5 Simple Tips for Better Data Visualization

As content marketing becomes increasingly visual, it’s important that marketers are able to efficiently and accurately leverage data visualization. Otherwise, it’s possible that all of your analytics and data collection efforts could be wasted in a myriad of words and numbers. Thankfully, it’s not extremely challenging or demanding to create vibrant and clear visualizations.

Keep These 5 Tips in Mind

As marketers, we have access to lots of data. And while there’s rarely a shortage of information available, the challenge is consolidating this information into something that can be digested by readers.

“The mass of inflowing data is too overwhelming and fast for us to single out one meaningful piece of information and take our time to understand the causation behind it, its impact and context,” writes Agata Kwapien of datapine. “This is why journalists should use data. It enables them to transform something abstract into something everyone can understand and relate to.”

While Kwapien is discussing the use of data in journalism, the takeaway remains relevant for content marketers. If you want to grab the attention of your readers, you need to invest in better data visualization. Here are some tips:

1. KISS

You’ve probably heard the KISS acronym, which stands for “Keep it Simple Stupid.” Well, this rule applies to data visualization. If you want to keep readers focused and moving towards a particular conversion goal or call to action, it’s important that you keep the visualizations simple and straightforward.

2. Select the Right Format

Different types of visualizations exist for different situations. While choosing the correct data points is most important, don’t underestimate the need to choose the appropriate format. A pie chart may work in one situation, but would a line graph be better in another? Think about the message you’re trying to convey and then choose the format that allows users to clearly understand the takeaway. Here’s a helpful guide to choosing the right format for any situation.

3. Use Colors to Your Advantage

One of the most valuable tools you have is color. When developing visualizations, color can be used to add emphasis, draw connections between different graphs, or highlight particular data points. Use color when you need to help the reader draw the right conclusion and be aware of how different shades, hues, and tones communicate different messages. For example, green is considered positive, whereas red may be seen as alarming.

4. Avoid Distortion

One problem that people often encounter is creating a visualization in one format only to publish it in another. This frequently results in distorted images that are blurry, grainy, or otherwise unreadable. To avoid distortion, it’s important that you design visualizations in high-quality formats that can be scaled up or down according to the needs of the final format.

5. Use the Squint Test

Any time you use a chart or graph, it needs to pass the “squint test.” In other words, when you squint at the page, are you still able to get anything from it? Or is it useless? The squint test simply provides a quick way to gauge whether or not the visualizations you’re using are effective.

Satisfying the Demand for Visuals

In the marketing world, you could say that data visualization is the new black. Readers are becoming more accustomed to sleek charts and beautiful imagery, which means black text on a white screen no longer does the job. If you want to maximize the value of your data and engage with users, it’s important that you learn how to satisfy this demand for better visualization. Use the tips mentioned in this article to get started.

About Larry Alton

Larry Alton is an independent business consultant specializing in social media trends, business, and entrepreneurship. Follow him on Twitter and LinkedIn.

One Response to 5 Simple Tips for Better Data Visualization

  1. Victor says:

    Hi, Larry!
    Thank you for these useful tips! I’ve got interesting things there.
    Agreed that visualization is a critical element of the data publishing. So it’s very important to implement different graphic/video/etc. solutions for it.