Data-Informed Design
The data-design poetry department; dilemma & anthology how-to guide.
Hi, I’m Felix! Welcome to this week’s ADPList’s Newsletter; 🔒 subscriber-only edition 🔒 weekly advice column. I write high-quality insights on designing products people love and leadership in tech. If you’re interested in sponsoring us, let’s chat!
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A guide on data-informed design even when you have no data (or too much data).
Last week, I wrote a LinkedIn post on how designers overestimate their opinions. Many designers/design leaders had things to say. Today, this is for those of you wanting to design with data into your strategies; this piece is tailored just for you.
Perhaps you're gearing up for a product launch or revamping an existing service. Or perhaps your day-to-day involves consulting or freelancing, each new project bringing a fresh client and unique challenges. Questions like… 👀 What's essential to grasp business and consumer perspectives? How do you gauge success? And what insights do you need to refine your designs continuously?
This week’s post aims to unpack five common dilemmas you might face when integrating quantitative data into your design process. As we interviewed Julie Zhuo (Former VP of Design, Meta), I’m here to share actionable insights that will benefit designers beginning to navigate the intricacies of data-informed design.
“Diagnose with data, treat with design” — Julie Zhuo
We’re going to dive into a list of challenges & advice:
What to do when you have “No data.”
What to do when you have “Too much data.”
How to translate your data into insights.
What if there are outlier data?
How to move past Amplitude/Google Data?
The Design-Data Dilemma Sheet
Before we get into the weeds, let’s define a couple of terms that will come up frequently: 'data' and 'insights.” Consider data as the raw numbers and insights as the interpretations that transform those numbers into actionable wisdom.
Now, let’s jump into the deep end.