When I was in middle school, a cool girl invited me to her birthday party at the country club. I wanted to impress, so bad. This was not my place. These were not my people. But I was gonna try.
So, after luscious cupcakes, I climbed the ladder at the country club pool all the way up to the high dive. I’m scared of heights but my desire to carry out my mission and make friends overruled my shaky legs. Once I got to the top, I realized, I don’t really know how to dive.
So my head told my body to just do what it looks like in the movies: elegant swan dive.
In reality, I bellyflopped so hard.
Some of my hopeful friends snickered. Some just turned their heads away from the crime scene and didn’t speak to me again.
It’s felt the same when my graph and I bellyflopped into the deep end, right down to the emotional damage and painful abdomen.
I’ve learned that if your viz flopped, it’s because you’ve messed up one (or more!) of these four areas.
The point isn’t clear.
Nobody wants to expend their limited time and focus trying to decode a cloudy graph. You’ve got about 3 seconds to get your initial point across. The easiest way to save your graph from flopping in this particular area is to use some text (like your graph’s title) to tell people your point.
See how this works?
Even if you still need to fix up your formatting or rethink your chart choice, your point will be clear.
You mismatched the viz and the audience.
Graphs flop when they aren’t answering the right questions.
Like, your leadership wants to know if the new infant health program is saving lives but you’re in the meeting with a graph about the number of brochures you distributed. Honey, that’s like bringing candy corn to a dessert bakeoff with Martha Stewart. You’re gonna be eliminated in the first round.
We get into this situation when we don’t understand our audience. Or when we simply don’t have data collection set up well enough to track the important indicators that’ll answer their questions.
You can also mismatch when you have the right data to answer the right questions, but the graph is pitched at a different level of data literacy.
Let’s say you’re headed out to staff the booth at a local community festival, where you’ll hope to engage people in conversations about maternal and infant mortality. But you’ve got this as your visual aid.
This visual is pitched for a highly academic audience. (Though I suspect many folks who say they have high data literacy would still struggle to interpret this.)
You’re gonna get people at that festival trying not to make eye contact with you. Because this visual isn’t hooking them in.
It’s aesthetically difficult.
My dear that’s another way of saying your graph is ugly. Oh you thought beauty standards only applied to humans? Nope, they’ve come for your graphs, too.
Thankfully, the beauty standards for graphs aren’t as oppressive and unrealistic as those foisted upon women.
You’ll get halfway there just by changing up the default formatting settings in your software (no matter which software you use).
I can walk you through the formatting steps you need to take. Get my data viz checklist and I’ll point you in the right direction.
You chose the wrong chart type.
Even if you’ve got a clear point in a well-designed graph pitched to the right audience, you can still bellyflop if you’ve chosen the wrong chart type. Your audience is going to read your point in your title and then look to the chart for evidence that confirms your point. If the evidence isn’t obvious because your chart choice is disguising it, you’re done.
And I feel for ya, because most people don’t know about all the possible chart choices that are out there. So we make bad decisions because we don’t realize that a better graph is possible.
I have so much more to say about choosing the right chart type. We teach you the strategic thinking you need to ace this (and how to make the right chart you land on) inside the Evergreen Data Visualization Academy.
Get on the VIP list for possible discounts and early access next time we open enrollment.