With the rise of digital content in businesses and data-driven decision making, data storytelling has become a much talked about skill that is associated with data science and community analytics. Data storytelling is defined as the process of translating data information into understandable terms to influence a business’s decision or action.
The idea of data storytelling is to connect the dots between very sophisticated data analyses and decision-makers, who, in return, might not be able to interpret the data. Data storytelling is often described in terms of traditional storytelling, for example, include a hook to draw the listener or reader in, the use of themes and emotion, and a conclusion.
Future of Data Storytelling
Data storytelling is a practice for communicating information that is tailored to a particular audience with compelling content. With so much data available to us now, data storytelling puts a human perspective to increasingly complex and quickly changing digital world.
The process of data storytelling merges three critical fields of skills, which include data science, visualization, and narrative.
The field of data science is the skill to extract knowledge and insight from data and make it readily available. The expertise of data science drives most of the technologies we take for granted today.
The development of technology solutions, like dashboards, became a solution to help us comprehend the massive amounts of data being collected. This is where data is transformed into graphs, pies, and line charts. Data visualization provides a glance snapshots of data, but lacks the perspective needed to explain why things are happening.
Probably the most vital part of a data story is the narrative. The description uses language in a structure that allows us to comprehend the new information we are receiving. The narrative is the critical skill to convey these insights, with visualization and data being important confirmation points.
What is Good Data Storytelling?
A good data story needs to leverage the three components of data, visuals, and narrative. Data storytelling is about communicating findings effectively and giving the data a recognizable voice. Each data point is a character in the story, and combined, narrative, data, and visuals create an account which can drive change in business.
Storytelling allows marketing to develop a meaningful connection with the audience. From the earliest history recorded, caveman used a form of storytelling to communicate, educate, share, and connect. Data storytelling blend both worlds of hard data and human communication.
Brand Benefits of Data Storytelling
Data storytelling is positioned to help markets achieve communications in many ways. These include:
Provide meaning and value – data storytelling connects the dots. It’s a useful tool for communicating valuable meaning, insights, and context of data that usually stays in spreadsheets.
Differentiate from competitors – when you have data know one else has, you can tell a story that is unique to your brand and company, differentiation you from the competition and make you stand out to customers.
Credibility – data storytelling shows the data, giving your content credibility and trust in your message and business or product
Message is heard – the blending of narrative and visual targets both sides of consumers’ brains and gives the best of both analytical and emotional experience, ensuring your message is being heard.
Creates engaging content – data storytelling inspires people to engage in the material. The two types of data storytelling, narrative and explorative, promote engagement but give the audience the ability to take different approaches.
Versatility – the information gained from data stories can be communicated to the public in different formats, such as articles, brochures, annual reports, infographics, presentations, and videos.