratives.

And they lived happily ever after . . .

Ms Honey proclaims her love for Matilda.

Given the increase in data that is being collected every day and the numerous benefits of combining narrative and data, today’s marketers should look to data storytelling as their trusty steed. With data storytelling by their side they can ride into the sunset, reaping not only the benefits of increased memorability, persuasiveness, and engagement, but also improved decision making.

Let’s tell the world your story.