Data Storytelling vs Data Visualization: Understand the difference


Table of Contents

Discovering key information is one job, communicating it is another. Data Storytelling is a new area of expertise that is becoming necessary in business. It is certainly very important to be able to collect, process, and analyze data, but there is another equally important skill: the ability to communicate it clearly and effectively.

Converting data into action is the primary objective of the new field of expertise that is Data Storytelling. What sets it apart from data visualization (or dataviz): human communication. Dataviz helps to memorize and better understand information, Data Storytelling helps to persuade and make the right business decision more quickly in business. And persuading means winning!



I worked as a consultant for almost 15 years in a major American consulting firm. It was a wonderful experience where I got to know a lot of companies, take part in their processes, process a lot of data, and make it understandable to ManagementMy daily routine was spending half my time on Powerpoint and Excel to make sense of the data, with which I told stories - real stories: scenarios, retrospectives, analysis of company events, etc., to facilitate decision-making for companies.


This consulting experience (half my life so far, if you count it) has really made me realize the importance of telling stories to employees using their data.  

Your employees will be interested in your data and graphs if they tell a story, especially a story they are a part of and feel involved in. It is therefore necessary to personalize and contextualize the data to make it live and to make it interesting. Without a story, data is only numbers; and these figures, however useful, will not be attractive enough to catch the interest of everyone in the company.

The concept already exists. It’s called “Data Storytelling.” Toucan Toco has industrialized it and transformed it into a software solution product.





Data Storytelling is a new field of expertise where quantitative, cognitive and other types of science converge – the science of communication.

In recent years, all kinds of data can be found thanks to the various information systems that equip companies. The accumulation of this data has inexorably led to the emergence of self-service BI tools, facilitating access to data for a greater number of people in the company. More specifically, these tools are used by data experts or Data Scientists, a profession that has emerged in the last 10 years, established to program, extract, and work with data, and serving various business functions. Yet there exists another skill that shouldn’t be underestimated: the ability to communicate clearly and effectively.

Indeed, if Data Scientists do not promote the result of their work or do not communicate it clearly to everyone, their scientific model (as powerful as it is) will have little impact and will not have the expected effects. This results in anobvious loss of value for the company: what would then be the point of investing in information systems to retrieve the data and the resources involved in managing the data, if the information did not translate into actions and consequences for the business?

It is therefore important to equip and support Data Scientists to enhance their activity, and anyone else in the company to transform the results of their work into stories of interest to everyone in the company.


Data Storytelling is often associated with Dataviz, infographics, dashboards, data presentation, and so on. But it's much more than representing information in a visually appealing way! Data Storytelling is the next evolution of Dataviz. It adds a fundamental element: human communication.

Let us compare Dataviz and Data Storytelling with a simple example.

Dataviz scenario:

I picked 8 apples in my basket and made 2 pies to sell.

Interested? Raw information found in all company reports to measure production and sales performance.

Data Storytelling scenario:

In my basket, I have 8 apples picked from my grandfather's garden, who grew them using all-natural methods. This apple harvest was transported with our hybrid car to the laboratory, where I invited the best cook in the country to make these 2 apple pies, which were already reserved by the mayor of the village on our website for Mother's Day!

Want to know what he thought of them?

The difference between the Dataviz and Data Storytelling scenarios is narration. The 8 apples become interesting because they are part of a story. The same applies to any information:once contextualized and personalized, information makes sense to readers and piques their interest. They will make a decision immediately because Data Storytelling puts them at the heart of the story.


Here is the Data Storytelling equation in a more scientific light. Communicating information requires the combination of these 3 elements: the data, the graphic representation, and narration.


Graphic representation of Data Storytelling elements

Source: Photo by Brent Dykes

  • when visuals are associated with data (in the case of Dataviz), this helps to highlight it. Without certain graphical representations we would be unable to understand certain information (e.g., a heatmap of a shopping mall or a customer’s journey on a website)

  • when narration accompanies the data, we can explain the importance of this information. Contextualization and comments are fundamental to enhancing the information

  • when the narration is accompanied by graphic representation, it attracts attention and amuses the reader/viewer. This is pure storytelling. People need to read and go to the movies for entertainment. Observe: there’s a good reason why the entertainment market (books, shows, cinema, etc.) is worth several billion euros!


When there is a balanced combination of these 3 elements: data, graphic representation, and narration, Data Storytelling influences decision-making and drives change unanimously.


People often ask what Data Storytelling is for: How can it revolutionize business decision-making? What is the point of making Data appealing in business? At the end of the day, it's all about numbers, information, and calculations. So for the more expert users among us, telling stories might seem like a waste of time: “it should be enough to present data in a way that is clear to everyone and the information communicated should spur action and decision-making.”

Unfortunately, this assertion assumes that business decisions are made based on simple logic and rationale. But they’re not! Neuroscientists confirm that decisions are based on emotions, not logic. Yes,we make decisions with our emotional side, and what’s more, we defend them with logic !

Making data visually attractive is therefore not a question of art, but efficiency! Design is not an afterthought here. It helps to improve the company's performance, to communicate and make the right decisions in less time.

Convincing means winning! Unanimously, telling stories with your data is the only way to convince your employees, customers, and partners and to make them feel part of your and the company's projects.

We might say that decision-making becomes emotional.


When we do data storytelling, we create a link between the data and the emotional part of our brain, and this has several interesting effects:

  • Information arouses interest: it helps to “connect the dots” and remove barriers, like the story of the apple (told in the previous paragraphs)

  • Information becomes convincing: To differentiate from the others, we often resort to storytelling. We tell stories to make ourselves look good. Changing perspective allows us to value some assets that others neglect. We market ourselves! And on the other hand, information is all the more convincing when it is based on data. The telling of the story becomes believable.

  • Information becomes easier to memorize: With adequate graphic representation, the reader remembers what is being said. The narrative guides the reading of the data. There is an analytical and emotional experience at the same time. On the other hand, Dataviz is used to increase understanding and retention.


Transform your data into business insights

Get the report

Build your first Data Story in less than 10 minutes

Get a Demo
Data Storytelling
Get the report

Table of Contents