Be it in the form of fables that teach good morals or mythological tales that underpin the major world religions, stories have been a proven medium for teaching, explaining, and influencing. Combining these benefits of stories with the factuality of quantitative data to drive decision-making is what data-driven storytelling is all about.
The effectiveness of stories in getting a point across stems from a psychological phenomenon called neural coupling. It is an event where, while listening to a story, the neural activation patterns of the listeners mirror those of the storytellers.
What this implies is that the listener becomes more receptive, trusting, and empathetic to the storyteller since both their brains are synchronized. And when infused with facts and data, stories or narratives can be a highly potent tool to bring about organizational change and shape business outcomes.
So, what is data storytelling?
Put simply, data storytelling is a communication technique that involves weaving stories or narratives around data to ensure that the insights from it are well received, retained, and acted upon. It involves the following three components:
Data storytelling requires you to have up-to-date and accurate data. Data reporting platforms automatically pull vast amounts of data from multiple sources and save a lot of time in data collection and cleaning. Once the collected data is cleaned, it is processed and analyzed using algorithms to derive statistics and actionable insights.
The goal of visualizations is to uncover trends and convey them in a comprehensible way. The insights extracted from data are graphically represented using charts, graphs and other visual elements to convey the information. These visualizations help in discovering underlying trends and patterns in complex datasets that may have otherwise been missed while using a spreadsheet. The trends and insights are then communicated in an easy-to-decipher manner to help businesses to come to conclusions quickly.
The final and most important element of data storytelling is narrative. Using a narrative to support the visualization and insights can help in presenting them in a simple language. Business users and analysts can use these narratives to highlight significant trends, changes, KPIs and metrics, and accelerate their decision-making process.
Why should businesses adopt data storytelling?
Today, businesses across industries are collecting more data than ever from various sources like social media, research firms, and their own processes in the form of analytics reports and logs. All this data can be used to analyze existing trends and make informed decisions.
However, most businesses are unable to make the most of their data. That’s because business leaders who are not data-savvy may have a hard time making sense of this data even after it is cleaned, sorted, and visualized by data analysts.
They are unable to interpret the data by considering the context, and thus cannot gain any actionable insights for decision-making. Hence, even if an organization’s data scientists perform incredibly astute data analyses, they cannot drive organizational change.
By adopting data storytelling and the power of language, business leaders are able to understand where their organization has been, where it is, and where it is heading in the form of fluid, easy-to-understand narratives. By reading or listening to data-driven stories, business leaders can easily grasp the most remarkable highlights from their data and can also gain clarity in terms of future steps to be taken.
And since stories have greater influential power than just data alone, data-driven storytelling can actually transform the way an organization functions and lead to improved business outcomes. It adds purpose and meaning to insights and makes it easy for businesses to process complex business information. Marrying data analytics with storytelling makes visualizations more engaging and impactful, helps in keeping the audience engaged, and leaves a lasting impact on them.
How can businesses facilitate data-driven storytelling?
In order to implement and benefit from data storytelling, businesses can do either of the following two things:
They can invest in training their data analysts to be good storytellers. It may take some time, but eventually, they can have analysts capable of providing insights through easy-to-consume narratives. Or,
Businesses can use natural language generation technology to automate report writing and turn their analytics reports into stories written in an engaging tone. These stories can build a convincing and impactful narrative around analytics data to tell business leaders what's happening in their organization, making the analysts’ job easier.
Get AI-generated Data Stories with Phrazor
Phrazor uses augmented analytics and natural language generation to create unique AI-generated e-commerce stories from data. It takes in the data, analyzes it to draw insights and presents them in the form of engaging stories with the help of narratives, all without human intervention. With Phrazor’s data stories, business users can make data-driven decisions at the speed of thought. All you need to do is upload your dataset and set the required parameters, and you can have multiple automated data stories compiled in a report, in just a few clicks.
Here’s what a data story generated by Phrazor looks like:
This is a monthly sales and customer analysis report for e-commerce companies that uses relevant analytics and visual dashboards written in natural language summaries to provide data-driven insights. Using this report, executives or sales and marketing managers of large organizations and SMEs can get insights from monthly e-commerce retail sales and customer analysis.
Businesses across the globe have adopted data storytelling to improve business reporting and decision-making processes. Regardless of the means used by businesses to implement it, data-driven storytelling can undoubtedly help them make the most of their data. By combining the objectivity of data with the fascination of stories, Phrazor creates compelling data stories from complex datasets in real-time and helps businesses in accelerating their journey towards becoming more data-driven, and hence more efficient and effective.
To try Phrazor for your business, get in touch with us.
Romil Shah is an AI enthusiast with considerable experience across varied technology domains, primarily Natural Language Generation (NLG), and Blockchain technology. He is passionate about technological innovation and more importantly its real-world applications. His work within the field has brought about constructive conversations and explorations around AI and its extended use in businesses.