5 Data Visualization Mistakes Most Infographics Make

By September 5, 2019 June 29th, 2021 Data Visualization, Infographics
illustration of effective data visualization, including graphs & charts

How many times have you seen a confusing graph or chart, and needed to read the details to understand what it meant? If you’re like us, plenty of times! Or how about the times when you don’t even have a graph or chart to reference, leaving you with only a block of text to explain the information? Again, we hear you. Proper data visualization is a unique, niche skill set within graphic design. But when you want to create a great infographic, data visualization is indispensable in communicating information quickly and clearly.

There are many ways to use data visualization correctly. Yet there are many more ways to miss the mark. Here are just 5 mistakes that many infographics make when it comes to data visualization.

1. Missing Opportunities for Data Visualization in Graphic Design

Quality visual communication takes advantage of every opportunity to visualize information. That means reducing reliance on text by letting the visuals do the work.

How can you do this? Include appropriate icons and illustrations along with data visualization wherever possible in your infographic. Use typography only when you need it to supplement and/or elevate the visuals, such as in introductions and conclusions.

In other sections of your infographic, check to see whether a visual makes sense first. Use typography only when no visual element or data visualization will accurately convey your information.

2. Failing to Consider Hierarchy in Data Organization

When the numbers in your data set are out of order — jumping from 12,000 down to 800 and then up to 14,000 — it can be more difficult to see trends and correlations. Order your data sets from largest to smallest, or smallest or largest, to keep things organized and simple to understand.

The exception? When your graph’s axis forces an order. The most common reason for this is chronology, such as with a timeline. What if the 12,000 value was in 1996, the 800 value in 1997, and the 14,000 value in 1998? The correct choice is to keep the data in that order, even though it’s not largest-to-smallest. With a timeline, chronological order is the most intuitive method. Imagine analyzing trends on a graph that jumps from the year 1997 down to 1996, and then back to 1998!

Data visualization examples for infographic design and more

3. Failing to Highlight the Most Compelling Information

Let’s say you need to use data visualization for the following stat in your infographic (totally fabricated for the purpose of this post):

90% of buyers will spend at least 10% more on groceries when the items are 25% off.

That’s a lot of percentages. Which one is most important? You could make a donut chart for the 90%. Then, a stacked bar chart to show the 10% increase in spend. Finally, a stacked bar chart to show the 25% cost decrease. Yet, if you put all these together, it’s hard to discern which piece of information is most important.

The thing is, there isn’t always a “correct” answer. What portion of a stat is most important might depend on the variables your audience is most interested in. On the one hand, 90% might be the most important because it refers to a significant proportion of people, implying that price reductions may have huge impacts on consumer behavior. (Remember, this stat was fabricated solely for this example!)

However, what if a particular grocery store in your audience has never experimented with discounts? While they’re impressed with the 90% figure, maybe they’d rather know whether a 35% discount could boost that number to 95% of buyers. Meanwhile, a different grocery store may want to find a way to get their buyers to spend 20% more, instead of 10%.

The most important info in a statistic is not a constant. For a successful infographic using data visualization, make sure to visualize whatever the most important stat is for your unique audience.

4. Using the Wrong Type of Data Visualization in Your Infographic

When many people think of visualizing a percentage, they assume that a pie chart or donut chart is the right way to do it. While this can be the right choice, it isn’t always.

Pie and donut charts are appropriate when you’re showing a percentage of a whole — for example, 50% of pet owners. However, when you’re comparing 2 numbers — say, 50% of pet owners and 29% of non-pet-owners — a pair of side-by-side pie charts isn’t as effective at showing the comparison as a stacked bar chart might be. Further, when showing a percentage increase or decrease (15% more pet owners than last year), a pie or donut chart would never be appropriate. That’s because the finite limit of a circle is 100%. One could never make a circle that showed more than 100% of anything.

All chart and graph types have specific use cases. Make sure you know what type of data visualization — or other graphic — is the right choice for your design.

Data visualization in graphic design, including pie charts, donut charts, circle charts

5. Not Including a Scale

Without a scale, there’s no real frame of reference for the true value of your data. In the below example, on the left, 25% looks like a very significant number — it takes up nearly the whole frame. But it’s common sense that 25% isn’t a large value in comparison to 100%. It’s certainly not a majority, even though it appears that way in this example. In all types of graphic design, the importance of accuracy and clarity in your data visualization can’t be overstated.

Always label your axes, provide reference points for 100% when using percentages (particularly when they’re not in a circular chart, which is self-limiting), and ensure that you’re not misrepresenting your data by omitting or incorrectly emphasizing something.

Why? It comes down to trust. Manipulating data shows your viewers that you aren’t trustworthy. That’s extremely tough to come back from.

Data visualization best practices for graphic design and visual communication, like infographics

Infographics rely on data visualization, in conjunction with icons and illustrations, to speak visually. To earn your audience’s engagement, and then their trust, pay close attention to the ways you’re using data visualization.

Lucy Todd

Author Lucy Todd

Lucy Todd is the Chief Process Officer at Killer Visual Strategies. She is a Seattle native and Western Washington University graduate. Her degree in Creative Writing and her customer service background both inform her work daily. A Killer employee since 2011 and executive since 2014, Lucy has researched for, written, and/or project-managed over 4,000 projects for the company, affording her key insight into our processes and projects. This experience is invaluable in allowing her to lead and empower Killer’s content and project management teams to success. Lucy enjoys managing the day-to-day at the office, offering a unique perspective when a team or colleague feels stuck, and learning from her peers and clients each day.

More posts by Lucy Todd

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