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

Data-Driven Storytelling

Stories have been used as a medium of effective communication for thousands of years. Religious books, followed by billions across the world, 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 the conclusions to the audience, and is exactly what data storytelling is all about.

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

Conclusion: Narratives are highly effective tools to convey hard data in engaging methods, and hold the capability to 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 in a powerful and compelling fashion.’ To create a successful data storytelling experience, focus on the following three components:

  1. Data

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

  1. Visuals

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

  1. Narrative

The heart of the matter when it comes to data storytelling are the narratives. Narratives are nothing but written summaries of a data set. The narratives complement the dashboard visualizations so business users understand dashboards much better and take data-based instead of intuition-based decisions. Narratives can be used to highlight trends, KPIs and metrics, detected changes/anomalies in data, and make their decisions optimal and fast-paced.

Data Storytelling

“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 naturally 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 are unable to make sense of the data due to dashboards being visually complex. Understanding the context (why did a certain thing happen?) understanding future implications (what’s next from here?) are all left to the intuition and experience of the decision-maker. This impacts organizational progress adversely.

Adoption of data storytelling will empower business users to understand the position of their enterprise in the market in the current time and also as compared to its own 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 as a result of optimal decisions fuels organizational goals both in the short and long run. 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?

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, may take some time, but it will make your analysts capable of providing 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 are able to make data-driven decisions at the speed of thought. All that is needed is to upload the dataset, 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:

 Sales and customer analysis report - Phrazor

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.

Wrapping Up

Gartner estimates that by 2025, data storytelling will be the most widespread means of analytics consumption. Moreover, a full 75% of data stories by then will be automatically generated using augmented intelligence and machine learning rather than generated by data analysts. Enterprises of tomorrow 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 and assisting global giants like Barclays, Fidelity, Olam, LifeScan, and more to accelerate their quest towards incorporating data-driven cultures, and better results in all organizational processes. Request a free, no-obligation demo with us to see Phrazor’s data storytelling live in action.