There’s the old saying that “a picture is worth a thousand words” — meaning that it’s easier to convey ideas and concepts visually than through text. The majority of the sense receptors in our body are in our eyes. Some people are more “visual” than others, but the visual representation of information is still one of the most powerful mediums for getting your message across.
When it comes to reporting and analysis, creating visual representations of data is nothing new. William Playfair is generally attributed with creating some of the earliest trend charts in the late 18th and early 19th centuries. One of my personal favorites is Charles Minard’s depiction of the losses sustained by Napoleon’s army in his march on Moscow in 1812. It combines a high level of information with simplicity and elegance.
Given that we’ve represented data visually so long, it’s a wonder why we still don’t get it right. We can all probably think of a report or some charts that we’ve seen in the last week that were unintelligible and left us none the wiser about whatever it is that we were supposed to know.
There’s an apocryphal story about Arthur Nielsen in the 1930s. Arthur Nielsen had just invented the concept of a “retail audit” to measure sales of products in grocery outlets. For the first time, manufacturers could see how much of their products were being sold in stores and what their share of the market was. Nielsen sold this data to the manufacturers in reports that were delivered every two months.
At the beginning, everything was fine, as the novelty of this type of information gave manufacturers new insights. But after a while, manufacturers were cancelling their contracts with Nielsen.
When one of his biggest clients said they planned to cancel, Nielsen asked why. They responded that, although they found the data interesting, they didn’t really know what to do with it. As a result, it wasn’t bringing enough value.
The story goes that Nielsen persuaded the client to let him demonstrate how they could use the information. If he could prove its value, they’d continue with the contract. He worked through the night on a train from Chicago to New York, charting the data and creating trend analyses that allowed the client to see the cause and effect of their marketing activity.
By creating charts, rather than relying on reports, he was able to demonstrate the value that could be extracted from the data they had. They remained a client for decades and the visual representation of information became a standard paradigm for all Nielsen services.
Despite the advances in technology (Nielsen’s charts were drawn by hand), many problems are still associated with good data visualization. One challenge is that we’re sometimes constrained by the technologies, such as the typical desktop applications we use everyday.
But we also forget that the most powerful messages are often the simplest. When it comes to marketing analysis and insight generation, we’re often involved in a massive data reduction exercise. We need to take the vast array of data at our disposal, reduce it down to some salient points, and then present them clearly and effectively.
Great analysis and insight can often be let down by poor presentation and communication. Sometimes this is where the technology doesn’t help.
In the latest version of Excel and PowerPoint, there are around 75 different chart templates available. For most insight presentations where I need to display data graphically, I probably use three chart templates: a simple line chart, a simple column chart, and a simple bar chart. Occasionally, I may use a scatter chart to show the relationship between two different variables or a bubble chart. I still have to work out when I would need to use the “100% Stacked Horizontal Pyramid” chart.
This is the trap that we get ourselves into sometimes. Having a “Doughnut” chart option doesn’t mean we need to use it.
At a time where more information is being delivered via presentation, “dashboards,” and the like, it’s important to remind ourselves of the purpose of the data visualization. It’s to make the point you’re trying to make simpler to understand rather than to demonstrate the prowess of a technology.
A picture is often worth a thousand words, unless it’s a “100% stacked area in 3D” chart. Simplicity and elegance are the watchwords.
Marketers need to know what’s in their data and trim out the filler to provide continuous, data-driven ROI for their brands.
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