Storytelling with Data: Skills I Learned From Becoming a Market Researcher
I first dove into the market research world not too long ago. It began from my curiosity to understand more about consumer behavior in this dynamic ever-changing world. Before I landed a job as a market researcher I was a digital marketer, this was the point where I knew I wanted to be a researcher. I wanted to go beyond data and marketing metrics. I wanted to understand the pattern and the 5W1H of it. I’ve equipped myself with more knowledge about market research before I secure a market research role in DANA and finally come to a realization that being a market researcher, or even a researcher, in general, is beyond conducting quant or qual research and crunching data. For me, one of the biggest challenges is how we communicate our data. We often (or maybe it’s just me) focus on what data could answer the problem statement but overlook how the particular team or person could read and get the message through our data. We are here to help in better decision-making towards our company business goals, moreover to converting insights onto business strategy, so we need to have a skill in communicating our findings.
There’s an art to telling stories with data. Everyone in the company relies on our data and findings. Not to mention, when you are faced with a different type of audience. This particular skill that I still manage to adjust every day, needs tons of trials and errors and constant feedback. I have joined workshops related to storytelling with data but one of the eye-openers came from the book that my mentor suggested I read. So I will highlight the key takeaways about storytelling with data according to Kaflic’s Storytelling with Data.
1. Understanding the context
There are 3 things to think about before visualizing any data:
- Who, Firstly, To whom are you communicating? It is important to have a good understanding of who your audience is and how they perceive you. For instance, let’s say you are a teacher and your audience is a kindergarten student, you would add things like a bunny, spider-man, bright colors, basically anything to draw their attention to your presentation. But, what if your audience is your future investors? there will be different approaches right?. This part can help you to identify common ground that will help you ensure they get your message. You may meet several types of audiences along your professional journey, but based on my experience two types stand out the most. They are the data guy who is detail-oriented and the visual guy who would be intrigued to take any action based on the well-visualized data. In that case, try to be in their shoes to make sure the kind of data visualization you need to be presented.
- What, Second, What do you want your audience to know or do? If you are an in-house researcher, often someone that you are communicating with is either from the business team, marketing team, or product team. A different team needs a different perspective. You need to dig as much information as possible about what they need to know because, at the end of the day, you want to deliver comprehensive and relevant data. You also want them to understand the findings whether they can confirm the hypothesis, give them recommendations, or suggest what action needs to be taken.
- and How. Finally—and only after we can clearly articulate who our audience is and what we need them to know or do—we can turn to the data and ask the question: What data is available that will help make my point? Data becomes supporting evidence of the story you will build and tell. Then, it will lead us to how we illustrate the data in the next key point.
2. Focus your audience’s attention
The important thing about telling stories with data is knowing how to focus your audience’s attention where you want them to pay it. To do that, before you begin to illustrate the whole slide, choose an effective visual to visualize your data. Briefly, every type of visual like graphs, lines, pies, and so forth displays a different type of information. There are dos and don’ts in choosing an effective visual. There’s another lesson to cover that tho I’d not jump into the detail here. And don’t forget to eliminate clutter, because it makes our visuals appear more complicated than necessary. We want the visuals to look clean and give a comfortable experience to our audience.
Read here or watch here to understand more about choosing an effective visual and eliminating clutter.
Here comes the interesting part. Unconsciously, our eyes often focus on something that is in contrast to anything that we see in front of us and that thing will be easy to capture in our memory. It goes the same way when we want to illustrate our data. To highlight the insight of your findings, you can use preattentive attributes. We always use it on a day-to-day basis be it only as simple as bold, italic, or a little bit of both. Without us knowing, Preattentive attributes played a significant role in how we visualize our data.
Preattentive attributes signal where to look. If we use preattentive attributes strategically, they can help us enable our audience to see what we want them to see before they even know they’re seeing it.
Back then, I recklessly put everything to the canvas and only picture how I see it aesthetically and overlook the audience’s comfort to understand the data. I’m starting to use the preattentive attributes strategically be it on the graph or the text. Let’s see the following illustration to help you get a bigger picture of preattentive attributes.
They use the preattentive attributes both on text and graph. Let’s break down the preattentive attributes they used:
- They highlight the key point in the title to ensure the audience directly understand the context of the graph on the left, by using hue (blue color) and bold text
- Now we’ve got the idea that Thailand and the Philippines have had the highest proportion of new users and then we look at to the graph start comparing each country, and the highlight the highest proportion country by using enclosure on Thailand and the Philippines’.
A side note: They use a stacked bar which is effective in displaying changes over time or categories.
Let’s see another illustration with a different context, here:
Can you guess where Google wants you to focus? When you see it at a glance you may directly focus on the number or text that has green color and the number with a giant font size without understanding the context at first. Then, you start to read and understand what Google wants us to know. You may also notice how they put the position of the data on the page or slide which makes it easy to read because it follows how people’s common method to read which start from the top left of your visual or slide and scan with their eyes in zig-zag motions across the screen or page.
The first thing you see is the title or the context of the illustration “Indonesians are also looking for treatments they can do at home” after you get the context and then you begin to scan the data which validates the context. So, be mindful of how you position elements on a page and aim to do so in a way that will feel natural for your audience to consume.
3. Tell a Story
We tell stories with data to influence the team in making better decisions. In this part, not only your strategic thinking is needed but also your communication skills.
If you are the one analyzing and communicating the data, you likely know it best—you are a subject matter expert. -Cole Nussbaumer Knaflic.
This puts you in a unique position to interpret the data and help lead people to understand and act. In general, those communicating with data need to take a more confident stance when it comes to making specific observations and recommendations based on their analysis. When it comes to presenting my findings, usually I will run through the whole presentation with my colleague first and create a scenario case to accommodate the unexpected questions and feedback. I will recommend you to have practiced before you present just like what you did in school. Make a speaking note of the important points you want to deliver and worry less, this will get easier with time.
Storytelling with data has become a skill I didn’t realize I need to have. Moreover, I’m loving the fact that I (learn and) gained this particular skill through my journey as a market researcher. Hope this article would also broaden your perspective to learn more about storytelling with data or maybe become something you never thought you needed to. I believe we need this skill in today’s job role that is always faced with data. Feel free to share if you have any feedback and thank you for reading!
Source
- Storytelling with data mini-workshop:
- Declutter and chart guide:
