Look at how marketers tell stories with compelling data visualizations

Storytelling is important for marketing, but how do you tell a story with data?

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Storytelling has always been a critically important skill for marketers. However, as content strategies have changed over time, it’s become increasingly challenging for marketers to tell clear and compelling stories that resonate with their target audience.

This is especially true when you look at the influx of data in the industry.

5 Tips for effective data storytelling

Almost every modern organization understands the value of collecting and analyzing data. With the incredible amount of attention data and analytics are getting, it’s tough to ignore. However, there’s one aspect even the most successful data-driven companies forget about: using data to tell meaningful stories.

The reason this is such a difficult concept to grasp is that data storytelling doesn’t fit into a little category. It requires both analytics and marketers — two very different groups of people — to join forces.

As a marketer, you need to overcome your fear of data and analytics and instead let this powerful information drive your storytelling efforts. Let’s take a look at a few tips and techniques for how you can make this happen.

1. Put the audience first

Storytelling — whether it involves data or not — must start with the audience in mind. While the content you produce may be designed to benefit the business, it won’t be successful unless it puts the audience first.

“Storytelling with data should always begin with stating of the purpose,” says Agata Kwapien of datapine, a leading provider of business intelligence tools. “What is the main takeaway from your data story? It’s clear that your purpose will be to motivate the audience to take a certain action. Therefore, instead of thinking of your business goals, try to envisage what your listeners are looking for.”

Putting the audience first requires you to know them and their desires. As a marketer, you’re likely familiar with customer profiles. If you don’t have specific profiles, now is the time to develop them. They will forever change the way you look at storytelling.

2. Use the right data

Now that you know exactly what your audience wants, you need to find data that will speak to them. While the process of identifying the audience’s needs and choosing data may seem interchangeable, it’s imperative that you follow this order.

“There is no shortage of large data floating around on the Internet, but fishing for stories in random numbers won't help you produce the best story,” communications expert Joel Kaplan tells businesses. “Instead, figure out the story you want to tell and then look for data that supports or challenges that story. The figures will be easier for you to interpret if you understand the data and it reflects your interests.”

Part of using the right data means vetting your sources. If you didn’t personally gather the data, then you must clarify who did and what methods they used. The purpose of telling stories with data is to increase the credibility of your content and validate your brand. Reputability here is crucial.

3. Carefully choose the right visualizations

When data is in the picture, you can’t simply craft written content and expect it to deliver maximum value. In order for your storytelling to resonate with the audience, there needs to be compelling visualizations. As such, choosing the right visualization is an important part of the process. Here are a few of the most common types:

  • 2D area. These visualizations tend to be geospatial, meaning they relate to the position of things on the earth’s surface. Cartograms, choropleths and dot distribution maps are some specific types.
  • Temporal. These are linear visualizations that have a definitive start and finish time. Temporal visualizations include things like connected scatter plots, time series and polar area diagrams.
  • Multidimensional. When there’s more than one dimension in play, multidimensional visualizations like pie charts, histograms and scatter plots are ideal.
  • Hierarchical. These visualizations consist of various orderings of group based on size. Examples include dendrograms, ring charts and tree diagrams.
  • Network categories. Finally, there are network data visualizations. These visualizations show how various sets are related to each other within a single network. Common types include matrix charts, node-link diagrams and alluvial diagrams.

As you can see, there are dozens of different options. The key is choosing the visualization that best tells your story and requires the least amount of interpretation. 

4. Ask for Feedback and Analysis

Before publishing your data visualization, it’s important that you get some feedback. Show your content to an independent source – ideally within your target audience – and ask for their opinion. They should be able to tell you exactly what the story is about and why it matters. If they can’t, then it’s a good indication you need to head back to the drawing board.

5. Publish and share

With your data story perfected and ready to go, it’s time to publish. The most important part of this process involves your dissemination strategy. Are you using the content as a paid resource, or is it going to be blasted out to as many people as possible? Which publishers will you use? Do you want your followers to share? These are all important questions that need specific answers.

Master the art of storytelling with data

In Stanford University Professor of Marketing Jennifer L. Aaker’s Persuasion and the Power of Story video, she says, “When data and stories are used together, they resonate with audiences both on an intellectual and emotional level.”

This is the power of storytelling with data. If you’ve yet to integrate data visualizations into your marketing efforts, now is the time to catch up with the rest of the industry. Audiences are becoming more sophisticated and the demand for compelling stories is at an all-time high.

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