How to Grab Attention With Your Data Visualizations

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The moment you glanced at this post, you were judging it. Before you were even aware of it, you were judging how long it seemed, what colors are visible on the page and in the images, whether or not the visuals prompted any emotional response, etc.

No matter who you are and whether or not you’re aware of it, every single time you’re presented a visual scene – whether looking at a web page, walking into a room or turning on your television, you start to make sense of that visual experience within 1/10thof a second. This is referred to as “pre-attentive processing” – you process visuals literally before you’re paying attention to them.

The most effective data visualizations take advantage of the notion that humans are pre-attentive visual creatures – that before we’re even conscious of what we are presented, we are starting to make sense of things, judging the sizes, shapes, colors, contrast, etc.

With this in mind, you should carefully consider the design choices you’re making and whether or not your visuals are bringing clarity or causing confusion during that pre-attentive period. The more clarity you can bring to that pre-attentive brain, the more likely you are to provide incentive and direction to users to continue to explore your content, thereby revealing more information and knowledge to them.

Here are 3 quick go-to techniques that I recommend you carefully consider on every project to most successfully capture your pre-attentive audience’s attention and interest.

The most important thing you can do for any communications task is to actually Know What You Really Want To Say. This is my “worst-in-class” acronym KWYRWTS (pronounced “k-whir-wits”). It’s a mouthful and hard to type, and impossible to remember. But, it is the most important thing you can do. You have to know your message before you can communicate anything to anyone. This applies to all of life, not just work.

For instance, if I go to McDonald’s and step up to the counter and start talking about the weather, politics or even if I’m semi-on-topic and talk about spaghetti and meatballs, I’m wasting everyone’s time (not to mention pissing off the people behind me in line). I need to do what I’m there to do, which is order some burgers and fries.

So how does KWYRWTS apply to data visualization? I can’t just decide what the data is saying – this isn’t about lying with your numbers. The point is that you need to understand what you’re trying to accomplish with your visualization.

Why do we visualize data? The only reason is to reveal patterns, outliers, trends, correlations and make comparisons that can’t be easily (or at all) found when looking at a table of numbers. But the devil is in the details here.

For instance, say your boss handed you 12 quarters of financial performance data for your company and said to do a report for your CEO. What do you do? Your first instinct might be to create a line chart with 12 data points for gross sales, profits and stock price. But this is allowing the data you have in-hand to drive your decision about what chart to use, what data to share, etc. This is not a strategic approach.

The right thing to do is to first find out what is the purpose of the report. Ask yourself:

Well, maybe you need to do a quarterly report but break it out by division … and maybe it’s less about the gross sales and all about profits … or maybe it’s all about the fact that the world’s demand for widgets has gone down, as it always does when gas prices are low, but the coming spike in gas prices will surely result in a rebound of widget sales, so a fuel price prediction data display along with projections about widget sales would be most appropriate.

KWYRWTS is the most important first step in any project.