Are you burnt out on infographics? We often see organizations relaying messages using generic and unengaging data visualization methods. And—to be honest—it gets a bit old. Here are several problems that are dragging down data viz:
- You’ll commonly come across “ice cube infographics” or those depicting icons in little square boxes where all the icons essentially look the same.
- Devices and technology are ever changing. How do you keep up when we’re constantly being told to learn new tricks? No wonder you feel like the world keeps coming out from under you. Just when you learn how to use a new tool, the next brighter and shinier one is released.
- There’s too much data and visualization information so we experience burnout. Visualizations are getting so complex that they’re no longer useful and instead lead to information overload.
So how do we bring life back into data visualizations and avoid these common problems? That’s the topic Sonia Jalfin, founder of Sociopublico, and Carni Klirs, Senior Graphic Designer at the World Resources Institute, addressed at the October DC Breakfast Club.
Here are some of our takeaways from the discussion.
1. Use your words.
The saying goes that a picture is worth a thousand words, but sometimes a picture can’t express what you need to say in…well…words. Don’t be afraid to use words as part of your data visualization strategy.
It’s okay to use words to provide context for your data. Alternatively, you can use charts (with words) to enrich your data, or you can use things like chatbots that “talk” to you to help you get to the data you’re interested in. You ask the chatbot for data and it gets you what you’re looking for based on the words you typed in. A picture isn’t worth a thousand words if no one understands the image, so use your words.
2. Build something useful.
Everyone wants to think that their data visualizations are applicable and practical, but are they really? The next time you’re deciding how to spend your time and budget on data visualization, ask yourself “Am I creating something useful for my intended audience?” If the answer is “No”, then you may want to rethink your approach. Maps and graphs, for example, can be very helpful to your audience who is trying to better understand the data you’ve provided.
3. Put your audience at the center.
When designing and crafting your visualizations, think about who will be engaging with them. Data visualization is not just about what you want to say. It’s also about what it is that people want to hear. Get this—people are selfish. I know, mind blowing news, right? And because we are selfish, we are more likely to engage in visuals that tell us something about ourselves. When data is organized around the user, they’re generally interested. For example, you may want to consider personalizing a graphic with someone’s name on it. That’ll grab their attention.
4. Provide an experience.
Your audience is more likely to engage with your data if you give your audience experiences, not just knowledge. Think about what you’re communicating, and then see if there are ways you can create a data-driven yet personable experience that is immersive and appealing. Essentially, you want to entice your audience to dive in and interact with your data, which is easier to do if there’s a surrounding and related experience. Keep in mind, however, that when you create an interactive graphic, it is also important that your audience is able to capture all the crucial data from the static version of the graphic in case they don’t partake in the experience.
The World Resources Institute created a data visualization of greenhouse gas emissions by country that is both interactive and engaging, allowing the user to zone in on certain regions or see overall emissions for countries across the world.
5. Ask the right questions.
As you build your data visualization, it’s important to ask the right kinds of questions to ensure you’re producing effective content. Here are some good ones to start with:
- Do you want a static or interactive data viz? Will it become interactive if a user simply hovers, or do they need to click on it?
- Are custom visualizations worth the effort? Do they bring you closer to your goal?
- How do you track and measure if your visuals were effective?
- What voice or tone are you going to use? Playful and fun or neutral and authoritative?
- How do we incorporate data viz in rich media, such as podcasts or video?
User-centered and immersive data visualizations are key, and by asking the right questions, you’ll get closer to bridging what your audience wants to hear and the story you’re trying to tell.
If you’re looking for a deeper dive into data visualization and how it applies to think tanks, you may be interested in reading some additional thoughts on the subject.