What is Data Storytelling?

According to researchers, colour visuals increase a human’s willingness to read by 80%. Furthermore, data visualisations are known to help an individual’s ability to interpret data faster, recognise patterns and find exceptions, in a fun and efficient way.

And with the proliferation of data in our daily social lives, data literacy is becoming more crucial for making sense of intricate cross-cutting issues. This is where data storytelling has a role to play.

In this blog, we will discuss the importance of data storytelling and how it can be used to communicate complex information in an effective manner.

What is data storytelling?

Data storytelling is the process of using data to tell stories, with a compelling narrative. It involves the use of data analytics, narrative techniques, and visualisations to create stories that are both informative and engaging. 

data visualization 1

Photo by RODNAE Productions

Data storytelling is principally employed to explain trends, identify patterns, and draw conclusions from data sets. It can also be utilised to illustrate the impact of decisions and actions, make data more memorable and persuasive, and provide insights into the future. To create compelling data narratives, it is essential to understand the key elements of data storytelling.

Data stories can be told using any kind of data—whether it’s a financial transaction history at grocery stores, weather patterns over decades on end, or even how many times people text each other per day. 

Why is data storytelling important?

Data storytelling has many benefits in a world where data continues to grow but is not fully exploited. It can help to make complex information easier to understand, as it utilises narrative techniques to explain trends and patterns in data sets. Therefore, it enables organisations to discover more valuable insights and then communicate them effectively.

It can also be used to illustrate the impact of decisions and actions and to provide insights into the future. Thus, leading to less uncertainty and more decisiveness whilst presenting a clear path for discussion for stakeholders.

Finally, data storytelling can help to inform and persuade audiences, as it can be used to communicate complex information in an effective manner. 

Advantages of data storytelling

Data storytelling provides companies with different advantages:

  • Valuable insights: Data storytelling enables organisations to move from insights to action more quickly. With strong data stories, businesses can present their work with a definite picture of the situation and an executable direction to move forward.
  • Decision support: Besides helping teams to make decisions, storytelling helps them act smarter with data guiding their direction. So, rather than working off gut instinct, the business can make more intelligent, data-informed decisions.
  • Motivates action: Whenever one customises their data storytelling to suit a target audience, it makes the data more relatable and impactful. This, in turn, can drive customer action. 
  • Targeted messages: Storytelling can help present a more targeted message and narrative around the data. Thus, clearly indicating why the message is important.
  • Improved collaboration: Data storytelling facilitates effective communication and collaboration with stakeholders throughout the organisation. This can lead to greater innovation when solving problems.

Data storytelling process

By using data, we are able to tell a story that is more engaging and memorable. This means one can get their audience engaged on an emotional level. However, to achieve this effect, there is an intentional process dictated.

1. Identify the story

For the most part, data storytelling starts with data collection, followed by analysis,  preparation, and then visualisation. 

However, this is all meaningless without a story direction. It is important to identify a story that serves a clear and specific objective. This determines the approach and plotline one should take.

2. Data collection and preparation

Once you have identified the storyline, you’ll need to collect the data to help you with analytical storytelling. 

Ensure to prioritise only the data that’s beneficial to your analysis and avoid overwhelming your audience with infinite data points. 

3. Data visualisation

Visual assets engage the audience with hidden insights to support your narrative, both at a granular and high level. Generally, visualisations aid comprehension by helping users identify patterns among different pieces of data sets through their common characteristics (like size), rather than just focusing solely on isolated facts themselves.

Read: What is data visualization, and why is it important? 

4. Create a narrative

To capture your potential customer’s attention, create a compelling storyline or narrative. The narrative should constitute an exciting and engaging plot to help your audience distil complex information into actionable insights. Your narrative will create a clear context to drive the linear nature of your data storytelling.

5. Presentation

After creating a narrative and collecting the data, it is important to consider how you present it to bring your entire story to life. You can choose between pie charts, infographics, or line charts, depending on your task.

