14 Jun Indispensable Skill for a Marketer: Data Visualization
Early in high school, my English teacher said something to me that I can’t forget. I was reading an essay by some famous author and it was difficult to understand. It had big words that I had never heard and the prose seemed unnecessarily complicated. So I asked the teacher why the author chose to write like that. The teacher told me that decades ago, some writers liked to display their writing prowess and intellectual superiority by using big words. If we can write and easily understand what they are writing then they are no better than us. As I thought about it there was some logic to that. One reason I think Einstein was way smarter than me is that he figured out the Theory of Relativity and I still do not understand it even when it is explained to me. And I have tried.
But for a marketer, the opposite has to be true. For us, our message is only as good as our ability to communicate it. We have to make complex things simple to understand. The mechanism of action of a drug, superiority of a device, efficiency of a service has to be explained and shown in simple terms. As, my hero, Einstein once said,” If you can’t explain it simply, you don’t understand it well enough.” When I teach marketing and business classes, I take great pride in making complex topics easy to understand with examples and visual tools, I discovered that when I did not fully understand all nuances of a topic, I had greater difficulty explaining it in simple terms. Simplicity does not mean a simple mind.
So how can a marketer distill plethora of data that we collect into valuable insights and then deliver it in an easy-to-understand manner to the audience? We must become, at least adequate at data visualization or dataviz.
Data visualization can be defined as a way of encoding quantitative, relational, or spatial information into images to make it easier to understand and digest for a reader.
There is so much data and we have to do the grunt work, not our audience. We have to uncover important nuggets of information, separate wheat from the chaff, and then deliver it precisely, concisely, and in a visually appealing manner. One of the basic ways of dataviz is by making charts, graphs, or infographics. Infographics is a topic unto itself and will be covered in a separate blog.
As a marketer, we get an abundance of data. It could be performance data from a clinical trial, competitive intelligence, or sales performance. We have to convert this information to actionable insights, share subtleties with colleagues, and determine course of action. This serves two purposes. First, it helps us understand what is happening and why. Second, people would appreciate the work you did to recognize and ignore the clutter to bring the real story to life. If you overwhelm them with information, they will tune you out. I wish I had a dollar every time I have heard at the end of a meeting, “so what is the take-home message.” That is a clear sign that you lost them. They just want to know what the bottom line is, in case it is something others may expect them to have picked up by sitting through that dissertation. And they clearly did not and want you to throw them a lifeline.
Some data visualization tips:
- In a chart or table only show copy or illustrations that tell your story. If you get your hands on a table with sales data on diuretics, calcium channel blockers (CCBs), and angiotensin receptor blockers (ARBs), but you and your audience care only about ARB sales, just show data about your drug, e.g., Avapro, and other ARBs like Diovan, Cozaar, Atacand etc. There is no sense in cluttering your message by showing sales information on diuretics and CCBs.
- Do the math for them. If you see someone take out a calculator, you failed them.
- Don’t use colors to be colorful. Use colors to distinguish things, make them easy to see, and bring certain ideas to life. Use colors to show different objects. For example, if you are showing sales data between January 2017 and January 2018, use different colors for each year. Make sure there is sufficient contrast between colors. For example, I have a Rummikub tile game which has 4 colors; blue, yellow, orange, and red. Frustrated players frequently ask, “Is that tile orange or red.” They have a hard time telling them apart. I’d like to ask the manufacturer,”Why?” Did they run out of colors or they like to irritate people? It is baffling. On the other hand, if you are showing intensity of one parameter, like temperatures or population density, gradation of one color works well.
- Avoid pie charts. It is not overly clear which slice is bigger than the other. Use bar graph instead.
- If a pie chart has to be used, limit the numbers of slices to 5 or less.
- If a comparison is being made between 2 things, try to have them on one slide side-by-side or the very next slide, if space is an issue. Don’t have one as Slide 14 and the other as Slide 35. Now I understand sometimes you have to build up the story before you can show what you have on Slide 35. The story needs to mature more and cannot be shown on Slide 14 or 15. In this case, re-insert Slide 14 as Slide 34 and remind people what they had seen previously.
- If numbers have one or more outliers, use a scale break. If you do not know what I am talking about then try to graph the following:
- Labels seem to give some people difficulty. Make sure everything is labeled, labels are clearly visible, and legends are clear. If you can label lines directly, readers won’t have to hunt for what they stand for.
Following these data visualization techniques will add clarity to your presentations. And you can be certain that your audience would appreciate it.