Having a story to data adds the ‘human touch’ to the otherwise ‘hard cold numbers’ and provides the reason why the numbers matter to the audience. However, data storytelling often takes the backseat when compared to other aspects such as technical skills even though both are equally important and have the power to amaze people.
Let every little insight you discover lead you to the story
From experience, I found when I was too focused on the main story from the beginning, it turned out that the story is non-existent. I like to approach it like how I approach writing. I jot down my ideas and insights as I’m exploring. In the end, I look at these little insights again but with a bigger picture in mind to see if there’s 1 big theme connecting them. Just because I found many insights, doesn’t mean I want to put all of them in my viz.
Be comfortable throwing away your insight if you feel it doesn’t add value to the main story that you decide on.
What I found is having a narrow focus tends to help build the story. This doesn’t mean that I should only have a few points in your viz. I can still cover several areas as long as it still fits under one theme. In my Airbnb viz, I covered lots but still kept the insights to revolve only around the important factors in understanding the current Airbnb market in Sydney – price, and demand.
How I usually approach my data
I don’t always approach the data with a blank slate. There are 2 approaches I usually take:
1) Hypothesis questions (can come from thinking of the purpose first) and
2) Exploration without anything in mind. Keep your options open at this stage.
Where does the story come from?
Context adds meaning to the data to your audience and there are various ways how you can add context. Think about your end audience when you’re building the viz.
1) External
1. Domain knowledge
This may come from the field you studied or industry experience. For example, how I analyse survey data is heavily influenced by my knowledge of Marketing. I like
2. Research
Do your research, look up academic journals, websites or others. Research is especially crucial when you’re not that familiar with that subject. Even if you have knowledge in the domain, reading from other sources can offer a different angle from what you’ve thought of before.
My viz about EGMs in Victoria is very heavy on research, I can probably say that around 50% of the work is reading through academic journals to understand the gambling industry better in Victoria and Australia as a whole. External research can help provide the background why we should talk about that particular topic in the first place.
3. Supplementary data
(often the aggregates – e.g. government statistics). As a comparison of how ‘good’ or ‘bad’ these numbers imply, and may even suggest the urgency?
4. Personal experience or someone’s experience (the one person from the statistics)
[embedyt] https://www.youtube.com/watch?v=2dlVZ_pxGvM[/embedyt]
2) The data itself also tells a story
When people think about numbers and statistics, what come to mind are the aggregates: average, median, mode, you name it. And outliers are often forgotten.
Questions to ask when digging into insights
Dig deeper. This is what differentiates a computer from a human. Just scratching the surface.
1) Don’t stick with just descriptive insights
Dig deeper into the reason why it happens and the implications of what you found.
2) Why is it relevant to your end audience?
Keep on asking ‘So what’ to your insights. Yes, the insights seem interesting but why do I need to know them and how are they going to be useful to me?
Finding the story is just one part of the process, how you convey them also matters.
Structure, flow.
Narrow focus?
Choice of chart, I decide on what charts to use after deciding on the story. Some charts that I used for exploring end up in the final dashboard but some are charts I made specifically for that particular insights because I just found that it would be a more effective way to narrate that.