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Data Storytelling: The key to communicating data insights

Updated: Jan 24


Outstanding, you have the right data and the insights into what that data means for your organization. Now, how do you share this critical information to your organization or customer. Finding the best way to communicate the results from a data analysis can be a challenging task as listeners can easily get lost, confused, or even bored. Sharing the results through data storytelling helps your audience understand what the data means in a more effortless way resulting in better comprehension, action, and results


What is data storytelling:

Data storytelling is communicating the results from data analysis into a visual narrative story that is easily understandable to the target audience. But how do you take those inferences and craft a compelling narrative?


Key points to consider when developing your data story:


1. Do you have the right data to support your argument?

Whether you have identified a problem that you are trying to solve with insights from data or simply communicating the results from a data analysis effort, it is critical to ensure you are using the right data to support what you are conveying. The right data will motivate your audience to act. The wrong data will weaken your data story and confuse your audience


2. Know your audience

It is imperative to know your audience when telling a data story. Knowing your audience allows you to customize your presentation towards describing the data insights that will be the most impactful to them, thus compelling them to take action. Below are some audience characteristics that will help you tailor your data story to the right audience.

  • Business role: Are you speaking to business executives, managers, subject matter experts, data scientists? Based on the business role, you will need to tell your data story in a way your audience can understand as well as see the relevance of the data.

  • Why is your audience there: Are you selling a product to executives outside your company? Are you sharing information with your companies’ stakeholders? What is most important to them? What do they care about?

  • Level of understanding in data analytics: As you develop your data narrative it is important to craft your message in a way that resonates with your audience. Know how much detail to display with your data visualization as well as the level of sophistication with how you described how you obtained the results. Using plain language is preferable to data analyst jargon. Remember, less is more, but always be prepared with a robust appendix to address any questions.

3. Make sure your data is correct

There is nothing worse than giving a presentation and a member of the audience questions your data results. Make sure your data is correct. Check your data sources, data results and data within your data graphs, charts and displays. In addition, know where your data came from and validate your sources. These checks will ensure your full confidence in your data storytelling.


4. Develop your data story

Every meaningful story contains an introduction, a body of compelling information (in a good fictional story, a plot twist), and a conclusion. Data storytelling is no different as you creatively tell your story in a way that compels your audience to action. Your goal is to capture the audience’s attention while ensuring that you present a clear objective for what you want them to do. Key components as you develop your data story:

  • Create a specific objective for the data story: It is important to decide what specific action you want the audience to take as a result of telling your data story. Perhaps, a sale of a product, a change in the behavior in the organization or convince your company in a more efficient automotive process for the company’s applications or data pipeline.

  • Introduction: The introduction is to define the problem. Externally, this is typically the customer pain point. Internally, this is a specific problem ailing your company operations.

  • Body: The body is where the data becomes alive in the story. Let the data drive the story. Identify the data that tells your story in a compelling fashion and proves the objective to compel the audience to act.

  • Conclusion: The conclusion is the summary of what you describe in the body, but most importantly the call to action that you desire from the audience.

5. Choose the right data visualization for your data story:

Here is the fun part of data storytelling, picking the right data visualization that makes it easy for your audience to understand the data with respect to the story you are sharing. Data visual aids can be bar charts, line charts, pie charts, infographics, tables, heat maps, pivot tables, BI tools (such as MS Power BI, Tableau, SAS Visual Analytics). It is always a good idea to test out your data visualizations with someone similar to your target audience. In this way, they can ensure the data visualizations are consistent with your message as well as readable to your target audience.

Figure 1. An example of a data visualization using MS Power BI


Data storytelling is a powerful way to communicate the results of your data insights. Good data storytelling transforms plain confusing data to a compelling visual story that explains data insights and drives the audience to action. Need help with your data storytelling? Contact Scalesology, and let’s talk about the best way to tell your data story to your organization or your customers.