So, you have done it. Your trackers are in place, your data is clean, modeled and easily available. All the information you need is at your fingertips. But what about the business side of your company?
What about your colleagues in different departments and teams, who may be completely unaware of where this data comes from and what it means? Ideally they would be making data driven decisions as well and have a solid understanding of where the numbers you’re producing are coming from. This is where good data storytelling comes in.
What is data storytelling?
Storytelling is one of the oldest forms of education. Humans struggle to process too much complex information, but are great at remembering and retelling stories.
Data storytelling is the practice of transforming data into easily understandable insights. You can have the most advanced technologies at your disposal, but those won’t provide any value until you can tell the story behind the numbers you’re producing.
Having worked with many online retailers, especially those coming from a more traditional brick and mortar background, I can tell you that most raw numbers don’t mean anything to a lot of people. Things like conversion rates and marketing attribution are hard to do in a regular store and are even harder to grasp as a concept online for those unfamiliar with online spaces. But the stories behind the numbers are absolutely universal.
For example, a 30% increase in conversion rates might sound good, but on its own, it’s a useless number. Perhaps the number of purchases went down rapidly and only your most loyal customers kept ordering, or maybe you had a very successful marketing attribution project which increased your conversion rate beyond the 15% you had hoped for. Both stories could come from the same number, but they provide very different insights depending on who you’re telling them to.
Storytelling is powerful. Even someone who has only worked in a physical store will recognize the effect of customers intrigued by a new display or good demo, as well as the strength of word-of-mouth advertising, whether that is done through conversation or a social media share.
So you can understand that this practice extends to all forms of showing and explaining data. Whether you are presenting at a meeting, building dashboards or writing guides. Whatever the form information is presented in, it will always benefit from building a narrative to take the consumer on a journey from data to business outcomes.
Why should I do it?
Storytelling is one of the oldest forms of education. Humans struggle to process too much complex information, but are great at remembering and retelling stories. And this is exactly what you want to do with your data. You want people to remember the important information, act on it and draw the right conclusions that will help them in their roles. The business critical choices people made need to be rooted in the data you provide them with. And this can only happen if they remember and understand what they have been told.
Beyond that, stories can be retold. New coworkers, other teams and customers can all be provided with this information by anyone who can retell the story. And if that happens, it can actually relieve the data team from repetitive work, so they can focus on more exciting things like enhancing the data or driving powerful data use cases.
Lastly, providing data as a story means that data literacy is no longer expected or required from every team. Teams which are affected by the data, but not directly involved in collecting or consuming it can still benefit from a strong narrative. This way they do not have to invest in additional resources to create understanding, but they can focus on their everyday work.
How do I tell a good (data) story?
Creating a good data story relies on three key aspects:
- Know your audience
- Build a compelling narrative
- Make use of clear visuals
As with any presentation, knowing your audience is the best way to communicate effectively. If you’re telling your story to a board of directors it will look totally different from telling it to a team of customer service reps, even if both stories rely on the same data set. So before you dive into creating your narrative, it’s vital you empathize with the audience whom you’re presenting to.
Ask yourself who they are, what knowledge they already have about the subject and why would they be interested in what you’re about to tell them. Emotions are strong drivers in humans – you want to ask yourself which emotions you want to play on. Are the numbers you’re showing something to be celebrated, or are you spinning a cautionary tale?
With that in mind, also consider the context in which you’re telling your story. Going back to the earlier example about conversion, just highlighting a number or metric won’t really tell anyone anything.
Think about what background information your audience needs to appreciate what you are telling them. Any good storyteller knows that JRR Tolkien’s The Hobbit is a very entertaining story, but everything that happens becomes much more powerful if you have any notion of the plot in the Lord of the Rings. Obviously the suggestion is not to write an extensive trilogy, but do remember to properly set the scene. The right context will set your audience up for success.
Once you know your audience and you have a good understanding of their needs you can focus on building a robust narrative. Like any good story there will be a beginning, middle and end. In the beginning you want to set the scene and make sure the audience has the right context. Give them the information they need to understand the meat of the story.
Context is key
After an introduction we come to the core of the story. This is where the data is revealed, which is another important part to think out in advance. Make sure to reveal the data in the right order, an understandable order, that the audience can follow.
Your audience has to understand where something comes from, as well as understand what all of this information is leading up to. Few people will remember numbers out of context, but they will have a much better time remembering them if they have the right context. And if they’re led through a journey with a logical reveal at the end, they will be much more engaged with the content as well.
Timing is also crucial. Give your audience the time to process the data and information you’re sharing. Humans need time to process numbers, visuals and complex information. Don’t bombard them with number after number. Give the data context and allow people time to reach their own conclusions as well.
Wrap it up with the important parts
An important thing to remember is that visuals should add to your story, not distract from it. Keep them clean and simple
Finally, at the end, wrap everything up. The data has been given proper context and has been revealed and now you drive home the insights and take home messages. Keep this simple. The best endings are short, sweet, and easy to remember.
So with the story planned out, the next step is to think about your visuals. Visuals are a great way to support learning, remembering and understanding.
An important thing to remember is that visuals should add to your story, not distract from it. Keep them clean and simple. Too many colors, details and moving parts will only serve as a distraction. While your audience is trying to figure out what they are looking at, they are not listening to your story and therefore missing important context or information. So illustrate the important parts and leave out anything else.
So when you know your audience, your narrative and your visuals you can tell a data story that captivates.
By doing this you create the opportunity for anyone listening to learn, to remember and to act on the important information you have to share. People remember stories, not raw numbers. And the rewards for telling a good story will last a long time, form strong relationships, and others can continue to share your story, giving you and your team more time to focus on the next project.
This is a 5-part series
Click below to navigate to the next chapter
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Chapter 1 The challenges of working in data in 2021
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Chapter 2 A guide to data team structures with examples
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Chapter 3 Breaking communication barriers with a universal language
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Chapter 4 Reducing data downtime with data observability
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Chapter 5 How data storytelling can make your insights more effective
