More data has been generated in the past two years alone than in the entire history of the human race up to this point. This flood of information has a name, “big data,” and, like it or not, it’s already influencing every aspect of your business – production, sales, and, most interesting to us, marketing.
With all of this information flying around – and mountains more being generated every single day – it’s never been more important to truly understand how to present, read, and share data in an intuitive, effective way.
Effective analysis – the sort that leads to valuable insights and actionable goals – depends not just on having accurate data, but on a clean, effective presentation of those numbers and trends. Our friends at Hubspot put it well:
“One of the struggles that slows down… reporting and analysis is understanding what type of chart to use - and why. That's because choosing the wrong type of chart or simply defaulting to the most common type of visualization could cause confusion with the viewer or lead to mistaken data interpretation.”
In today’s marketplace, the power of your brand to educate, inform, and convert customers is directly tied to your ability to represent data in a clear, succinct, and meaningful way. But how do you know the right way to visualize and communicate your stats? It all comes down what type of information you’re presenting, and your goal in presenting it.
To find the right fit for your content, look at your data and consider your intent. Are you trying to…
If your goal is to show how numbers got from point A to point B over a specific period (or periods), then you’ll want to use a chart that conveys growth and decay in clear trend lines. Consider a line graph or column graph if you’re looking at the trends for just one data set over time; for multiple sets, you may want to use a bar graph or dual-axis line graph, which allow you to plot multiple points and metrics at once.
Looking for how A stacks up to B (or C or D or E)? While it may be tempting to fill up a spreadsheet and leave it at that, you’ll really want to employ a chart or graph that makes data comparison visual. Try a bar/column graph for two or more datasets, a scatter plot for a diffuse array of data, and a pie or circle chart if you’re comparing multiple parts of one whole.
…Find Commonalities or Outliers?
Looking to highlight the one data point that doesn’t fit with the rest, or, conversely, quickly showcase where the average or median of your data is centered? Consider a visualization that visually points to these numbers: Scatter plots or bubble charts are great for identifying clusters and outliers, as are area charts, which allow users to quickly glean both individual and overall information.
…Highlight Parts of a Whole?
Say you’re trying to compare the sales numbers of a ten-member team, or the allocation of a fixed budget. In both of these cases, you’re gauging the relationships between multiple parts of one whole. To represent allocation and composition, use a pie or circle chart, a stacked bar chart, or a “waterfall” chart, which breaks down one initial number into more specific positive or negative values
Data isn’t just numbers; it’s factors and variables and change. How does value A effect dataset B? What does factor C do to the distribution of dataset D? To represent positive, neutral, or negative effects, you need to be able to compare multiple datasets at once. Consider a line graph, scatter plot, or bubble chart.
Looking for visual content experts to help you break down your big data into beautiful, shareable graphics and multimedia? Look no further! Drop Geek a line to get started on your digital future today.