January 08, 2015
Stats Shouldn't Stand Alone: Why You Need Data Visualization to Teach and Convince
What makes a good story? Strong characters, some suspense, a bit of humor, and a clear outcome.
Telling stories in business is no different; the same elements engage and compel us -- with one exception. The rational decision-making required in the business world needs an objective foundation. That's where data comes to your aid. When you need to deliver an interesting message, prove a point, or communicate information to convince your boss, colleagues, or prospects, data is a great tool to use.
All too often, marketers rely only on text and statistics to communicate. But data alone -- without context or proper presentation -- can be stale or difficult to interpret. Whether you’re delivering a report to your boss or editorial content to your blog readers, visualization can turn glossed-over data points into a convincing, memorable story.
We're going to dive into three ways data visualization can help you connect with your audience, but first, let's explore how data visualization -- where data meets design -- can transform any ordinary idea, message, or argument into one that compels your audience to take action.
The Value of Data Visualization
So why should you be more proactive about not only using trustworthy data to support your ideas, but taking that data even further with visualization?
Why Data Visualization Makes for Better Content
Data visualization adds credibility to your content.
Convincing data demonstrates that you’ve done your research and provide a strong, objective foundation for your argument. This solid foundation increases your argument's overall credibility and helps your audience have more trust in you and what you have to say. Effectively presenting that data in a clear and easy-to-understand visualization can furthermore show -- not just tell -- your audience what you want them to know.
To see what we mean, let's explore two separate visuals that each attempt to do the same thing: communicate the risks of Type 2 diabetes and ways to prevent it. Which one does a better job conveying information? Which one makes you want to adjust your own lifestyle if you happen to be at risk for diabetes?
The brochure below aims to convey the risks and concerns of a serious disease, but only offers one data point to support its argument. “Type 2, it could be you!” is the message supported by a sole statistic telling us Type 2 is the most common form of the disease, affecting 85%-90% of diabetes sufferers. But where is the comprehensive story? Where are the additional data points that inform us more about what Type-2 Diabetes is, who it affects, why it might affect us, and what we should do to best prevent the disease?
Contrast the brochure with this data-heavy infographic. Unlike the brochure, the infographic goes above and beyond one data point by providing statistics on who is affected by Type 2 diabetes, the complications of the disease, the top predictive disease factors, and what preventative measures we should take. What's more is that each data point is illustrated to ease our ability to digest all the information, to be convinced to take Type 2 diabetes seriously, and to take responsibility for our own health.
See how the combination of supporting data and design turned the infographic into a much more credible, trustworthy, and convincing piece of content than the first example of the brochure?
Data visualization increases the impact and recall of your idea, argument or message.
If your valuable insights are glossed over or easily forgotten, why share them in the first place? By presenting data that's well-designed, information can come to life to help your readers interpret and remember what they are looking at.
Infographics (information + graphic) are a popular medium through which to communicate data, but it's important to note that an infographic is not synonymous with data visualization. Infographics ideally should contain visualized data, but an infographic that simply states one or more statistics with accompanying images does not count as data visualization.
Here are two different infographics that illustrate this difference. Each aims to communicate the same message -- that raising a child is expensive -- using the same data source. Which piece of content uses visuals to help convey data rather than merely illustrating around it?
In the below graphic, data is presented but not visualized in a way that allows us to draw comparisons or to understand in a larger context. We're left having to do some mental olympics to figure out how the percentage of income spent on food compares to other categories, or what the cost of raising a child over time looks like. While the stats are depicted with text and images, the visual leg work hasn't been done to present the data in charts, tables, graphs, or other visualizations that utilize differences in length/size, shape, orientation, and color to decrease mental processing on your viewer.
On the flipside, the graphic below, which you can explore in detail here, features much of the same information, but it uses data visualization and design to break the information down to the viewer. Notice the color segments on the stacked bar chart and how they make it easier to not only compare categories, but to see them as compared to costs in 1960. The line chart clearly shows us how much the cost of raising a child has increased over time. These simple tweaks make the data much easier to interpret, and more impactful as a result.
Data visualization encourages engagement and action from your audience.
In addition to adding credibility and increasing the impact of the message you're trying to communicate, well-designed data -- whether presented in a static or interactive form -- can communicate a greater depth of information than mere stats coupled with images. Layers of detail allow someone to quickly comprehend high-level insights or explore any areas of particular interest further.
The screenshot below of a detailed interactive visualization communicates not only the number of deaths caused by gun violence but also how much of life is truly lost -- an arguably more engaging angle. Users can explore the data by sex, age group, region, and time -- each adding another layer to argument that guns lead to premature deaths.
This post appeared on Hubspot on November 19 2014 and is reprinted here with permission. It was written by Ross Crooks, cofounder/CCO of Visage and co-author of "Infographics: The Power of Visual Storytelling" (Wiley, 2012).