Rethinking how we make everyday laundry decisions.
A research-led product exploration into how contextual guidance could reduce the cognitive effort behind laundry — without taking control away from the user.
- Discover
- Principles
- Prototype
- Test · Round 1
- Iterate
Help users make better-informed laundry decisions with less cognitive effort — without asking them to surrender control.
Next · 02Why does this need to exist?Where does laundry become harder than it needs to be?
Behind a simple wash cycle sits a series of decisions. For some people they’re automatic. For others they create uncertainty.
- 01Before washingChoosing the right approach with confidence.
- 02When something goes wrongUnderstanding the problem and knowing what to do next.
- 03Before a consequenceIdentifying opportunities to prevent avoidable mistakes.
How might we reduce the cognitive effort of laundry decisions while preserving user understanding and control?
The challenge wasn’t doing laundry. It was the thinking behind the decisions.
- Insight_01More settings don’t automatically create more confidence.Access to choice doesn’t mean confidence in making the right one.
- Insight_02Convenience is also about reducing cognitive effort.Hard-to-interpret information pushes people back to familiar defaults.
- Insight_03Automation preferences exist on a spectrum.Reducing effort shouldn’t remove the ability to decide.
- Insight_04Support often starts after the problem.Technical feedback only helps if it can become an action.
- Insight_05 · creates a tensionTiming matters.Guidance may be worth more before a mistake than after it.
The research didn’t give me a feature list. It gave me a set of principles.
- Choice can create uncertaintyGuide, don’t overwhelm
- Recommendations need trustExplain, don’t just recommend
- Automation preferences varyAssist, don’t take over
- Problems create reactive behaviourSupport the moment of need
- Some mistakes may be preventablePrevent where possible
Designed around moments of uncertainty.
From “what do I pick?” to a more informed decision.
Each screen states why before asking the user to accept anything — and the recommendation can be overridden without leaving the flow.
Turning technical problems into actionable next steps.
The explanation names what is already correct as well as what isn’t — so it reads as an assessment, not a list of faults.
The product isn’t finished because the thinking isn’t.
When is a warning valuable enough to justify breaking the user’s flow?
An alert can be useful, or it can become another interruption.
Garment Health — a longer-term view of clothing care.
Open question: is this a meaningful user need, and what would make the information credible enough to trust?
A polished prototype is not proof that the experience works.
Scenario-based usability testing around the core journeys — comprehension, trust, expectations and reactions to automation. No findings are reported until the patterns are synthesised.
- Complete Round 1 · now
- Synthesise patterns
- Review assumptions
- Prioritise
- Iterate
- Retest
The next iteration should respond to patterns in evidence — not isolated opinions, or a desire to defend the original concept.
Not a story about arriving at the perfect solution. A story about taking an idea seriously enough to let evidence change it.
Not a finished interface — enough evidence to challenge an idea I initially believed in.
Research should shape direction, not decorate it. Explainability is part of the experience. Uncertainty can be a legitimate outcome.
Sole designer and researcher — concept, prototype and study design.
Claude
