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“By 2025, data stories will be the most common way to use analytics.”
This prediction from Gartner a few years ago was aimed at CFOs, but it applies perfectly to another group that deals with data: marketers.
Gartner even identified the rise of dynamic storytelling as one of four data and analytics trends:
“Leaders across organizations continue to struggle to interpret financial insights. Despite modern analytics and business intelligence (A&BI) platforms, insights often lack context and are not easy for the majority of users to understand or act on.”
Replace “finance” with “marketing,” and the challenge remains. While marketers have access to vast amounts of data and numerous tools to analyze and present it, non-marketing professionals in the organization struggle to understand the meaning of the data.
David Ciommo, a leading expert in decision intelligence and data storytelling at Humana, discusses this dilemma in his presentation at the Marketing Analytics & Data Science (MADS) conference. “I'm surrounded by people all day who are interested in data, but the audience, the people who are using the data, are the people who are making the decisions,” he says.
To help you, David explains how to close this gap.
How data can make a difference
Working with data, David says, typically follows this six-step process:
- Define the goal.
- Collect the data.
- Clean up the data.
- Perform field level analysis.
- Consolidate data.
- Analyze data and gain business insights.
However, David says too many marketers don't spend enough time on step 6. Data alone won't convince executives to approve your marketing budget. You have to use the data to gain insights and take action. You have to use the data to tell a good story.
Data is cold, factual and objective. Stories are warm, emotional and subjective. One study found that only 5% of people could remember a statistic after a presentation. However, 63% could remember a story from it.
“Storytelling shapes and influences our brains to some extent in ways that we are completely unaware of, but that we enjoy nonetheless. When you come out of the cinema or a play and talk about it for days, your brain chemistry, including dopamine, is affected,” says David.
The mission for marketers is clear: To increase your company's impact, you must use data as the basis for a great story so more people will remember it. In other words, you must become data storytellers.
What makes good data storytelling
David says, “Data storytelling is the ability to effectively communicate insights from a dataset using narratives and visualizations. It allows you to put data insights into context and inspire your audience to take action.”
Creating a dashboard with charts using a business intelligence tool doesn't make you a data storyteller. “All you get is a data visualization. You don't understand the story,” says David.
Data stories include four elements:
- Visual design that incorporates images and other design elements and principles
- context This shows that you understand the audience, have a clear purpose and goal, and use feedback loops
- Data from high-quality sources that are carefully analyzed and presented
- narrative that encompasses the message, has a beginning, a middle and an end and contains calls to action
David shares one of his favorite sayings: “Every single data insight must be meaningful, valuable, and actionable.”
To achieve this, ask yourself these questions when creating a data story:
- Does it appeal to the target audience?
- Will it eliminate doubts and clarify decisions?
- Does it reveal truths and provide meaningful insights?
- Does it offer actionable opportunities?
If the answer is no, go back and rethink your data story idea.
How to create a good data story
To tell powerful data stories, David follows this order: story, data, visualization and tool.
This may seem contradictory. In a data story, the data should be the first step and the story the last. That's not the case, says David.
He explains: “Many departments within an organization often rely on data to understand what is happening. As a result, when teams reach the reporting or dashboarding phase, the end product is more focused on displaying data rather than telling a compelling story. This approach can reduce the impact of the insights that the data can provide.”
The story-first framework prevents over-complicated use of data without actionable insights. You start by asking a series of questions to understand the business priority and perspective before diving into the data.
“Ask critical questions about the intent and key insights you want to gain. By outlining the specific answers you're looking for, you can minimize the amount of data presented and avoid overcomplicated analysis. This ultimately saves time and money,” says David. “It helps us organize our thoughts in advance and ensure we stay focused and get our points across as efficiently and clearly as possible.”
Example of data storytelling
David walks through a fictional scenario so you can see the story-first framework in action:
A company's sales team wants to understand the market for a new product. To help with this, the marketing team doesn't just compile all available data into a dashboard, but works with the sales team to clarify the goals for the insights.
They conclude that the goal is to launch the product in existing and new regions. They know that the current products have been well received in neighboring regions and believe the new product will be successful elsewhere. This focus helps identify the core story and focus on a need that is not being met elsewhere.
Next, marketers can identify the data they need to analyze to support the story and determine how to present it in a report or dashboard. They can then work with the data to uncover relevant insights.
After processing the data, it's all about visualizing the data in a way that clearly communicates the message of those insights. Data visualizations aren't suitable for every story – not everything needs a line, bar or pie chart.
The goal of data storytelling is to select visual elements that simplify insights. For example, exploring opportunities in a new market might be a good idea to use a color-coded geographic map.
The visualization tools depend on your goals and their capabilities. For example, some business intelligence platforms may not be able to display real-time data. In this case, the data story would not contain real-time data.
Follow these data visualization tips
David’s tips for creating a high-quality data story that adds value and inspires action:
- Identify the right data for the story.
- Simplify the story with fewer but more meaningful images.
- Use color to tell the story.
- Summarize less important information.
- Adapt the imagery to the message and needs, not the wants.
- Only include insights that will help the viewer make decisions.
- Do not ignore or exploit cognitive biases.
David also reveals a few things to avoid.
First, we should stop using tables, because when we process data in that format, it takes too long for the viewer to gain insight. “We process visual content faster than text. If you take the exact same data and put it in an image, the story comes across much faster,” says David.
Check out this example, which includes a table on the left and a visualization of global COVID-19 infection rates on the right. The world map works well for those who want a quick overview, while the table serves a portion of the audience that may want to do further analysis.
The second tip to avoid is adding something just for the sake of it, or as David calls it, “chart garbage.”
In this Brexit pie chart, the data is simple: 47% say yes, 43% say no, and 10% don't know. But the presentation gets in the way of the data. The British flag is the image on the circle, making the data segments hard to see, and the graphic uses two shades of blue, red, white, black, and yellow. “The drop shadows, gradients, textures, etc. confuse and muddy the waters. It makes the story hard to read,” says David.
Are you ready to tell stories with data?
You're overwhelmed by numbers: web analytics, social media, video, paid search, lead generation, email marketing, and more. This sea of data results in tons of tables, reports, charts, and dashboards. You invest valuable time every week in creating and managing these reports, but does it ultimately benefit the marketing team? Are they even read by the entire organization?
Instead, build stories from your data. As a refresher, make sure each story:
- Involves the target group
- Eliminates doubts and clarifies decisions
- Reveals truths and delivers meaningful insights
- Offers actionable opportunities
You may like the story David told. Now it's your turn to use your data to tell an equally good story and create a bigger impact in your organization.
Let the analysts and data scientists in your organization know about the Marketing Analytics & Data Science conference, running concurrently with Content Marketing World. Register today and save $100 with promo code BLOG100.
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Cover photo by Joseph Kalinowski/Content Marketing Institute
Create your very own Auto Publish News/Blog Site and Earn Passive Income in Just 4 Easy Steps
