In the first part of this three-part series on metrics, we discussed bad metrics (aka vanity metrics). If you’re new to this post, you may want to read the first article in this series on metrics and then hop on back.

Ready or not, let’s dig into ugly data, and by that, I mean flawed charts.

The Ugly – Flawed Charts

As often as product managers talk about making data-informed decisions, it’s amazing how often data is presented in ways that are completely misleading or downright wrong.

Many of you may remember the Venn diagram incident from Hillary Clinton’s presidential campaign several years ago.

The general point her campaign team was trying to make was true. The majority of Americans support universal background checks, including a majority of gun owners. If you think about it, though, the yellow circle should be completely inside of the blue circle because the gun owners referenced here are all Americans. But that’s now how Venn diagrams work! This information should’ve been presented using a different type of chart.

In this example on the right, it appears the designer messed up the doughnut chart. As you can see, the green line goes around more than half of the circle, even though the number referenced is 41%.

The chart to the left is bad for several reasons.

If you follow the use of colors, you’ll see Iceland, Finland, Portugal, and Spain nicely represented with different colors. Then it shows the UK, Denmark, Australia, Venezuela, and Kenya as part of the same country. This would’ve worked much better as a simple bar chart!

The lesson here is to make sure you use the right type of visualization for displaying your data and that your chart is correct.

Where to get help with selecting and creating charts

If you’re struggling with deciding which type of chart to use, I highly recommend From Data to Viz.

Whether you’re new to the world of creating graphs or you’ve been doing this for years, this website is a treasure trove of information about how to present data.  

Based on the type of data you have, such as chronological or numerical, it will guide you through the relevant types of visualizations that are best suited for your particular case. 

Depending on the type of chart you’ve selected, it will also inform you about the pitfalls to avoid.

Another great source of information is this book by Edward Tufte. The Visual Display of Quantitative Information is the bible in the industry. I can’t recommend this book enough!

Ff you ever get the chance to attend one of his seminars, it’s well worth it!

Now you know how to avoid some of the biggest mistakes when creating data visualizations. Plus, you’ve got some great resources to get inspiration on the best way to present your data effectively. Being able to communicate data persuasively is a key skill all great product managers should have. It will help you manage your stakeholders, influence product decisions, and build support for your work. Wield this power wisely, grasshopper!

The next and final post of this series will culminate with how to use data for outcome-based product teams. Don’t miss it. Sign up to stay informed when it comes out.

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