For example, a line chart can be employed to show growth versus decline over time, while pie charts may be used to show percentages within categories such as age ranges or socioeconomic backgrounds (elderly vs young adults).

Data storytelling techniques

Generally speaking, data storytelling is a powerful tool that can be used to communicate complex information in an engaging and meaningful way. 

However, the two main types of data storytelling techniques are: visualisation, and storyboarding. Each has its own strengths and weaknesses, but they can all help you convey your message more effectively. Here’s how each one works:

  • Visualisation: This technique involves creating a visual representation of the data in order to help people understand it better. For example, if you’re trying to explain how your company’s customer loyalty program works by describing its main features (elements like “points” or “badges”), then a graph might be the best way for people who aren’t familiar with them to understand what those terms mean when applied at scale across multiple customers over time. 
  • Storyboarding: Storyboarding may be used to graphically translate data in an incremental step-by-step process. 

Data storytelling best practices

Data storytelling is different from other forms of communication because it conveys insights from your data rather than just telling facts or sharing opinions. 

It’s also useful as a way to connect with people who aren’t involved in research projects—for example, if you want someone outside of academia (or even inside) interested in learning more about what you’ve been working on lately. Here are some of the best practices to adopt to deliver effective data storytelling. 

Make data easily accessible

Strategically ensure that your data is accessible to all types of stakeholders and present it in an unbiased manner. 

Use visuals effectively

Consider the type of audience before you present visual assets that require high data literacy to understand. For example, if you are targeting highly educated business professionals, you can use complex charts. 

By the same token, avoid technical jargons that may confuse non-technical stakeholders, and rather, use business metrics to convey the impact of the data. 

Engage your audience

Ensure to engage your audience by focusing on the improvement of business metrics rather than technical metrics for business stakeholders. Technical elements may make the audience lose interest in the presentation. 

So, focus on highlighting, for example, an improvement in customer experience, or an increase in retention rates.

Keep it simple

Clutter always takes up the cognitive load whilst not delivering additional value. Removing distractions from the presentation brings attention to the core message of the data visualisation. 

So, strive to minimise the use of superfluous words, colours, and lines without sacrificing clarity. 

Use the right tools

Utilise data storytelling tools to generate interactive stories with your data, without the need for any technical skills. You can use any of the following:

  • Storyboardthat: This is an online tool that allows you to create interactive stories with your data.
  • Storify: This tool allows users to create dynamic content and share it on social media platforms like Twitter or Facebook.

Data storytelling examples

Building a narrative is a major element of the data storytelling process. However, this process also depends on your audience’s ability to understand and translate that narrative from an unbiased point of view. Here are a couple of examples of companies that have had success with data storytelling. 

Spotify typically sends out annual recap stories to its users in the format of an email. These short stories constitute engaging statistics for each user such as the number of minutes they’ve listened to music on their app.


Image from: https://open.spotify.com/

Similarly, Uber employs data storytelling to communicate annually with its users. However, instead of the annual recap, Uber sends an email showing how much value the service has delivered to its riders. 


Image from: https://www.uber.com/


Data storytelling is a powerful tool that can be used to communicate complex information in an engaging and meaningful way. 

It combines data analysis with narrative techniques to create compelling stories that can be employed to effectively inform and persuade an audience. It can also be used to illustrate the impact of decisions and actions and to provide insights into the future. 

Overall, data storytelling is important because it helps people to:

  • Understand what the data means and how it can be used to make better decisions.
  • Understand how to use data to solve problems.
  • Use data to make better decisions. 

Overall, data storytelling is an invaluable technique for anyone looking to communicate complex information in an effective manner. 

asian creative manager man presenting the successf 2022 12 16 03 32 39 utc scaled

As companies build up self-serve capabilities in analytics, it is imperative that more non-technical professionals get access to data storytelling skills to communicate insights and drive action. 

Reach us at Accord Training for workshops and training on data visualisation and storytelling and visual analytics.

Reviewed by

Comments are closed.