“By 2025, data stories will be the most widespread way of consuming analytics.”
That prediction from Gartner a few years ago was geared toward CFOs, but it applies perfectly to another group that traffics in 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 insights from finance. Despite modern analytics and business intelligence (A&BI) platforms, insights often lack context and aren’t easily understood or acted upon by the majority of users.”
Replace “finance” with “marketing,” and the challenge remains true. While marketers can access vast amounts of data and have numerous tools to analyze and present them, non-marketers in the company struggle to understand what the data means.
David Ciommo, a decision intelligence leader and data storytelling lead at Humana, discusses this conundrum in his presentation at the Marketing Analytics & Data Science (MADS) conference. “I’m surrounded all day long by people who care about data, but yet the audience, the people consuming the data, are the people who are making decisions,” he says.
To help, David explains how to bridge that gap.
How data can make a difference
Working with data, David says, usually follows this six-step process:
- Define the objective.
- Gather the data.
- Clean the data.
- Conductfield-level analysis.
- Consolidate data.
- Analyze data and glean business insights.
However, David says too many marketers don’t spend enough time on Step 6. Data alone doesn’t convince leadership to approve your marketing budget. You must use the data to get insights and action. You must use the data to tell a good story.
Data is cold, factual, and objective. Stories are warm, emotional, and subjective. One study found that after a presentation, only 5% of people could recall a statistic. However, 63% could remember a story from it.
“Storytelling, to some degree, creates and affects our brains in ways that we are completely unaware of, yet we like it. When you walk out of that movie or that play, and you talk about it for days, what’s happening is that the chemistry of your brain, including the dopamine, is being affected,” David says.
The mission for marketers is clear: To drive more impact in your organization, you must use data as the basis for a great story so more people will remember it. In other words, you need to 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 can be used to put data insights into context for and inspire actions from your audience.”
Using a business intelligence tool to create a dashboard with charts doesn’t make you a data storyteller. “All you get is data visualization. You don’t get the story,” David says.
Data stories encompass four elements:
- Visual design that incorporates imagery and other design elements and principles
- Context that indicates you understand the audience, have a clear purpose and goal, and use feedback loops
- Data from quality sources accurately analyzed and represented
- Narrative that encompasses the message, has a beginning, middle, and end, and includes calls to action
David shares one of his favorite sayings, “Every single data insight has to be meaningful, valuable, and actionable.”
To achieve that, ask yourself these questions when creating a data story:
- Does it engage the target audience?
- Will it remove doubt and clarify decisions?
- Does it reveal truths and deliver meaningful insights?
- Will it provide actionable opportunities?
If the answer is no, go back and rethink your data story idea.
How to put together a good data story
To tell effective data stories, David follows this sequence — story, data, visualization, and tool.
You may think that seems counterintuitive. In a data story, data should be the first step, and the story should be last. Not so, says David.
He explains, “Many departments within a company often depend on data to understand what is happening. Consequently, when teams reach the reporting or dashboarding phase, the final product tends to focus heavily on displaying data rather than telling a compelling story. This approach can diminish the impact of insights that the data can provide.”
The story-first framework prevents the overcomplicated use of data with no actionable insights. You begin by asking a series of questions to understand the business priority and perspective before diving into the data.
“Ask critical questions about intent and key insights you aim to uncover. By outlining the specific answers you’re going after, you can minimize the volume of data presented and avoid overcomplicating the analysis, ultimately saving time and money,” David says. “It allows us to organize our thoughts in advance, ensuring we stay focused and convey our points in the most efficient and clear manner 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, the marketing team doesn’t compile all the available data in a dashboard, and it works with the sales team to clarify its goals for insights.
They conclude that the goal is to introduce the product into existing and new regions. They know the current products have performed well in neighboring regions and believe the new product will succeed elsewhere. That focus helps identify the core story and allows it to focus on a need not provided elsewhere.
Next, the marketers can identify the data to analyze to support the story and how to present it in a report or dashboard. Then, they can work with the data to extract relevant insights.
After the data processing, the work turns to visualizing it in a way that clearly communicates the message of those insights. Data visualizations are not appropriate for every story — not everything needs a line, bar, or pie chart.
In data storytelling, the goal is to select visuals that simplify the insights. For instance, exploring opportunities in a new market might lend itself to a color-coded geographical map.
The visualization tools depend on your goals and their capabilities. For example, some business intelligence platforms may not be able to show real-time data. If that was the case, the data story wouldn’t incorporate real-time data.
Follow these data visualization tips
Among David’s tips for crafting a quality data story that will provide value and drive action:
- Identify the right data for the story.
- Simplify the story with fewer, more meaningful visuals.
- Use color to help tell the story.
- Aggregate less important information.
- Calibrate the visual to the message and the needs, not the wants.
- Include only insights that will drive viewers to make decisions.
- Don’t ignore or play into cognitive bias.
David also shares a couple of things to avoid.
The first is to stop using tables because consuming data in that format requires the viewer to spend too much time to gain insights. “We process visuals faster than text. When you take that exact same data, and you put it in a visual, the story comes across so quickly,” David says.
Look at this example, which includes a table on the left and a visualization on the right about global COVID-19 infection rates. The world map works well for those who want a quick understanding. The table exists for a segment of the audience who may want to do further analysis.
The second tip of what not to do is adding pizzazz for the sake of pizzazz, or as David calls it, “chart junk.”
In this pie chart about Brexit, the data is simple: 47% say yes, 43% say no, and 10% don’t know. However, the presentation gets in the way of the data. The British flag is the image on the pie, which makes it hard to see the data slices, and the graphic uses two shades of blue, red, white, black, and yellow. “The drop shadows, gradient blends, textures, etc. confuse and muddy the water. It makes the story hard to read,” David says.
Are you ready to tell stories with data?
You are awash in numbers: web analytics, social media, video, paid search, lead generation, email marketing, and more. This sea of data leads to oceans of spreadsheets, reports, charts, and dashboards. You allocate precious time to generating and managing these reports each week, but in the end, is it serving the marketing team? Is the broader organization even looking at them?
Instead, build stories from your data. As a refresher, ensure that each story:
- Engages the targeted audience
- Removes doubt and clarifies decisions
- Reveals truths and delivers meaningful insights
- Provides actionable opportunities
Maybe you like the story David told. Now, it’s your turn to tell an equally good story with your data and have a bigger impact within your organization.
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Cover image by Joseph Kalinowski/Content Marketing Institute