What is data storytelling, and what is the most sufficient way to make use of data storytelling?
This is the most efficient method of disseminating corporate knowledge and driving results.
Businesses currently collect data at an incredible rate. You may now collect data on virtually every area of your business and, indeed, your life.
Despite the rise of solutions like BI tools, dashboards, and spreadsheets in the last few decades, businesses still can’t take advantage of all the opportunities hidden in their data.
Dashboards and spreadsheets simply provide information about what is happening. However, they do not tell us why.
There are several limits to BI tools, dashboards, and spreadsheets:
Data wrangling and manual reporting are still commonplace. The requirement for human intervention hinders data analysis and internal communications.
These tools only display data in the form of numbers and charts. They lack the necessary narrative component for successfully communicating facts and insights.
Scaling information requests is not feasible with current tools. Most marketing, sales, operations, and analytics teams don’t have the resources or time to respond to all reporting requests from all levels of a company and from outside groups like customers.
Simply said, data in dashboards and spreadsheets only tells you what is going on. However, they do not tell us why.
So, how can businesses turn their data center into a profit center where all stakeholders gain access to important data presented in a language and format that is appropriate for them?
The solution is straightforward: instill a data storytelling culture in your organization.
What Is Data Storytelling?
The capacity to successfully explain insights from a dataset using narratives and visualizations is referred to as data storytelling. It can be used to contextualize data insights and drive action from your audience.
Data storytelling is comprised of three major components:
- Data: The cornerstone of any data story is a thorough study of correct, full data. Data analysis techniques like descriptive, diagnostic, predictive, and prescriptive analysis can help you understand the big picture.
- Narrative: A tale, also known as a verbal or written narrative, is used to express insights drawn from data, the context around it, and actions you advocate and hope to inspire in your audience.
- Visualization: Visual representations of your data and narrative can help you tell your story clearly and memorably. These can take the form of charts, graphs, diagrams, photographs, or movies. For charts, you can use a WordPress tables plugin that does the heavy lifting for you.
Data storytelling can be used both inside and outside of your company. For example, you can use it to show that your product needs to be improved based on user data, or you can use it to make a strong case for buying your product to potential customers.
Why is data storytelling the way of the future?
Data storytelling is a means of communicating facts with a compelling narrative to a specific audience. It is the last 10 feet of your data analysis, and it could be the most important.
As humans, we have evolved to share stories as a way to pass on information.
According to some theorists, storytelling was the primary means of transmitting knowledge across large groups of people, resulting in the transmission of cultures as we know them today and allowing for evolutionary success across generations.
Only data storytelling can give us a human point of view on the increasingly complicated and rapidly changing world of the digital era because we have so much data at our disposal now.
Data storytelling brings together three essential areas of expertise:
- Data science is an interdisciplinary field of science that pulls knowledge and insight from data and makes it publicly available. This interesting field has made substantial changes to our daily lives in the last few decades.
- The technology we take for granted is all driven by this field of expertise, yet there is one thing that data scientists are not inherently skilled at: Storytelling.
It’s common for data scientists to be good at getting and distributing data, but they don’t have the skills to communicate how to find and use the opportunities that are hidden in the data.
The introduction of technology solutions such as dashboards became a natural solution to assist us in comprehending our massive volumes of data gathered. Transforming data into graphs, pie charts, and line charts allowed us to see our data like never before. Nevertheless, data visualizations on their own have limitations. They supplied data snapshots at a glance but lacked the context required to explain why something happened.
The narrative is the third and, in some ways, most important narrative of a data story. The narrative employs language in a format that is tailored to our specific needs, enhancing our full comprehension of new information. Visualizations and data are important proof points in a narrative, which is a good way to share ideas.
How to Write an Engaging Data Narrative?
Using the same elements as any other story you’ve read or heard before, data storytelling tells the same story. It has characters, a setting, conflict, and a resolution.
As an example, pretend you’re a data analyst who has just discovered that your company’s recent sales fall has been driven by clients of all genders between the ages of 14 and 23. When you find out that the drop in sales was caused by a viral social media post that showed your company’s bad environmental impact, you start to write a story based on the four main parts of a story:
- Characters: Customers between the ages of 14 and 23, environmentally-minded consumers, and your internal team are among the players and stakeholders. This doesn’t have to be in your presentation, but you should figure out who the important people are ahead of time.
- Setting the scene: Explain that there has been a recent reduction in sales, which has been driven by clients of all genders aged 14 to 23. Use data visualization to show how the number of people in each category fell, with a focus on young people.
- Describe the root cause of the conflict: A viral social media post showed your company’s bad environmental impact, causing tens of thousands of young customers to discontinue using your product. Remind the team of your company’s existing unsustainable manufacturing processes in order to explain why customers have quit buying your product.
- Solution: Propose your solution as a resolution. Based on this data, you propose a long-term aim of shifting to sustainable manufacturing techniques. In addition, you focus your marketing and public relations efforts on making this pivot visible to all audience segments. Use diagrams to show how the money spent on environmentally friendly manufacturing methods can pay off in the form of new customers from a growing group of people who care about the environment.
If there isn’t a conflict in your data story—for example, if the data shows that your current marketing effort is driving traffic and exceeding your goal—you may skip that step and recommend that the present course of action be maintained.
Whatever story the data tells, you can effectively express it by organizing your narrative with these pieces and guiding your audience through each piece with visualizations.
What constitutes a good data story?
A good data story incorporates three essential elements:
- narrative, and
The data component is straightforward; we must have reliable data in order to achieve proper insights. The visual component allows us to spot trends and patterns in datasets that would be difficult to see in spreadsheet rows and columns.
Data storytelling is about effectively communicating your insights and giving your data a voice.
The narrative components that concern the simple language used to describe the data might be thought of as giving the data a voice. Each data point is a protagonist in a story with its own story to tell. Putting narratives together with the right data and images can make data stories that can make businesses better.
Data storytelling is not a novel idea. Companies have been doing it for many years with varying degrees of success.
Here are some examples of how companies like Spotify, Slack, and Uber have used data storytelling to interact with their customers.
Slack, a new type of communication technology, is using stories to start a new conversation with clients each month at the time of billing.
Instead of sending an email with the invoice at the top and center, Slack sends a visual story communicating how its customers have used their service.
This high-impact communication is changing the conversation with customers.
Spotify, a music platform, has provided annual recap stories to its clients in the format of an email in recent years.
These short stories extract interesting facts about each user, such as the amount of time they’ve spent listening to music on their app. Instead of sending them an invoice or a simple thank you for utilizing our service, this is a more engaging approach to communicating the value of their service.
Uber, like Spotify, has used data storytelling to communicate with its customers every year.
Instead of an annual overview email detailing how much money you’ve spent with Uber, they’ve altered the conversation to demonstrate how much value the service has provided to their riders. You can see right away how much of an impact the app has had on your daily life by seeing statistics about your own experience with it.
We wanted to remind consumers of the importance Uber plays in their lives and show how using the ridesharing service is a partnership that allows them to travel across cities on a daily basis.
The three examples have three things in common: accurate data, a narrative, and meaningful visuals. Data storytelling has three components.
The following are the three examples’ similar themes:
A) You drove for Uber for X miles.
B) You’ve driven the equivalent of two world tours or X number of kilometers.
Although these three examples are strong in their own right, the resources required to carry them out were immense. These data stories are difficult to execute at scale due to the use of different teams, skill sets, and budgets.
Imagine using technology to automatically generate these stories, allowing you to engage with your key stakeholders whenever and however they want.
Does your CEO want an email data story once a month, while your customers prefer daily WhatsApp alerts sent directly to their smartphone?
Why is data storytelling so effective?
Throughout history, civilizations and societies have told stories; from cave paintings to novels to films, stories have been the primary means of transmitting important information.
People have been telling stories for a long time, but cave drawings are the earliest examples we know of. The oldest one was found in 1940 and dated back between 17,000 and 15,000 BCE.
Although oral storytelling appears to be an immediate byproduct of the creation of language, writing appears to have begun approximately 3,400 BCE in ancient Mesopotamia. The Sumerian civilization carved marks on clay tablets, which were used to record commercial and administrative data. Sumerian scribes also wrote and recorded more of their teachings as civilization progressed.
Two Sumerian manuscripts, the “Kesh Temple Hymn” and the “Instructions of Shuruppak,” are said to be the world’s oldest literature. The oldest fictitious story, written by the Sumerians once again, is thought to be “The Epic of Gilgamesh,” which was written approximately 2,000 BCE and chronicles the stories of King Gilgamesh, who ruled in the same period.
Facts just convey data, but the narrative of a story adds context to our knowledge and drives useful insights.
Fast forward to the nineteenth and twentieth centuries, when technology advanced at a breakneck pace. We evolved the channels through which we told and shared stories. Inventions such as printing, the radio, and television have significantly impacted human life and storytelling. We are constantly presented with new ways for people to tell their stories and affect others.
Orson Welles’ War of the Worlds, first broadcast in 1938, is a strong example of storytelling through the use of new technology.
It is widely assumed that when the story was initially broadcast, it was considered factual, causing widespread panic due to the imminent threat of an alien invasion. Although subsequent studies have revealed that this is a hoax, the story of fear is still reported and cited as an illustration of the power of radio and the media.
Modern storytelling may be found in our movies, TVs, newspapers, and on the internet; any medium we consume has the capacity to tell a story.
Even in the field of education, leaders are harnessing the power of storytelling.
For example, an examination of the popular educational and informative video series “TED Talks” discovered that stories account for at least 65 percent of the content.
Because stories have always been a simpler way to convey significant information.
As humans, we are social beings by nature, and we have evolved uniquely in comparison to other species as a result of our more social world. Stories have the ability to help us understand important information and, as a result, can mold our values, decide our prejudices, and affect our dreams. Religious texts are at the heart of this.
The most interesting stories in these texts are still influencing the modern world, both vertically across generations and horizontally between people who live together.
In our modern age of information overload, the psychology of stories, particularly as a memory aid, is an extremely important topic. Facts, by definition, convey data; but the narrative of a story provides context, which enhances our knowledge and produces useful insights.
The Story Method, or telling stories to remember, is a simple strategy utilized by memory champions. The method works because narratives can help people remember things better by making them more emotional, which can help them remember more parts of their brains. This makes it easier to remember the story and its parts.
A study undertaken by a team at Berkley tried to show this, and the results may be found here: