The Art of Coding User Feedback
The Art of Coding User Feedback
Meet GRAMS: Your Friendly Research Framework2
Techniques to Code Like a Pro (Without Going Cross-Eyed)3
They say data is the new gold, but much like gold, in its raw state, it’s pretty useless. That’s where coding comes in. Not the kind with curly brackets and caffeine-fuelled all-nighters; no, we’re talking about the kind that turns messy, human responses into meaningful insights.
TL;DR: User data on its own is just noise. Coding turns that chaos into patterns you can actually use. With frameworks like GRAMS (Goals, Reality, Alternatives, Motivations, Struggles), plus simple tools like Excel or even Post-its, you can uncover hidden needs, make smarter product decisions, and finally see why people behave the way they do. GRAMS essentially helps you find the signals from the noise.
If you’re a UX designer, service designer, product owner, or marketer, you’ve probably gathered heaps of user data at some point and thought, “Now what?” This guide is here to demystify the art (and science) of coding user data. We’ll walk through frameworks like GRAMS, explore different coding methods, and yes, even make a case for Excel as your trusty sidekick.
So, pop the kettle on, and let’s get stuck in.
Why Bother Coding User Data?
Think of coding like sorting socks after a wash, except the socks are thoughts, feelings, and behaviours. Coding helps us make sense of the chaos and uncover patterns. Done well, it allows us to understand users more deeply, identify unmet needs, and ultimately make smarter decisions.
Because in the end, understanding why people do what they do is what makes or breaks a product.
Meet GRAMS: Your Friendly Research Framework
GRAMS stands for Goals, Reality, Alternatives, Motivations, and Struggles. Think of it as the scaffolding for your analysis — it helps you structure interviews and decode responses without getting lost in a sea of Post-its.
Goals — What’s your user trying to achieve?
Reality — How do they feel when using your product or navigating a challenge?
Alternatives — What are they actually doing to reach their goals?
Motivations — What’s driving their behaviour?
Struggles — What’s the context or environment behind the scenes?
Used consistently, GRAMS gives your data meaning, your personas weight, and your presentations a lot more punch.
PS. You can download a free PDF of the GRAMS framework here
Techniques to Code Like a Pro (Without Going Cross-Eyed)
There’s no one-size-fits-all, but here are some trusty classics:
1. Thematic Analysis
Perfect if you like uncovering juicy patterns. You’ll start with raw transcripts and gradually build up themes. It’s great for identifying what’s really going on beneath the surface.
2. Grounded Theory
Ideal for when you’re open to discovery. Rather than confirming assumptions, you’re building understanding from the ground up. It involves open, axial, and selective coding; yes, it sounds technical, but it’s just a fancy way of saying “dig deep and connect the dots.”
3. Content Analysis
More structured, and sometimes quantitative, this one’s for when you need to measure frequency or keyword patterns. Think “how many people said X” or “what words are being used repeatedly?”
Excel: Not Just for Budgets and Boring Graphs
While there are plenty of fancy research tools out there, sometimes good old Excel is more than enough. You can:
Create a GRAMS-coded sheet
Tag and filter responses
Use pivot tables for themes
Colour-code pain points
Chart trends in a click
It’s not glamorous, but it works — and sometimes that’s all we need.
The Secret Sauce? Pair Coding with User Research
Numbers are great, but they don’t speak for themselves. That’s where qualitative research shines. Interviews, surveys, usability tests — they bring context, tone, and emotion to your data. Coding without research is like baking without tasting.
Motivation Theory: Why People Really Do Things
From Maslow’s hierarchy to behavioural nudges, motivation theory helps us unpack the “why.” Are users driven by convenience, social pressure, fear of missing out? Map it out and align it with the data you’ve gathered. Suddenly, the behaviour starts to make sense.
Use Post-its. Seriously.
Sometimes the simplest tools are the best. Stick your coded responses on a wall. Move them around. Group them. Debate them with your team. Post-its make insights feel tangible, and they’re brilliant for collaborative sense-making.
From Patterns to Prototypes
Once you’ve coded your data, it’s time to form hypotheses. Spot a trend? Turn it into a question you can test. Whether through A/B testing, user trials, or small pilots-validation helps turn insight into action.
Even failed hypotheses have value. They tell you what not to do. (And who doesn’t love crossing something off the list?)
Don’t Fear the Robots
Worried AI will take over? Don’t be. AI can crunch numbers and surface patterns, but it can’t replace human curiosity, empathy, or creativity. Think of it as a research assistant-one that doesn’t drink your tea or forget where it put the Post-its.
Keep Your Curiosity Alive
Whether you’re swimming in spreadsheets or knee-deep in sticky notes, remember coding is just a means to an end. The real goal is understanding people better.
So, keep exploring, keep questioning-and if you’re looking to sharpen your skills even further, have a look at our Consumer Psychology & Behaviour Design courses. They’re packed with frameworks like GRAMS, grounded in real-world practice, and designed to help you turn research into results.
Final Thought
The more you understand your users, the more magic you can create for them. Keep listening, keep learning-and keep coding.
