Your Graphs Look Like Crap: 9 Ways to Simplify and Sexify Data

Remember your last marketing team meeting? That one person spoke to your team and just started throwing data at you from your monthly marketing reporting deck. No context -- just numbers, graphs, and the occasional pop of color. Instead of intriguing you, he or she put you to sleep -- it was really hard to stay awake when someone was just throwing data at you.

You don't want to be that person. 

Instead, you want to be the one who uses data to tell a story in your monthly marketing reporting. The one that uses data to prove an argument. The one that makes data easy to understand. The one your boss notices for using data smartly. 

And there are quite a few ways to accomplish all of those things -- but the most simple and immediately effective is through the design of your graphs and charts. Based off of Edward Tufte's The Visual Display of Quantitative Information, the folks over at Darkhorse Analytics put together this awesome visual of the many things you need to do to beautify your data: 

I'm sure you got all of that ... right? If you're like me and need a second to take it all in, I'm going to break down each step of the GIF above to show you how your graphs can be improved.

How to Improve the Readability of Your Graphs and Charts

If you want some charts to play around with these next tips, download our monthly marketing reporting template. We'll be using it as the example throughout the rest of this post. 

1) Remove Backgrounds

Backgrounds add distraction. Remove the background color of your graph so it matches the slide background by clicking "No Fill" under the fill paint can icon in the top-right corner.

2) Remove Duplicate Labels

Your marketing teammates are smart -- they can read what's on the chart without you repeating yourself in the X-axis and legend. Plus, getting rid of duplicate labels gives you more room to tell your story with what matters: the data. 

3) Remove Borders in Chart Elements and Background

The whole point of these tips is to keep the design minimal so the data can speak for itself. Borders, like several of the design elements mentioned in the following tips, are unnecessary and distracting. Get rid of them!

4) Reduce Colors

Colors are a great way to help tell your story. For example, if the point of the slide is to show just how awesome Twitter is, you should highlight the data that speaks only to Twitter -- which is why it's the only one that has a color on the graph. Use color to make important data pop and the unimportant data take a backseat.

5) Remove Special Effects Like Shading and Shadows

Like you did in step 3, get rid of any distractions, including shading and shadows. They add to the clutter -- exactly what you're trying to fight against. 

6) Get Rid of Bold Text

Is the bold text in the chart below really adding anything spectacular? Nope. So un-bold, un-italicize, un-underline. Less is more when it comes to formatting.

7) Lighten Secondary Data Labels

Again, you're trying to highlight important data when designing graphs and downplay "meh" data. In this example, are the Y-axis benchmarks important? Not as important as the X-axis. Lighten the color, or skip right to step 9.

8) Lighten or Remove Lines

While you might think that gridlines will help you line up bars to their respective value numbers, they really only add clutter. Can you really tell how far away a bar is away from the lines to determine if it's 3.65% or 3.7%? No way. So go ahead, take those lines out.

9) Remove Y-Axis Labels and Label the Bars Directly

Back in step 7 we told you to lighten non-essential data, but if you want to really trim fat on your graphs, take out the Y-axis completely, then label each bar individually. That way, you can see exactly which value each bar is representing while also getting a general visual comparison of it with all the other bars. 

And voila! Here's what the finished product will look like:

With these few simple graph design tips, you can make your data much easier to digest -- something your boss and teammates will all appreciate. 

What other data design tips to you have? Share your ideas with us in the comments.