BrewMatch - Removing friction from everyday choice
Choosing a coffee should be quick and satisfying, not a moment of pressure or uncertainty.
BrewMatch is a concept website that helps people confidently choose and make coffee using a short, friendly quiz that adapts to taste preferences, dietary needs, and available equipment. The focus isn’t on teaching people about coffee – it’s on reducing decision fatigue and ambiguity at the moment of choice.
Project Snapshot
Purpose
Explore how guided decision-making can reduce overwhelm in everyday consumer experiences.
Platform
Desktop web (responsive exploration not included)
Role
UX/UI Designer
Tools
Figma, Adobe Photoshop
Type
Concept Product
Why This Problem Was Worth Solving
Coffee menus – both in cafés and online – are deceptively complex.
Users are often presented with:
long lists of drinks,
unclear ingredient information,
assumptions about equipment or expertise,
social pressure to decide quickly.
As a result, people default to the same “safe” choices, even when they want something better suited to their taste or needs.
This project explores how clarity, filtering, and reassurance can turn a stressful micro-moment into a confident one.
Key User Challenges
Choice Overload
Endless combinations of roasts, syrups, milk types, and sizes make it hard to narrow down options quickly.
Unclear Dietary Information
Allergen and dietary details are often hidden or inconsistent, forcing users to guess or ask questions under pressure.
Equipment Mismatch
Many online recipes assume specialised tools, leading to frustration when users can’t replicate drinks at home.
Decision Fatigue
In fast-paced environments, users default to familiar choices rather than what they actually want.
These challenges showed up consistently through café observation, informal interviews, and competitive analysis.
Design Approach
Rather than presenting more information, BrewMatch focuses on structured guidance.
The core idea was simple:
Ask a small number of the right questions, then do the organising work for the user.
This meant prioritising:
speed over completeness,
reassurance over education,
filtering over browsing.
The Solution: Guided Choice Instead Of Browsing
A short, focused quiz
Users answer a small set of friendly questions about:
taste preferences,
strength,
sweetness,
dietary requirements,
mood or occasion.
The quiz reduces the menu from dozens of options to a curated shortlist, immediately lowering decision effort.
Built-in dietary filtering
Dietary and allergen considerations are embedded directly into the flow, ensuring unsuitable drinks never appear in the results.
This removes the need for last-minute checking and increases confidence – especially in time-sensitive situations.
Equipment-aware recipes
Each recommendation includes:
required equipment,
realistic alternatives,
clear, approachable instructions.
If users don’t own a specific tool, they’re shown practical substitutes rather than being blocked entirely.
favourites for fast, repeat decisions
Users can save preferred drinks, making repeat choices quick and pressure-free – particularly useful in café queues or busy mornings.
Validation & Feedback
“I love that it only shows drinks that fit my diet – no more Googling mid-order!”
During testing, users reported feeling:
more confident in their choices,
more willing to try new drinks,
more successful recreating café-style drinks at home.
The quiz speed and clarity were consistently highlighted as key strengths.
What This Project Demonstrates
BrewMatch is intentionally lightweight, but it reflects how I approach design problems:
identify where friction actually occurs,
reduce unnecessary choice,
respect users’ time and attention,
design systems that support confident decisions.
While the scope is smaller than a full product build, the project shows how thoughtful structure can outperform sheer volume of options.
Next Steps
BrewMatch was designed as a concept exploration rather than a production-ready product. Given more time, future iterations could include responsive layouts, richer personalisation, and deeper testing across different user contexts.