It’s no secret: content marketers are scared of data. According to our study last year, 38% of content marketers rarely use data for their content strategy.
It’s also no secret that content marketers need data: data-driven content proves that content marketers have the stats to back up their claims.
But our content can’t just be a bunch of data points strung together. Data has to show and tell. We have to tell a story with it—make it relevant and engaging to our readers.
Data is best when it tells a story.
Of course, research shows visual deliverables help reach visual learners. And that social media audiences are more likely to engage with images than with written articles. But how do we make sure that visual content can tell a story the same way a written piece can?
Adam Singer of Google has a few ideas. During our C3 conference, he offered his go-to steps for creating data visualizations that are (1) relevant to your audience and (2) communicate data clearly.
Here’s how to let your data speak for itself:
1. Treat your data visualizations like all your other content.
You might be tempted to think of data visualizations as something you can create from previously-written content, but Singer suggests building data visualizations from the ground, up.
Data visualizations are a different medium for providing relevant content. As such, simply transposing written content into visual content doesn’t guarantee it’ll maintain its relevance or effectiveness.
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To create new content destined for a visual format, Singer recommended the following process for generating data visualizations (which you’ll recognize as similar to most content creation processes):
- Define your audience
- Create a hypothesis
- Sketch the visualization
- Get the data
- Explore the data
- Tell the story
2. Less is more.
Henry Thoreau aspired to simplicity as an ideal way to live one’s life. From what Adam Singer said about data visualizations, I think he’d agree with Thoreau (at least as far as digital marketing goes). They’re both smart guys.
As a visual medium, data visualizations must communicate an idea in an immediate way. To accommodate your audience and make your visualization “click” immediately, you need to keep things simple.
The lesson here? Trim the fat from your visualizations. Leave only what is required to communicate your point. Consider the following images, which Singer used to illustrate his point:
The first image is cluttered, without a clear takeaway. In the image to the left, a clear description, limited callouts and less extraneous information allow you to get your point across concisely and ensure your audience doesn’t get lost in the visual.
3. Tell your audience what matters.
In the same vein as keeping things simple, Singer says you’ll want to be clear about what you want your readers to take away from your data visualizations. Don’t leave your readers to guess at what you want them to notice.
Best way to accomplish this? Call out percent changes over time (rather than the actual values). Doing so emphasizes the meaning behind the data rather than just raw numbers. Again, check out how the images below reflect this point:
On the graph to the right, the story behind the image is more focused and the audience knows that a rise in internet news as a source is the stat they should takeaway.
4. Don’t lie.
This one goes without saying, right?
Sure, as marketers, we’re all familiar with spin. But you can’t paint a picture that isn’t consistent with the actual story behind the data.
We’ve all tried to play with the scale on a graph. Don’t do it.
As Singer points out: you WILL be found out. Your customers are out there and they don’t take kindly to truth-stretchers.
5. Be creative and have fun!
The lessons so far have focused on outlining the foundations of what makes an effective data visualization. But on these foundations, you can build whatever visualization that best speaks to your audience. You can get creative with these visualizations. You can have fun with them.
Novel ways of communicating your data not only help get your point across, but also help to engage your readers, develop rapport, and build brand affinity.
Straight-forward correlations hit home:
Fun seasonality from Facebook data:
Integrating analog visualizations can illustrate your point:
And here’s a bonus tip for you:
Use data visualizations in your internal processes.
While the tips above focus mainly on presenting data to your customers, they can also be applied to your internal reporting processes, too.
Do you send reports regularly to your stakeholders? As part of your routine, use the same data visualization to communicate your data. It’ll help your stakeholders quickly and effectively understand what you’re reporting if they see the same visualization every week, month, or quarter.
Whether your using visuals internally or sharing them with the outside world, the story remains the same. And, now that you know the path ahead of you, go forth and make data-driven masterpieces.