Using data and visualization techniques, data storytelling is a strategy that data and narrative converge for communicating insights, trends, and findings in a compelling and meaningful manner.

Zuhal Yılmaz
5 Minute Read
Data Storytelling
Narrative Visualization
Data-Driven Storytelling
Data Visualization and Storytelling
Narrative Visualization Examples

Data Storytelling: Where Data and Narrative Converge

Data has been the key to growth since early civilization. People consider the variables and come up with a conclusion. So, analyzing data is crucial for improvement. Nevertheless, analyzing and understanding data is not enough without explanation. Communicating with data is also an important way to get into action under the influence of data. All these needs create the necessity for data storytelling.



  • Using data and visualization techniques, data storytelling is a strategy for communicating insights, trends, and findings in a compelling and meaningful manner. 



In this approach, data is presented in a narrative format that resonates with the audience and helps them comprehend its significance. It is an effective way to make sense of data, and it is also a powerful tool for convincing, informing, and educating audiences. Data-driven storytelling is becoming increasingly important in an age of data-driven decision-making.  



  • Data-driven storytelling has three fundamental components: Data, Narrative and Visualization.


  • Data:
    Before starting to tell a story, people should collect all of the data they need to tell the story accurately and clearly. People may prefer business analytics tools to collect the necessary data. 


  • Narrative:
    Building a strong narrative according to your audience is important. Your audience should understand your point of view through the story based on complex information. Your narrative should transform complex information into informative insight for your audience. 


  • Visualization:
    Visual representation provides a clear, memorable, and understandable story for your audience. By using narrative visualization, for example, using a graph to demonstrate fluctuations in sales over the course of a year, you can convey much more information than by using a paragraph. 



By using B2Metric, one can quickly and easily create visuals to illustrate the data in a meaningful way.

B2Metric blogpost

When these three key elements are successfully integrated, your data storytelling process is ready to impress your audience and make your insights understandable and memorable. 



People need a good story based on data to make an impact on their audience. So, people need a story that isn't quite different from classic stories.


  • To build a story, there are four key points to follow:


1) Characters:

  • Let's assume that you're a Growth Manager and your company has expanded. As a consequence of increasing customer segments, your team faces customer segmentation optimization problems.

In this case, the characters will be the customers, stakeholders, potential audience, and growth team. 

Note that: characters won't be told in your data story, but people should know the characters of their stories. 



2) Settings:

  • Continue with the previous example, picture the current scenario: Our company has enlarged and because of increasing customer segments, the growth team faces optimization problems about customer segmentation, which may cause a reduction in customer success. 



3) Conflict:

  • This includes defining and describing the root issue. This step isn't a must for a data story. If there's no conflict, then people can skip this part of building a story. 


4) Resolution:

  • This step is about proposing a solution. Making your audience find solutions by themselves by asking questions is an effective technique to persuade them to the solution. 




  • For our example, the company should start using a tool for customer segmentation. With B2Metric’s micro-segmentation companies can provide their customers hyper-personalized offers. In this way, they achieve better analysis and insights about their customers and stop the reduction in customer success. You can check Turk Telecom's customer success story similar to our example. 



  • At every step in the process, people should not forget to use narrative visualization. A visual representation of the data, which is the third fundamental component of data-driven storytelling, is extremely important to the audience's impression.  



  • A lack of effective communication can make your audience miss out on crucial insights if your message isn't delivered effectively. There is no doubt that communication is the most important factor when it comes to transforming your data insights into action. For every business today, data storytelling, which consists of both soft and hard skills, has become one of the most crucial elements of the organization. Especially, data-driven organizations should invest in the development of communication skills among their data science teams. By doing so, they can ensure that data insights are properly communicated and translated into effective action.


  • To reach your audience with better explanations and clear data storytelling and visualization, analyzing and simplifying data is important. At B2Metric, we provide easy-to-use dashboards for better understanding and correlating data for both technical and non-technical users. By combining the data from all the different data platforms you use, you can gain a holistic view of the situation. 


You now know how to tell a data story efficiently and how to analyze your data in a way that will take you less time. In order to impress your audience, you will want to spend as much time as possible improving your data storytelling skills. To see how easy it is to analyze data, explore the demo!

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