From the course: Data Visualization: Storytelling

Data storytelling is essential, except when it isn't

From the course: Data Visualization: Storytelling

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Data storytelling is essential, except when it isn't

- [Lecturer] Your primary job as a human is to be a communicator. Full stop. Many studies have shown that humans spend 70 to 80% of their waking hours communicating. So, regardless of your job, your communicator, first and foremost. Think about it. If a tree falls in a forest, but there's no one there to hear it, does it make it sound? If you do your data analysis and discover wonderful things, but don't tell anyone about it, did it happen? Or as we say these days, pics or it didn't happen, right? And in case you want to argue with that point and say, "Yeah, but I work in a dungeon crunching spreadsheets and hand those to someone else who worries about what to say about it." Yeah, but you probably have to explain what's going on to that other person. Also, there was a survey of about 400 recruiters of college graduates studying business intelligence and analytics that found that the highest ranked of all desired skills was communication. So, if you're looking to be hired, the best thing you can do, literally number one, is to be a good communicator. To be a good communicator, you need to craft a narrative to have the largest impact with the most audiences. Jennifer Aaker is a marketing professor at Stanford who says, "Stories are up to 22 times as memorable as facts alone." She also refers to a study of charity fundraising that used one brochure with a bunch of statistics and another that had stats and a story. Guess which one raised twice as much money? But here I am trying to convince you with just a bunch of stats. How can I craft a story to convince you that stories outweigh statistics alone? What if I told you 21% of children under the age of 18 live below the poverty line in the US? That might have an impact on you, but odds are you won't remember it three days from now. But instead, if I said this, "I remember my best friend Tom would give his teacher an apple every day in grade school, but I never understood how he could afford it because he was poor. Last year, I found out that one in five kids live below the poverty line in the US and that makes me think about Tom and how there were probably 20 Toms in my small school of just 100 kids. I wonder how many of them gave their teachers apples every day." Now, after that, admittedly very simple and not very interesting story, you're more likely to remember that statistic. One of the reasons stories are so powerful is that neutral words like chair activate the language portions of our brains. But when we hear certain other words like coffee, the portion of our brain that processes smells is also activated. And the more different parts of the brain that are activated, the more memorable and emotional and impactful the story is. Statistics are like the neutral words. They trigger the language portion of our brains only. So weaving in statistics with story and including details like the apple Tom brought in for his teacher every day activates more portions of the brain creating more sensory inputs, and therefore, stickier and more impactful content. We feel it quite literally. At least our brains think they feel the sensory inputs when those statistics are weaved into stories. So, use visuals to activate the visual cortex and write copy that weaves a real narrative, including other sensory inputs whenever you can. Now, all that being said, you don't always have to tell stories. There was a great paper that came out of Stanford a few years ago titled "Narrative Visualization, Telling Stories with Data," that talked about author-driven data storytelling versus reader driven data storytelling. As the paper says, "A purely author-driven approach has a strict linear path through the visualization, relies heavily on messaging and includes no interactivity. Whereas a purely reader-driven approach has no prescribed ordering of images, no messaging, and high degree of interactivity." I would argue that purely reader-driven visualizations are not data stories at all. They're dashboards. They're great for when you're sharing data with experts or people who need to explore the data directly. They may not need a narrative. Perhaps it's a tool, not a communications device. So, if this is your case, then perhaps you don't really need data storytelling, but, and this is important, you need to seriously think about if that's realistically your universe. Even A CEO dashboard often needs more storytelling than even the CEO herself would admit. When in doubt, tells stories. As the Stanford paper says, "Data stories appear to be most effective when they have constrained interaction at various checkpoints within a narrative, allowing the user to explore the data without veering too far from the intended narrative." In other words, they're not exploration tools, but rather narrative experiences that provide context and direction, not just a pile of numbers and charts.

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