Visualizing Data: A Guide for BeginnersMarketing
October 18, 2017
Visualizing Data: A Guide for Beginners
At Storyblocks, we love data. From pulling the numbers and crunching them to visualizing and sharing the results, we cannot get enough. Data is wonderful and can help us get to the bottom of tests and results, but sometimes even total data nerds find it difficult to determine the best way to visualize our data for others to consume. For instance, how can you share your 25 data points about coffee without writing a text-heavy blog post? Is it best to share a slide presentation or an infographic?
Tips for Visualizing Data
Keep It Simple
One of the first things you need to do when determining how to best visualize your data is to figure out which metric or metrics you want to focus on. Too often, we think that we need to report out on every single data point that we’re tracking when only one or two are the most important. Consider your audience and choose the metrics that you think are the most relevant to them and their job. If you’re not sure which ones they want to see, then ask. Even if you do need to share every metric, keep things simple by simplifying visually and focusing on only one metric for each graph.
Label Your Data Clearly
Make sure that not only is each of your axes labeled, but your title is informative. To eliminate the need for a textbox explaining what’s going on in your graph, make the title the description. For example, the graph below might typically be titled “Iced Coffee Sales in the Northeast.” While it’s fairly easy to also see that iced coffee sales have decreased in October, a more descriptive title can make your data easier to interpret. If you go with the title “Iced Coffee Sales Have Decreased by 50% in October,” then without doing any math or hovering over your graph, your audience will understand the point you are trying to make, and they’ll be happy that you saved them the time.
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Tools for Visualizing Data
There are plenty of tools out there for visualizing data, but for now, we want to go over two of the basic ways for beginners to visualize data.
Data Visualization with Google Data Studio
You can easily pull a lot of data into Google Data Studio. From Google Analytics to Google Sheets, the options are endless. One of our favorite ways to use Data Studio here at Storyblocks is to pull information about our blog—how much web traffic are we receiving from search engines versus social media, and which blog posts are people reading the most? Rather than going into Google Analytics every time we want to find this information, we set up a Google Data Studio report to pull the information for us, so all we have to do is check the report. These reports are easily shared, and you can give editing access to anyone on your team (just like a Google Doc). They are also much more visually pleasing and customizable than Google Analytics.
Why We Love Data Studio
- It’s easy to pull data from sources we already use
- Filters allow us to look at individual folders and pages on our site
- You can customize everything including the colors to keep your reports on brand
- It’s great for beginners
A Couple of Complaints
- You can only use one data source for a graph
- It’s lacking integration with some big external reporting sources
Infographic Templates for Simple Data Visualization
Of course, not all data can be neatly packed into a simple graph. Earlier we used the example of visualizing 25 data points about coffee—but what should you do if instead of 25 data points, you have 25 quick facts? For instance, “63% of adults in the US drink coffee.” Infographics will help you display these facts in a way that’s easy to visually comprehend.
Infographics allow designers and marketers to showcase lots of information in a compact and visually pleasing way. You can push one line facts, pie charts, and other infographic vectors in to organize and display your data. Most of us have been caught in the trap of an infographic because they really do work. Here is just one of our favorite infographic templates. See how easily it creates a hierarchy of information, packing what would otherwise be an overwhelming amount of data into digestible and interesting chunks.