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Home » Do people really understand your data visualizations?
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Do people really understand your data visualizations?

EconLearnerBy EconLearnerNovember 11, 2023No Comments6 Mins Read
Do People Really Understand Your Data Visualizations?
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But many data visualization gurus advocate a different approach. One method, called decluttering, involves making charts look clearer so that the audience can more easily process the information. Another method, called focus, highlights the information or trend the presenter wants the presenter to notice—for example, by making one line red and all others gray.

Steven Franconeri, professor of psychology at Northwestern and professor of marketing at Kellogg (courtesy), and his colleagues wondered if these techniques really worked. Did decluttering or focusing help the presenters get their message across?

In a study with college students, they found that using the two methods in combination helped people more clearly understand the basic whiteboard tool. But without focus, decoupling alone didn’t have much benefit beyond making a visualization look a little more professional. People were just as likely to miss the point as when they saw a cluttered graph.

“We didn’t find the cognitive benefits that were predicted,” says Franconeri.

Some presenters may think that the focus technique is unnecessary because the pattern “screams at the audience,” he says. But what seems obvious to an expert may not be to an audience.

Presenters have “a curse of expertise,” says Franconeri. “They see what’s important in a chart and they think the public does too. They are usually wrong.”

The research suggests the importance of not just letting the data speak for itself and the benefit of using multiple techniques to guide people toward a desired conclusion.

Fundamental flaws

Charts are ubiquitous in business presentations because the appeal to people’s visual system “can be extremely powerful,” says Franconeri.

But many of these charts fail to convey their message effectively. They often cause confusion or leave people unsure of the main conclusion. “Most data visualizations seen in business settings have some fundamental design flaws,” he says.

The declutter technique, advocated by many data storytelling books, involves removing extraneous visual elements. For example, presenters are advised to delete borders, gridlines, checkmarks, and unnecessary data value labels. And instead of using the whole rainbow, they should minimize the number of colors or make everything gray or black.

For the focus technique, presenters are asked to add a clear heading or text that explains the basic trend in the data. For example, it could read “X is growing twice as fast as Y” or “A and B are the two most important factors.” They will then call out this pattern by making the relevant bars or lines a different color than the rest of the chart.

Franconeri’s team—which included Kiran Ajani, Elsie Lee, Cindy Xiong, and William Kemper, then at Northwestern University, as well as Cole Knaflic, CEO of the company Storytelling with Data—wanted to quantify the effectiveness of these techniques.

In particular, the researchers questioned whether the declutter technique would have the benefits claimed by the gurus. The assumption was that a sleeker design would “remove the information firehose and enable people to focus on the data,” says Franconeri. But his team hypothesized that it might not be that difficult for the public to filter out the grid lines or labels.

“People have a lot of experience looking at this kind of clutter, and they’re able to tune their brains to block these things out,” he says.

Cleaning up the mess

To test the techniques, the researchers assembled six graphs that presented data on different topics. For example, a bar graph showed drivers’ top design concerns for a new car model, and a line graph showed how people’s news sources had changed over time.

For each chart, the team created three versions. One was a cluttered chart with a lot of excessive graphical detail. The second was a much sleeker, sleeker version entirely in shades of gray or black. And the third was messy and clustered, with the basic tendency to be told in a different color and an explanatory title or caption. (The team did not create graphs that were cluttered and focused, because the focusing technique generally requires decomposition first to pick out the relevant trend.)

For example, on the line graph about changing news sources, the team added the headline “A growing percentage cite the internet as their main source of news,” with the word “internet” in bold blue. The lines and labels for “internet” on the graph were also bright blue, while those for other news sources (TV, radio, newspaper and friends) remained gray.

The researchers then showed the graphs to 24 students and community members at Northwestern. Each participant saw two versions of three data stories. After looking at each chart for 10 seconds, they were asked to redraw the chart by hand. They also wrote what the graph was about and its main conclusions. Finally, participants were shown all three versions of each chart and asked to rate the charts on aesthetics, clarity, professionalism, and how credible the presenter seemed.

Memory booster

When the team compared responses for uncluttered versus uncluttered charts, they found that people thought the uncluttered versions were more professional. But, importantly, when it came to redrawing the diagram or correctly describing its conclusions, participants who saw the uncluttered version did not perform significantly better.

Adding technical focus, on the other hand, had a significant effect on comprehension. Compared to people who saw a graphic only with unfocused, participants who were shown a graphic that was both defocused and focused were about 2.5 times more likely to record the main conclusion in their written descriptions. And they did a better job of redesigning the related trend.

“People definitely had a better memory for the highlighted pattern,” says Franconeri.

Users also rated focused graphs higher for aesthetics and clarity than graphs with only inappropriate content. But some participants had complaints about the plan. In written comments, some complained that the focused charts seemed unreliable because the presenter appeared to be pushing an agenda.

Franconeri says presenters should be aware of the risk that the focusing technique can prove cumbersome, but he believes the cognitive benefits outweigh this potential downside. “The vast majority of people will appreciate guidance in the right pattern,” he says.

Because decluttering seemed to give a sense of professionalism, it’s still worth using this technique—and more importantly, it helps pave the way for the focusing technique, says Franconeri. To draw attention to a trend, the color palette should be reduced so that the important lines or bars can be seen. Presenters should keep the number of colors to a maximum of two, and ideally one, he says.

Storytelling skills

The study suggests that audiences are accustomed to clear graphics that guide their attention to key elements such as those displayed The New York Times‘ Upshot section, FiveThirtyEight.com and other media sites. Professional presenters should follow suit.

“Pasting straight from Excel isn’t going to cut it anymore,” says Franconeri.

Some presenters may be able to get help from their organization’s graphic designer with simpler tasks such as absorption. But not all work can be outsourced. You’re the expert on your own data, so unless the designer interviews you to “pick your brain,” they may not know what pattern to highlight and how to comment on it, Franconeri says.

“Typically you can’t delegate it to someone else,” he says. “Anyone who presents data to other people needs to know the basics of data storytelling.”

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