Qualitative Chart Chooser 3.0

Why isn’t qualitative data viz as well developed as quantitative data viz? Here at Evergreen Data, we are trying to tackle that. Qualitative data gives us more power to engage people’s hearts and minds. We are able to extend our data story to a more personal level.

When we are being told a story, not only are the language processing parts in our brain activated, but so is any other area in our brain that we would use when experiencing the actual events of the story. If someone tells us about how delicious certain foods were, our sensory cortex lights up. If it’s about motion, our motor cortex gets active.

Our main goal in communicating with our audience is that they will remember our main point, right? Well, when we tell people stories they are better at remembering what we say because more parts of their brain are engaged. Stories inspire people to take action.

All of that to say, qualitative data gives us more power to tell our audiences engaging data stories.

Sounds like it should be simple to effectively visualize qualitative data but it can be tricky. That is why we have all seen SO MANY bad qualitative visual representations, like endless pages of bulleted quotes. Yuck! No one likes that. It isn’t engaging, it’s cognitively demanding, and it’s super boring.

At Evergreen Data, we are committed to providing you with useful tools so you can figure out which visual fits your audience’s needs and your story.

That’s why we are proud to release the Qualitative Chart Chooser. I’ll send the very most updated version of it to your inbox.

When we designed this qualitative chart chooser, it was important for us to incorporate (1) the overall nature of the data, which drives the kind of story you can tell, (2) account for whether, in your analysis, you want to quantify the qualitative data or keep it purely qualitative, and (3) whether you want to highlight a word/phrase or display some kind of thematic analysis.

Our goal is to make this chart chooser useful for all, whether you are a die-heart qualitative person or a quantitative person who periodically asks open-ended questions.

All other visual techniques we teach at Evergreen Data still apply to all these qualitative visuals.  Let’s take something like a timeline (one of my favorite qualitative visuals).

Here is a nicely designed timeline (done all in PowerPoint). It visualizes different stages of an project overtime. No matter what way you slice it, this is slightly overwhelming. Remember your data viz secret weapon, whenever a visual gets overwhelming, break it up into small multiples. This is one of the most useful techniques to apply to qualitative visuals.

So when you include a project timeline like this in a scope of work, present it in whole form first. Then as you talk through each part of the project, show just a small portion in the margin. I also threaded color coding into the different sections of the scope of work.

We hope this qualitative chart chooser will make it easier for you to explore effective qualitative visual options. If there’s something on here that you haven’t heard of before (journey mapping, anyone?) we will tell you all about it. You can get started with our growing collection of qualitative visuals.

This chart chooser is in Effective Data Visualization, where Chapter 8 includes the largest compendium of qualitative chart choices available. 


Announcing Chart Chooser Cards

Update: After a successful Kickstarter campaign where we raised over 1,000% of our goal, the cards are in production and you can now order a deck, an infographic, and our templates from our permanent website. Thanks for your support, lovely people.

Chart Chooser cards are simple and easy to use. They help you choose the best type of chart to display and format your data.

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Each chart card shows you the common name of the chart type, a description, a visual example, when it is used, and what type of data set it’s best for.

The chart chooser deck has 51 cards, including 33 chart types organized into 6 data categories to help you quickly sort through the noise. 13 bonus cards help you sort through what people are looking for in data, and how to format your chart.

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I’ve been using these cards in my data visualization workshops. They are an awesome tool to narrow down the wide world of chart choices and identify the right one for your data.

Want a deck? The cards are now available as part of a Kickstarter campaign. We offer different pricing levels with all kinds of awesome swag, including:

An infographic of the chart types available in the Chart Chooser Cards

An Excel file with every single graph within the deck, already made and ready for your data

A Tableau file with every single graph within the deck (Bless you, Andy Kriebel!)

One-year of access to my currently-closed-to-enrollment Data Visualization Academy

With all of these tools as your fingertips, you’re well on your way to being a Data Visualization Rockstar! Check out your options on the Kickstarter page.

Juice Analytics

Zach Gemignani, of Juice Analytics fame, gave the keynote at the AEA/CDC Summer Institute yesterday. I had followed their 30 Days to Context Connection list earlier last year, so I was super excited to witness the fun in person. His keynote speech focused on the 10 steps to becoming a Data Vizard. Yep, vizard.

Good tips in there, too. One was to follow the leaders – meaning, check out the awesome folks who have cut down some of the hard work out there on data visualization. Though I thought his list was a little slim (okay, he only had 45 minutes), he did point out the range of leaders out there, from Stephen Few to Jonathan Harris (Side note: Why only white men getting to lead the field of data viz?)

My favorite tip was to think like a designer. He said there’s a thin overlap of folks who are both data junkies and designers (that’s me). But those more on the data junkie side can make tiny adjustments to normal presentations that will help make a bigger impact. For example, choose one color for emphasis and use it to actually emphasize, not decorate. My hack job of his slide, illustrating this idea, is below.

Another tip was about choosing the right chart. For help on that task, check out Juice Analytics’ chart chooser. It’ll guide you through your data needs and let you download a chart template for Excel that is designed for clarity and beauty. Cool!

From the blog