Operationalising big data is a major challenge to overcome for the marketing industry. While machine learning helps you solve one piece of this puzzle, data visualisation is another step towards ‘making more sense’ of the information at your disposal. In this quick guide, we’ll show you how to use it for better decision making.
While machines prefer to crunch numbers, us humans are wired to process visuals. In fact, 30% of the brain is devoted to visual processing alone, while only 3% is allocated to hearing. Turning the numbers we have into a visual asset helps us spot emerging trends, repeating patterns and ultimately discover new correlations between different facts.
What data visualisation can do for marketing
Most likely you have already used some conventional data visualisation methods – the beloved and ever-present pie chart or a bar chart are a couple of examples. They are great to visualise a quick stat or two but when you are dealing with larger amounts of scattered data, you need a bolder solution.
Enter data visualisation – an elegant way to reconcile data in an easy-to-grasp manner. Here are just a few examples of how you can benefit from it.
Full-picture at one glance
When working with traditional analytics tools, you are constantly switching between tabs and columns. You focus on the seemingly important metrics while ignoring others you don’t fancy that much. At some points, all the numbers just blur into one and you fail to decipher the full story they are trying to tell you.
Data visualisation helps you combat analysis fatigue and reduces the number of steps you have to take in order to obtain quantitative insights. It will not only help you gain more visibility in your campaigns but can also lead to some really powerful business insights.
Related reading: Check out this example in which data visualisation helped us advise one of our customers where they should set up their next franchise: Why analytics is nothing without data visualisation
Let’s face it – our bandwidth for text processing is limited. As we get exposed to more and more information, we retain less and less of it. We don’t always have the time, or brainpower to read through something longer than a 140-character update.
However, the brain feels less pressure to process an image. In fact, it needs 13 milliseconds to render an entire image seen by the eyes. Text, though, requires more comprehension. Using visualisations instead of words can help marketers communicate better on multiple levels:
On-page optimisation suggestions can be visualised, instead of verbalised. In this case, the client can review what should be changed, why and what results those changes will yield.
Data visualisation can help you uncover new marketing vectors and steer you towards taking data-backed decisions, rather than following a ‘hunch’. Different team members, working on different tasks, often lack a comprehensive picture of the entire campaign. Data visualisation enables centralised analysis so that everyone on your team relies on a single source of truth and can make on-the-spot decisions without consulting with their superiors.
Researchers have proved that people following directions featuring both text and images do 323% better than peers who received plain text guidance. You can ‘patch’ the existing bottlenecks in your customer journey by offering visual prompts and information, instead of the often-ignored 100-page user manual.
Finally, data visualisation is the answer to routine and repetitive chores. Instead of copy-pasting and combining data from multiple analytics tools, you can connect all the sources to your tool and have the system organise everything for you. Your reports can be updated in real-time and instantly shared with anyone.
You no longer guess whether your data is accurate enough. You are empowered to see what’s working and what’s not. That is, of course, as long as you avoid some frequent mistakes made with data.
The common data visualisation myths
All data should be visualised
Not all data at your disposal needs visualisation to unveil the key insights. In some cases, machine learning algorithms alone can guide you towards the right action.
Data visualisation will always lead to certainty
The outcome’s accuracy largely depends on the quality of data you plan to use and the visualisation methods you deploy. As long as humans are involved in the process, the results may be biased. Data visualisation alone cannot replace critical thinking altogether.
Only ‘good’ data deserves visualisation
On the contrary, exhibiting different types of data can help you discover exactly what’s wrong with it, and highlight some interesting trends.
By strategically leveraging data visualisation, marketers can develop a better comprehension of historical data and the relationship and relativity of the key entities within it, and use these insights to create high-performing campaigns.