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Why and how is data storytelling revolutionising emotional design?

Published on 8 July 2022

«Data storytelling is about using figures and facts to transform them into stories that everyone can understand.»

Data visualisation reports play a strategic role in a business. They allow, among other things, decision-makers to make rapid decisions. However, in reality, decision-makers are saturated with information, tables, charts, and figures. The most important indicators to retain are drowned in a mass of information.

A dataviz report that is difficult to understand, requiring control and verification phases, calls the entire report into question. So, what's to be done? How should we proceed to make reports more effective in the eyes of managers and decision-makers?

Integrate emotion through data storytelling!

Emotion is the key to embedding your dataviz messages in the memory of your hierarchy and your colleagues.

Data analysis is changing. Data alone is no longer enough; emotion needs to be integrated to help management make decisions. Data storytelling makes dataviz communications more effective and makes data stand out through a narrative approach.

« A story is 22 times more memorable than a statistic. »
Jennifer Aaker | Psychologist and Professor of Marketing at Stanford

Turn your data into readable stories

The art of telling a story with data and indicators is to use narrative methods within an interactive storytelling framework. Sequences, linearity, captions, explanations, explicit and implicit causality, message intensity, expected emotions and reactions.

How to implement Data Storytelling? We have listed 5 simple phases for you to consider for creating stunning dataviz reports based on the Data Storytelling approach:

Understanding and speaking to a target audience
To view, understand, analyse… everyone interacts with data differently. That's why we must listen to users and adapt to their level of data usage.
Select coherent data
In other words, understanding the context and nature of the data, its life cycle.
Build a scenario based on the data and the target
In order to find a relevant narrative that speaks to the user.
Select coherent data
Therefore, defining and choosing the indicators that have the most value for the end-user.

Format the data. In conclusion, indicators have a purpose and must deliver a message, because the user must accept and interpret the indicators that are displayed.

Example of emotional design

We present an example of a very common client case:

«I am a manager who needs to use an understandable and actionable dataviz report to make good decisions quickly.»

The problem: The data displayed is confusing and inconsistent.

Solution: Implementing Data Storytelling to produce a report that communicates a compelling story:

Is history optimistic or pessimistic?
- Is the overall assessment positive / negative?
- Does the gross margin meet the objectives?

What will be the outcome of the story?
- Is the actual performance in line with the forecast?
- What is the health of my business?
- Will I have to take economic measures?

To understand the most significant, powerful moments in history:
- What is this spike in activity?
- Why was there such a large stock during this period?
- In terms of data, how has the merger and reorganisation of services disrupted our financial results?

What are the most important facts from the story that I need to remember?
- We have a deficit of 15% compared to last month on industrial equipment sales.
- The July reorganisation boosted financial results by 22%
- I need to get in touch with the CEO to strengthen our sales teams based on the data displayed to me.