Data-Driven Storytelling – What it is and why it matters

/ /

Stories have been a medium of effective communication for thousands of years. Religious books, followed by billions worldwide, drive ideal human morals through parables and stories. Schools use storytelling to teach, explain, and influence children at a very young age. Stories are an engaging art form; infusing them with the science and factuality of data presented through dashboards makes dashboards highly effective at conveying conclusions to the audience. It is exactly what data storytelling is all about.

There’s a scientific reason for this: Neural coupling is a concept that states that when an event is presented in the form of a story, the neurons produced in the listeners’ minds are similar to those in the speaker’s mind. This means that the listeners are on the same wavelength as the speaker and can interpret the message in the same manner the speaker tries to convey.

Conclusion: Narratives are highly effective tools for conveying hard data in engaging methods. They can bring about positive structural change and better decision-making systems.

Data Storytelling – Definition and Components

TDWI defines data storytelling as ‘the practice of building a narrative around a set of data and its accompanying visualizations to help convey the meaning of that data powerfully and compellingly.’ To create a successful data storytelling experience, focus on the following three components:

  1. Data

Structured and updated data is a prerequisite. Reporting platforms automatically retrieve large amounts of data from multiple sources, saving time invested in collection and cleaning. The cleaned data, which is processed and analyzed through algorithms, then derives actionable insights and relevant statistics.

  1. Visuals

Dashboard visualizations present extracted insights through charts, graphs, and other graphical representations available to report creators. The visualizations assist in extracting underlying data patterns and trends from complex data sets, patterns that may have otherwise been missed in traditional reporting using Excel spreadsheets. Such visualizations are intended to communicate actionable insights to decision-makers.

  1. Narrative

The heart of data storytelling is narratives. Narratives are nothing but written summaries of a data set. They complement the dashboard visualizations, so business users understand dashboards much better and make data-based instead of intuition-based decisions. Narratives can highlight trends, KPIs, and metrics, detect changes/anomalies in data, and make their decisions optimal and fast-paced.

A Venn diagram with three overlapping circles. The left circle is labeled “NARRATIVE” and has an icon of a document with quotation marks. The top right circle is labeled “VISUALS” and includes an icon of a pie chart and bar graph. The bottom circle is labeled “DATA” and shows an icon of a database. The center, where all three circles overlap, is highlighted in orange and labeled “Data-Driven Storytelling,” indicating the convergence of narrative, visuals, and data.

“People hear statistics, but they feel stories” – Brent Dykes

Should Businesses Embrace Data Storytelling?

The volume of data collection in today’s age is at an all-time high and will continue to grow as time passes. What this results in, however, is that most of the data collected and stored is not put to optimal utilization. One big reason could be that business users cannot make sense of the data due to visually complex dashboards. Understanding the context (why did a certain thing happen?) and future implications (what’s next from here?) are all left to the intuition and experience of the decision-maker. This impacts organizational progress adversely.

The adoption of data storytelling will empower business users to understand their enterprise’s current market position and compare it to its previous performance. Decision-makers will easily grasp, through the power of language and easy-to-understand narratives, the most important highlights of their data. Improved business outcomes result from optimal decisions, fueling organizational goals in the short and long run. Marrying data analytics with storytelling makes visualizations more engaging and impactful, helps keep the audience engaged, and leaves a lasting impact on them.

How Can Businesses Facilitate Data-driven Storytelling?

Businesses can take either of the following steps:

  1. Train your data analysts to become proficient storytellers. It is possible, and as with any long-term value-providing thing, it may take some time. Still, it will enable your analysts to provide actionable insights in easy-to-consume narrative formats.
  2. 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.

Getting AI-generated Data Stories with Phrazor

Phrazor applies augmented analytics and NLG (Natural Language Generation) capabilities to create unique AI-generated e-commerce stories from data. It intakes the data, analyzes it, draws insights, and presents them in engaging story formats with the help of narratives. All this is scalable, executed at machine speed, and without human intervention. With Phrazor’s data stories, business users can make data-driven decisions at the speed of thought. All that is needed is to upload the 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:

The image shows two bar graphs side by side. The left graph, titled “Geography-wise Analysis,” displays sales contributions from Germany (21%) and the UK (20%) for December 2011. The right graph, titled “Age Group-wise Analysis,” shows sales contributions from different age groups, with the 40-50 years group contributing the most. Below the graphs, there are paragraphs and bullet points discussing customer characteristics based on geography and age group, including specific figures like average sales per customer and order value.

This monthly sales and customer analysis report for e-commerce companies 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.

Wrapping Up

Gartner estimates that by 2025, data storytelling will be the most widespread means of analytics consumption. Moreover, by then, a full 75% of data stories will be automatically generated using augmented intelligence and machine learning rather than generated by data analysts. Enterprises of tomorrow will continue to adopt data storytelling methods to improve decision-making processes. Although the means of adoption and application may differ, data-driven storytelling enables enterprises to achieve the maximum out of their data.

Phrazor combines the objectivity of data with the fascination of stories to create compelling data stories from complex datasets in real-time. It assists global giants like Barclays, Fidelity, Olam, LifeScan, and more in accelerating their quest to incorporate data-driven cultures and achieve better results in all organizational processes. Request a free, no-obligation demo with us to see Phrazor’s data storytelling live in action.