What is the story behind the people supporting Donald Trump as a presidential candidate? Not to pick on Trump, but the question of “Who would vote for this guy?” looms large over his campaign. There’s a story there, one that many journalists are puzzling over, but one that one striking data visualization by Cubeyou explains at a glance. I don’t think there is a single article that explains his demographic quite so well.
Sometimes, the best stories are the ones words fail to describe. Take another example: OKCupid’s OKTrends blog. The title alone of their 10 Charts About Sex makes it clickbait, but the charts themselves are absolutely fascinating. They use pie charts, line graphs, bar charts, bubble charts, word clouds, Venn diagrams, and one that looks like the Very Hungry Caterpillar and defies description. If all you did was look at the pictures, you would understand the entire story they’re trying to tell.
Data visualizations like these can take any story and more quickly get your point across in a more compelling way than if you just listed out your data.
Telling Qualitative Data Stories
The stories you need to tell may not be as sexy as, well, sex, or as divisive as a hotly contended presidential candidate, but using data visualizations to tell your stories is still the quickest and most compelling way to get your ideas across.
Of course, data visualizations are usually only used with quantitative data.
But qualitative data has a different set of stories to tell.
Qualitative data includes any information that can be captured, that is not numerical in nature. This data comes from interviews, direct observations, or open-ended survey responses.
It’s the difference between “That party ROCKED!” and “That party was twice as fun as the last party.”
At first glance, qualitative data looks like it couldn’t possibly convert into numbers. It’s amorphous, emotional, intangible.
But then there’s NodeXL, an open-source template for graphing social network data. Check out the graph of 8,490 Twitter users discussing Snowden.
This chart shows how multiple groups form around the “Snowden” topic in “polarized crowds” (e.g., they’re all talking about the same issue, but each person only communicates within their own ideological camp).
Sentiment viz visualizes sentiment analyses around keywords, showing the wide ranges of emotions each word or phrase evokes in real-time. Words like “Christmas” and “Hanukkah” have overwhelmingly positive associations, but other keywords show just how varied public opinion can be.
Clearly, what people say, think, and feel can be quantified. And, you can use data visualizations like word clouds and bubble charts to tell the stories of customer interviews, customer sentiment (by marketing or demographic segment), or the number of children who played with your toy in the last focus group (versus those who sat in the corner looking confused). Before and after comparisons can be especially revealing with these types of charts.
Visualizing qualitative data also adds life to research and reports, like this chart from the State of Startups report for 2015.
When you have both quantitative and qualitative data, you can even show them side by side, like Johanna Morariu and Ann Emery did here.
Whatever your content may be — case studies, e-books, blog posts, internal reports — qualitative data can help you tell parts of the story quantitative data may miss. After all, not everything that counts can be (easily) counted.