Data Storytelling

What is data storytelling

Data storytelling forms a compelling narrative by putting data in context to show the challenges, insights and solutions of a specific business problem. It normally highlights a series of changes or trends over time through linked visualizations that combine to tell a story. Stories engage or inspire, and use data to inform actions we could take. Which presentation would inspire you to pull out your wallet? “Hunger is a serious problem that affects Africa’s children” or “One in six African children will go to sleep hungry tonight, including Michael.” 

Telling your data’s story is an important part of your data analysis that makes data actionable. It’s probably the most important aspect to convince your audience. Business narratives are usually constructed to inspire people to buy a product, join a group, or make a similar decision. When you present your data using a narrative that tells the story behind it, you’re providing context and giving the story a greater impact on internal and external customers. 

The difference between raw data and stories, the tipping point that will get your users or listeners to take action, is the emotional engagement that is inspired by a compelling narrative. After a typical presentation, 5% of listeners remember the statistics and the concepts they described, but 63% will remember stories used to illustrate key concepts. 

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Why it’s essential to tell stories with data

Using data provides a more compelling case for a business change that offsets an emotional argument, so it’s important to use analytics. However, telling stories and presenting data in narrative terms can amplify the impact of the data, by creating empathy and encouraging people to form emotional attachments to your story. This is the magic of Ted Talks.

Additionally, data storytelling brings understanding to different levels of the company — not just the data team. A good story will bring out the insights behind your data analysis without anyone needing to manipulate a spreadsheet. And with a BI platform, you can make your data even more accessible. The value of a modern BI platform is that you can create visualizations that allow users to easily access data insights and share them with other important stakeholders.

How to tell the best stories

Dashboards and visualizations are integral parts of data storytelling, but they’re not the end of the story. A story should include a solid narrative and a context to successfully create your story.  In brainstorming for a good story, ensure you consider  the “why” behind your “what.”  According to actor Kevin Spacey, in his presentation to the Content Marketing World Conference, there are three key elements to creating a compelling story:s conflict, authenticity, and audience. 

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Conflict creates tension, which is what keeps the audience engaged. Conflict is the struggle between opposing forces in a story, and it’s what drives the plot forward. It’s when our stories go against the settled order of things to achieve something unexpected. This might be expressed differently in a business context, but it serves the same purpose. 

Authenticity creates power and allows your stories to be real. Audiences are sensitive to anything that smacks of click-bait or fakery. Be sure that your stories are substantive and demonstrate passion. You don’t want to come across as keyword stuffing to boost your SEO ranking. 

The last key element to creating a great story is understanding your audience. Keep them in mind to develop loyalty and increase engagement. Audiences crave good stories. If you deliver a compelling story, they will want to talk about it to co-workers and friends and share it on social media. 

Data Storytelling Examples

At the end of 2019, music app Spotify celebrated its customer relationships by creating a unique presentation for each user, summarizing the past year in music listening. Spotify used data analytics to craft a personalized account, and emphasized its data with visualizations. This data story celebrated the customer relationship and cemented its connections with users in the face of a crowded market of streaming apps. 

The COVID-19 pandemic is a particularly data-driven experience that has brought data analytics and data visualizations to more users than ever before. News media outlets, government bodies, and even American high-school students have taken raw data about the rate of current infections, recovery or death rates, and the number of tests, and used BI tools like Sisense to analyze the data and tell stories.

We can see how these numbers matter when we look at recovery rates in communities by zip code, income level, or hospital density. Different stories can be told using data in this extraordinary time, concerning pollution levels, shopping habits, or leisure-time activities.

In conclusion

Data storytelling can be used in any industry and by employees in any department as a way to increase the impact of their data. Remember: when crafting your narrative, it’s important to be honest and authentic, consider your audience, and include conflict to inject tension into your story and increase the drama. People remember stories, not data. Give them insights in story form to turn your statistics and information into a powerful communication tool. 

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