Breaking news: in publishing, we deal with large amounts of data.
We work with sales data, consumer data, and social data, and somehow we want to find a way to make all of those data sets work together to tell us the story of what's going on in our own companies and across the industry. It can be intimidating to look at huge Excel spreadsheets and see walls of numbers, but by turning those spreadsheets into images (like graphs, word clouds, and other types of visual representation) we can get a better picture of what the data is telling us, understand difficult concepts, and spot trends and correlations.
At BookNet, we use data visualization for two main purposes:
- Our prime directive has, and always will be, to display data for our partners in the book industry in a way that can be easily understood and analyzed. In our research reports, both free and paid, as well as in blog posts and our infographics, we present data visually so readers who may not be used to consuming a lot of data can easily understand all that important information.
- We also use data visualization as a content marketing tool. The infographics we publish on our site are cute, colourful, and display bite-sized amounts of information that our audiences want to see in the most efficient and pleasing way possible. And a great bonus for us is that their popularity also generates a lot of traffic to our site, which can in turn lead to more users, clients, and partners for our services.
Why am I letting you in on this secret? Because, marketing teams, you can do it too! While "data visualization" may sound like the perfect way to scare away readers rather than attract them, surprisingly, it's super effective.
So how do you do it? How do you take whatever the heck is going on in that spreadsheet of doom and disseminate it in a fun and digestible way? Here are some of our most coveted visualization secrets:
Prepare your data
Messy data can happen in a myriad of ways: compiling multiple data sources into one document; exporting spreadsheets from one program to another; or even just the way the data can appear in default Excel settings.
On a grand scale, you want to make sure that the data streams you're merging are formatted consistently. If they're coming from multiple sources, they can arrive in different formats. It's important to format the identifiers attached to key data points consistently when merging data.
On a smaller scale, sometimes spreadsheets are just messy. Big numbers like ISBNs can turn into weird exponents; columns and rows can just generally be hard to read; and data can wander into the wrong place occasionally. Some general Excel clean up that may have to be done with your average file could include (but certainly isn't limited to): making sure dates are formatted correctly; adjusting row height and column widths; keeping decimal places consistent for all numbers and percentages; wrapping text; and formatting headers.
Figure out what you're looking at
One of the most difficult parts of visualizing data is seeing the story in the numbers. If it's your job to tell that visual story, you need to know how to identify the information that's going to display the narrative best and how to pull that from your data. This is where things like pivot tables are your friend. (I know, when I was in school I hated pivot tables, but they are incredibly useful for taking a large data set and tweaking it to show the different ways your data points are interacting with each other. eBOUND has a good beginner guide to pivot tables to help with this.)
Sometimes it helps to sift through all of your data sets and figure out which data can be easily grouped, and which information can be drilled down into more detail. Once you start to put your data in order, your narrative can begin to come together. Before I lay out an infographic, I use this strategy to sort through all the data presented to me by the awesome BookNet team. Then I can pull out the data points that are relevant to the story I want to tell, be it what the Canadian book market looked like in 2015 or what kind of cookies are most popular with the office, and organize those points as if I were writing a blog post: with a beginning, middle, and conclusion. Storyboarding can be very helpful with this process.
Our data sets are often so large that a lot of the information needs to be organized into multiple reports or graphics. In cases like that, it's helpful to identify a target audience and an end goal for a particular visualization. Figure out which additional information enhances your data and which distracts from it. Once your data is organized, you can make it work for you.
Different kinds of charts and representation lend themselves better to different types of data. Choose the one that will display your data in the most comprehensible way possible while keeping in mind what you're trying to accomplish. For example, you may want to:
- compare value sets;
- show the composition of a whole;
- understand the distribution of your data within a range of values;
- analyze trends;
- show how your variables affect each other; or,
- display a timeline or roadmap.
We recommend using this handy flow chart (haha) as a jumping-off point in making that decision:
But feel free to think outside the preset options in Excel—your imagination is the limit and sometimes an outside-the-box representation can cause a much bigger impact. We've used stacks of books as percentage gauges, characters from Star Trek to represent population, and a whole whack of other things outside the recommended charting guidelines. You can use hand-drawn elements, heat maps, actual maps, text... It helps to have a good understanding of the basics of visual design and a grasp of typographic hierarchy as well, because sometimes you don't even need charts; some creative typography and a well-placed image can sometimes be all you need.
When you have an idea of what you'd like to do, there are lots of helpful tools for creating these visuals. Excel has some excellent starter charts built in, and if you're handy with Adobe Photoshop or Illustrator you can create your own. If you aren't so handy with those, there are free online tools that specialize in data visualization like Piktochart and Canva.
After all the hard work you've put in, you'll want to make sure your audience can easily follow the story you've laid out for them or else it's all for nothing. While your data representation might make perfect sense to you, it doesn't hurt to test out your design on a focus group, be it a professional one or some friends you've rounded up in the office, and record their feedback. They may notice something you missed since you've been staring at the design for so long.
It's also a good idea to consider customizing any ready-made charts you've used. Do they need a legend to be understood? Do you need to label the different axis or remove labels and grid lines? The cleaner your charts look at the end of the day, the better.
If you need more inspiration for presenting your data in a visually pleasing and easy-to-understand way, or you're curious about more extensive tools and techniques (or just want to nerd out about some charts), you can check out these blogs: Flowing Data and Storytelling with Data. And, of course, keep an eye on our Pinterest board for the latest BookNet infographic.