Every minute, 350K new tweets are sent, 243K photos uploaded to Facebook and 65K photos published on Instagram [source: go-globe.com].
With all this content generated each day, there is no denying Big Data is becoming part of our everyday lives. As social listeners and data scientists, we are witnessing an ever-increasing demand from clients to collect, and drill into the data to uncover the insights within it.
However, when it comes to presenting data insights, I know from personal experience that it’s all too easy to get stuck in a rut. While it’s tempting to rely on spreadsheets, slides and graphs, these rarely provide enough oomph to make the data meaningful to the final stakeholders. Similarly, complex technical terms may well be part of our jargon, but they are unlikely to be meaningful to those receiving the data.
This is where the art of storytelling comes in. While sceptics may dismiss it as a buzzword, it’s anything but a passing fancy. In fact, storytelling existed long before recorded history and is an intrinsic part of societies and cultures around the world.
By adopting data storytelling techniques, we’re making the data more potent. Not only will a compelling story keep the audience’s attention, but, compared to a spreadsheet, it has a greater chance of making a lasting impact. After all, what better way to captivate someone than an engaging narrative?
What is Data Storytelling?
In short, Data Storytelling is about linking Data, Narrative and Visualisation. To move people to action, we need to combine all the three areas, as shown in the chart below.*
- Using data analysis to resonate with our most rational self. Data helps kickstart our thought processes, but we rarely make successful decisions based on data alone.
- Assimilating data through visualisation. With the help of charts and images, we find it easier to navigate around numbers and remember the main ideas.
- Seeing the full picture. A comprehensive overview of the data makes it possible to contextualise the result and, ultimately, empathise with it.
How to become a great Data Storyteller
Although, at first glance, data storytelling might look easy, it’s more complex than most people would think. In fact, each of the parts above have enough layers and different aspects to fill an entire book.
With this in mind, I will take you through the foundational elements of Data Storytelling. These all help me in my daily work, from analysing social media conversations and putting the data in context, to creating a narrative that appeals to the target audience.
Data Storytelling 101
1 – There are no shortcuts
Although it’s tempting to cut straight to the point, this should be avoided at all costs. In any type of analysis, there must be two phases:
(1) Exploratory: Where we analyse the data and search for knowledge
(2) Explanatory. Where we explain what we have learned
2 – Think about your interlocutor
It’s all too easy to forget the final stakeholder when you’re in the middle of turning the data into insights. But whether you’re giving a talk, writing a book or creating a report, you must always remember to frame the content as best you can for your specific target audience.
3 – Keep potential distractions to a minimum
Flashy decorations may seem like a fun addition, but rather than adding value, these are more likely to detract from the insights presented. Instead, make the data speak for itself and let the conclusion stand out. Personally, I follow this simple rule: Simplify, clean and organise.
4 – Don’t hand over the work to a machine
In his book Storytelling with Data, Cole Nussbaumer hit the nail on the head with his mantra “Our tools don’t know the story”. Here at Convosphere, it’s all about using the tools to better provide business answers, rather than relying on them to deliver the insights on their own.
5 – Follow a storyline
All stories are comprised of three core parts:
- A hero
- An antagonist
- Turning points and climax
You don’t need the skills of a professional scriptwriter to succeed in storytelling, but understanding the basic principles of storytelling will without a doubt help transform your analysis and make it more powerful.
Keen to learn more? If so, I recommend the book “Nobody Wants to Read your Sh*t” by Steven Presfield, an easy-to-understand and entertaining guide on storytelling.
Let us know how you get on with applying these storytelling techniques to your next analysis project where you need to convince people to take action.
*Our version of this chart published on Forbes.
This article is a summary of Tamara Lucas’ post originally published on the Spanish Women at Technology blog, powered by Womenalia, a worldwide social network for professional women.
With a background in brand communication and journalism, Moa heads Convosphere’s content marketing and is the editor of the blog.
Before joining Convosphere, Moa worked as a writer and brand consultant for agencies including The Future Laboratory, LS:N Global, Canvas8 and Stylus, with a focus on packaging, retail and technology trends in the UK and Scandinavia.
Prior to this, she formed part of Cision’s Scandinavian research and analysis division, where she worked on PR projects for clients across different sectors, managing a large team of freelance reporters.