In today’s world, business at all levels is data-driven. Where once it was considered viable to get by on intuition and gut feeling, the advent of the seemingly-limitless internet (bolstered by rich analytics systems and tracking tools) has made it necessary to stay apprised of technical and statistical performance or risk falling behind.
But the problem with all of this data is that it’s incredibly intimidating (even to those equipped to interpret it). There are certain tasks that the human mind is suited to, but parsing vast quantities of data is not one of them. When we look at huge tables of metrics, our eyes glaze over and we stop taking anything in. Straining concentration doesn’t help. The best we can hope for is spotting the trees — the woods remain imperceptible.
That’s why we need to get creative with the presentation of data. By turning a dry table of stats into something with more visual flair and clarity, we can make it comprehensible, knowing that if we need to get more granular, we can. Let’s consider the psychology behind this.
We’re visual problem-solvers
Through natural selection, humanity developed a brain structure that works wonderfully for pattern recognition of a certain kind. In the pre-civilisation days, the most pressing concern was staying alive, for which the proto-humans needed to do two main things: find food, and evade (or defeat) predators. Each of those two tasks required the same thing: an ability to spot other animals. This essentially meant discerning animal patterns from hazy patches of color.
But this spot-the-difference ability doesn’t extend to our abstract reasoning through the language systems we’ve developed. It’s entirely sensory. This is why we find diagrams, illustrations and videos so useful. Something that we fail to grasp across several explanations can immediately click when we see a visual depiction.
When running a small business, you don’t have a large team to take it in turns to pore through analytics data, or the resources to bring in a data expert with the kind of experience needed to take one look at a table of metrics and actually understand what they mean. That’s why you need visual mapping to establish a format you can interpret at a glance.
We need a sense of scale
Furthermore, when we deal with analytics data in its purest form, we’re left without any kind of context or scale. Every metric feels as vital as any other, and there’s only a distant relationship between what we read and what we imagine. Think about the difference between reading the height of Mount Everest and actually standing in front of it. Until you see it, you can’t truly understand what the height figure means.
This is entirely the case for analytics data, particularly when stats tie into locations. In text, any location feels as impactful and significant as any other. A city, a state, a country, a continent — each one is nothing more than an alphanumeric string. You need a hierarchy, a representation of how those locations relate to one another and what they actually mean.
This is why you need to visually map your locational data. For a small business, location is of immense importance — if you’re focusing on your local area, then you’ll want to confirm that you’re attracting traffic from the right places, and if you’re planning to expand, then you’ll want to see which areas are sensible to target next.
We require visuals for geographical logistics
Massive improvements in technology across the last 20 years have made it possible for businesses to operate exclusively online. This is abundantly clear when you look into the advent of websites being traded as assets that can be operated without any physical presence.
But even with the incredible opportunities of the digital world, it remains true that every business needs to factor in geographical logistics. Why? Because there’s always a physical component to a business, whether in shipping, distribution, or taxation. The last one is particular significant because of a ruling in 2018 earlier this year that empowered more US states to seek sales tax from online companies that sell to their citizens from other states.
By getting a top-down view of the geographical spread of its customers, a US business can devise prospective alterations to its distribution model that might save it time and money, and determine which states it might want to avoid selling in for fear of having tax issues. Though taxation is less relevant elsewhere in the world, logistics remain important. Could you reach such conclusions without data mapping? Yes — but not effectively.
We’re visual creatures, and if we have any hope of making effective use of large pools of analytics data, we need strong visualisation to help us parse metrics. If you’ve never tried visual data mapping, now’s the time! Check out this great list of relevant tools from Creative Bloq, and see if there’s something you can use.