How to Tell a Data Story: Five Simple Steps

See the transformation of a default chart into a data storytelling slide with the help of StoryIQ’s 5Ds of Data Storytelling.

We’ve talked a lot about why Data Storytelling is important. However, it can be tricky to figure out how to begin applying it to your work. To make the process easier to comprehend and remember, here are five simple steps we’ve created called the 5Ds of Data Storytelling:

Let’s walk through how we applied the “5Ds” process step-by-step to transform the data analysis of this default chart on the Global Web Browser Market Share:

…to this made-over version with a clarified message:

1. Define

Our first step is to know our audience to define the most critical insights from our dataset that would be valuable for them. It is not enough to know our data inside out; we also need to think about our stakeholders right from the start and use their needs and expectations to guide us in defining what message we must call out. What does our audience care about? How can we link our message closely to what matters to them?

In our sample chart or graph, there are many noteworthy trends that we could choose to focus on. The trend that stands out most is the rapid rise in Google Chrome’s market share, which has more than doubled in the last eight years. This well-known product’s explosive growth might be the most relevant story for a broad audience.

However, imagine that we are presenting to an audience of iOS (iPhone) developers. These developers may be more interested in Apple’s Safari browser’s market share, especially on mobile devices.

Our role as data storytellers is to determine what insights will best serve our audience’s needs so we can present the chart or graph in a way that immediately calls out the essential. Once we’ve established what our audience needs to know, we want to convey our insights concisely. Our new headline, “Chrome Crushes the Competition,” helps us achieve this, capturing the key insight using just four words.

2. Draft

In this example, we are focused on forming a single slide highlighting a key message relevant to our audience. But in a typical business context, we might be asked to present a full deck comprising multiple charts and other slides that may or may not contain data. The last thing our audience needs is a long list of insights that might not be necessary or make sense altogether. Not only can this be overwhelming, but it can also be a waste of everyone’s time to go through data points that are not valuable for that moment.

Drafting our story encourages us to consider the big picture early in developing our data story to avoid wasting time building slides that might not be essential. It can be easy to get lost in the sea of insights and end up with dozens of slides or data visualization, half of which we might not even use. By starting with the pillars of our story in mind, we can make guided decisions on what is worth showing to our stakeholders, what might be better set aside in the appendix, and how to sequence them all to drive our point forward.

Going on slide sorter view can give a broader perspective of your slides so you can see how they relate to each other, sequence the slides in a way that works for your audience, and remove anything that does not add value to your data story’s central goal.

3. Display

Back to our main chart: We now have a critical choice. How do we visualize our data so that it’s easy for our audience to understand? Do we need to use a chart, and if so, what chart type will best showcase our insights? This is where thoughtful chart selection comes into play. Every chart has a specific purpose, and not all charts can be easily perceived by the human eye. Thinking about the Display forces us to consider not what type of chart looks good for us but what type works best to communicate the insight to our audience effectively.

In this case, our top choice for visualizing trends over time is a line chart. Compared with our 100% stacked bar chart, we can see that the lines facilitate a faster comparison of each product’s market share.

4. De-clutter

Once we have selected the optimum chart type, we must relentlessly purge any visual components that are not working hard to support our key takeaway. Often, these extra chart elements could distract from the main message we want to highlight and cloud the headspace of our audience.

In this example, we can simplify the chart by:

  • Removing gridlines.
  • Simplifying the X-Axis labels.
  • Replacing the legend at the bottom of the chart with labels next to each series, allowing us to use color more sparingly.

5. Direct

Finally, we want to direct our audience to the parts of our chart that support our key insights. In this case, we’re highlighting the Google Chrome series in bright green. This highlighting lets our audience immediately identify that the data supports our title and key takeaway.

Visually directing our stakeholders to the right information helps them to make better data-driven decisions.

A well-designed, clutter-free chart is a powerful tool for directing our audience’s attention to some additional insights. This could also help stakeholders make better data-driven decisions. For example:


Whatever message we highlight, the 5Ds of Data Storytelling help ensure our audience can understand and engage with our message meaningfully and help them make data-driven decisions.

Want to dive deeper into the 5Ds and apply this in a more comprehensive example? Check out our book, Data, Story, Action!.

To master the art of Data Storytelling and find other learning opportunities on data communication, check our scheduled workshops or contact us to set up an exclusive training.

Learn with us and earn your certificate in Data Storytelling. See you at our next workshop!

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