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and places this understanding within the context
of the bigger picture or issue which is to be solved. If you’re an analyst working on a dataset and you don’t know the business issue or what it is you are trying to solve — stop working on the data now and ask your manager or client to explain the bigger picture.
Let’s assume we can distinguish relevant data
from irrelevant data or “noise” — we now have the basis upon which to tell our data story. For many, storytelling is the domain of novelists or something pursued by award winning film studios such as Disney or Pixar. If we were to look for parallels
which are closer to our business, we’ll find that good storytelling skills are also possessed by great orators and leaders throughout history. Those people who can land their narrative squarely with their audience, share their vision and bring the audience along with them. Examples here could range from the famous, such as Martin Luther King through to the infamous (I am sure we can all think of a few). These leaders possess an innate ability to tell a story and to be able to share their story in a compelling way with their audience.
These are the masters, the entities whose words are studied by academics and then deconstructed to understand what are the ingredients for powerful stories.
“Does your client (or manager) expect you to deliver a story to
rival that of Disney or Pixar –
most certainly not! But can we deconstruct the ingredients of good story telling and try to learn from the masters – absolutely!
In the book “Persuasion and the Power of Story”, Stanford University Professor of Marketing Jennifer
L. Aaker explains that a successful story is built on three pillars:
1. It has to be memorable — to be special or unusual and making it worth being remembered
2. Ithastobeimpactful—tobebelievable/ truthful and thus resonate with the audience
3. Ithastobepersonal—thereisaconnection in the story and meaning is extracted
In summary, data storytelling is when someone takes a mountain of data — they use their technical skills and business acumen to interrogate the data to extract meaningful insights. These insights are then crafted into a story that others can engage with emotionally.
To be clear, when we say “emotionally” we mean
within the context of business — we’re not talking about making your audience cry, or overflow with tears of laughter. Emotional in this context means to make it personally relevant, to deliver a story that resonates with your audience.
By converting data insights into a human story using layman terms to invoke feelings, we are getting our audience to imagine a person and not navigate through a large set of numbers. For example, don’t
focus on reporting high and low ad engagement rates, try to humanise the data by adding context; make the connection with why the target audience might be engaged moreso with Creative A, as opposed to Creative B.
Strangely enough, stories with a lot of statistics don’t generally evoke an emotional response — it’s important to infuse the story with a human touch for maximum impact on your audience.
Why is Data Storytelling so powerful?
In her book “Persuasion and the Power of Story”,
THE EDIT ISSUE 05 | Q1 2017