Marketing Tactic For Business: Story-Driven Content Visualization

Why Data Storytelling Is Marketing Gold for Your Business?

Data, data, data—as marketers, we hear that word thrown around all the time. But data alone can’t improve your results; it’s what you do with that data that matters. Enter data storytelling. Through data storytelling, you can make better decisions, create effective content that connects with the right people, and improve your content marketing operation all around. Today, we’re diving into the power of data storytelling to show you how your brand can use it to transform your content strategy. 

Data is central to many business decisions and operations

Whether you’re communicating with an internal team or a customer, data can help you tell a compelling story that supports your position and highlights the value of your products or services. However, raw data can’t do the job on its own. You can’t simply give the audience a handful of spreadsheets with rows of numbers and hope that they’ll figure out your key message or take action. To get the point though and achieve your objectives, you need to present the information in a compelling way to engage your audience. This is where data-driven storytelling comes in to turn data into an effective, engaging, and convincing communication tool.

Storytelling is a comprehensive way of sharing information. It involves data visualization, which plays an important role. As the two are related, we asked marketers about their experiences with both for the report. Increasingly sophisticated tools and platforms will continue to provide us with innumerable data points, and it will fall on marketers to make sense of it all. Data storytelling will only grow as a key function of the modern marketing professional. This report provides a baseline for the data storytelling skills of marketers in different industries. 

How To Create Story-Driven Data Visualization In 5 Steps

1. Review Data Set

Before you can create any visualizations, you’ll need to look at your raw information first and explore the direction you can take with your story. What’s at stake for people who don’t do X (the solution)? What are some ways that you could make things better if we solved the problem together – architecting solutions based on data insights from validated user stories

• Is there anything about my data that surprises me?
• Is there anything in my data that suggests any trends or themes?
• Is there anything in my data that stands out as a key character or player? 
• Are there any recurring themes?
• Are there any key characters or players in this data?

Answering those questions will help you identify the most important key points in your data—and story.

2. Develop Your Narrative

The story you tell yourself about your business and its future is just as important to its success. Your positive mindset will help drive motivation, too, so make sure not only do know what’s going on. Oftentimes, this involves tying your plot points and the characters or players you’ve identified in Step 1 with a story arc. Alternatively, you can also come up with a creative story that narrates your plot points, in a way that resonates and appeals to your target audience. 

3. Build Your Outline

Once you have your plot points and story, the next step is to develop a narrative framework. This process can vary depending on the format you choose to communicate your story, but here’s a general approach you can use as a starting point:

• Outline your key sections
• Craft copy for each section to frame your data and develop your story
• Determine the most important data points you want to highlight
• Develop the introductory copy that sets the stage for your story

As you work through your narrative framework, you’ll need to decide which data points and information will go on your visual, including your base and second layer of content, if you have any. The secondary layer of content requires viewers to either click or hover over certain visuals to see additional information.

4. Select Data Visualization Formats

Depending on the data you want to present, you’ll want to choose the visualization formats that can best communicate and illustrate your story. Here are four of the most common data relationship types you can consider to convey your data:

• Nominal comparison compares sets of data in no particular order.
• Part-to-whole looks at how individual data points relate to each other as part of the whole data set.
• Ranking organizes and orders your data points using a specific measurement.
• Time series, as the name suggests, categorizes data points by time.

You’ll need to first identify the type of relationship your data points deal with, and this will help you determine the most effective data visualization formats you can use to convey your story. These can range everything from bar charts to line charts, pie charts, stacked bar charts, and area charts.

5. Create Your Visual   

Now that you have developed your content and data points, narrative framework and visualization formats, it’s time to actually create the visual! You’ll want to work closely with your designers to make sure that, from creative concept to execution, you can tell your story in an engaging and interesting way.

Purpose Of Data Storytelling 

The use of data storytelling is prevalent in all industries, for internal and external purposes. What’s interesting is how the purpose of data storytelling changes between industries.

• Data visualization expertise is a necessary marketing skill, and only growing in importance.
• A majority of data-driven marketing content is seen as effective but rarely branded.
• The range of software for data visualizations is limited, and many marketers rely on using multiple solutions to compensate.
• In some industries, data storytelling is used solely for internal reporting and business insights. It drives high-level decision-making, and tactics.
• In other industries, data storytelling is a key factor in the acquisition and sales funnels and is only moderately important for internal reporting.
• There are significant differences in the budgets that support data visualization and storytelling when comparing industries. The average data visualization budget may surprise you.

Data Visualization Expertise is a Core Marketing Skill

We learned that a majority of marketers create data visualizations on a regular basis. A majority of marketers also felt confident in their ability to tell stories through data and considered themselves skilled. However, very few had any formal background in data analytics and reporting. How often do you create data visualizations for your marketing?

To Conclude

Many factors are involved in the decision to produce data visualizations at an organization. The importance placed on data visualization by leadership; technical skills available to visualize data; the costs of software needed to visualize data; and the cost for outsourcing design work (when in-house talent is not an option) are just a few factors. 

There are cases where data visualization is a major business driver. It is a way to communicate marketing impact, share insights for growth opportunities, support the sales team, learn about your customers, and more. 

Using data visuals in marketing work is common and expected of marketers today. It’s no surprise that a majority of respondents stated they were confident in their ability to use data in their marketing.