All Projects
(01)
Designing for Rest
Project type
Product Design, Mobile UX, Health & Wellness
Project role
Product Designer, UX Researcher, UI Designer
Date
2024
01
Overview
A deep sleep feature for the Oura Ring built around the science of rest.
A deep sleep feature for the Oura Ring built around the science of rest.
Oura tracks sleep stages, deep sleep, and readiness with quiet precision. But users were left holding a score, not a next step, rich data that rarely translated into changed behaviour.
Oura tracks sleep stages, deep sleep, and readiness with quiet precision. But users were left holding a score, not a next step, rich data that rarely translated into changed behaviour.
02
Understanding the disconnect
"Users receive insights but lack actionable next steps."
"Users receive insights but lack actionable next steps."
Research approach
Research approach
I conducted mixed-method research to understand the gap between data and behaviour change. This included 5 in-depth interviews with active sleep trackers (ages 23–38, diverse professions), a survey of 17 wearable users, and competitive analysis of WHOOP, Fitbit, and Apple Watch. I synthesized findings into an affinity map to identify patterns across motivations, barriers, and opportunities.
I conducted mixed-method research to understand the gap between data and behaviour change. This included 5 in-depth interviews with active sleep trackers (ages 23–38, diverse professions), a survey of 17 wearable users, and competitive analysis of WHOOP, Fitbit, and Apple Watch. I synthesized findings into an affinity map to identify patterns across motivations, barriers, and opportunities.
Survey · Question 01
What would make sleep data more actionable for you?
47.1%
Personalized recommendations ranked first, while lifestyle tips, the most generic option, came last at 5.9%. Guidance had to be shaped around the user's own patterns to count as actionable.
Personalized recommendations ranked first, while lifestyle tips, the most generic option, came last at 5.9%. Guidance had to be shaped around the user's own patterns to count as actionable.
Personalized recommendations
47.1%
Goal tracking
29.4%
Integration with other health data
17.6%
Lifestyle tips
5.9%
01
Finding 01
Finding 01
Research
Users wanted guidance “front and centre the first thing you see when you open the app.”
Decision
Surface micro-actions as a dropdown on the main dashboard easy to check off or snooze.
Surface micro-actions as a dropdown on the main dashboard easy to check off or snooze.
Impact
Guidance became unavoidable instead of buried three taps deep.
Guidance became unavoidable instead of buried three taps deep.
02
Finding 02
Finding 02
Research
Quiz-like, guided inputs were strongly preferred for creating a goal.
Decision
A short guided set-up with personalized feedback and visible progress tracking.
A short guided set-up with personalized feedback and visible progress tracking.
Impact
Goal-setting felt easy and motivating rather than like data entry.
Goal-setting felt easy and motivating rather than like data entry.
03
Finding 03
Finding 03
Research
People wanted digestible, plain-text reporting, not raw metrics or graphs.
Decision
Lead with plain-language insights and suggestions; keep the charts secondary.
Lead with plain-language insights and suggestions; keep the charts secondary.
Impact
Reporting read like a coach, not a spreadsheet.
Reporting read like a coach, not a spreadsheet.
04
Finding 04
Research
Daily check-ins were desired, but must never feel overwhelming.
Decision
Optional check-ins with a customizable frequency.
Optional check-ins with a customizable frequency.
Impact
Engagement without the fatigue that kills a daily habit.
Engagement without the fatigue that kills a daily habit.
What emerged
What emerged
Across all research, one theme dominated: users had rich data but no path forward. They wanted guidance that was actionable, personalized to their life, and delivered in plain language, not more metrics. These insights directly shaped the design phase, driving every decision toward simplicity, personalization, and micro-actions over data visualization.
Across all research, one theme dominated: users had rich data but no path forward. They wanted guidance that was actionable, personalized to their life, and delivered in plain language, not more metrics. These insights directly shaped the design phase, driving every decision toward simplicity, personalization, and micro-actions over data visualization.
03
Process
Process
Strategic goals & prioritization
Strategic goals & prioritization
Research revealed three aligned priorities: users needed clarity and actionability, business needed engagement and trust, both required simplicity over complexity. This shaped feature prioritization.
Research revealed three aligned priorities: users needed clarity and actionability, business needed engagement and trust, both required simplicity over complexity. This shaped feature prioritization.
Aligned goals
Business
Drive retention & engagement
User
Progress tracking & insights
Shared
Clarity + Actionability + Trust
Feature prioritization
P4
Partnerships · Research mode
P3
Smart home
P2
Social · Education
P1
Sleep goal tracking
Sleep goal tracking
AI coaching
AI coaching
Behavior tracking
Behavior tracking
Simplified dashboard
Simplified dashboard
From P1 to Two Flows
From P1 to Two Flows
With P1 features locked : goal tracking, AI coaching, behavior insights, simplified dashboard, the design challenge became singular: how do these features work together?
With P1 features locked : goal tracking, AI coaching, behavior insights, simplified dashboard, the design challenge became singular: how do these features work together?
What do I do today?
Setting daily habits
Transforms data into micro-actions: small, easy suggestions users see immediately.
Transforms data into micro-actions: small, easy suggestions users see immediately.
Where am I going?
Setting a deep-sleep goal
Gives users a north star and personalized roadmap.
Understand the problem
→
Set a goal
→
Receive daily guidance
→
Progress toward it
From scores to steps
Make the data do something
Make the data do something
Early concepts simply added more charts and tested cold. Reframing the work around micro-actions changed everything: the same metrics started to feel like coaching instead of homework.
The brief became less about visualising sleep and more about guiding the next small decision at the right moment, in plain language.
Early concepts simply added more charts and tested cold. Reframing the work around micro-actions changed everything: the same metrics started to feel like coaching instead of homework.
The brief became less about visualising sleep and more about guiding the next small decision at the right moment, in plain language.
04
From research to design
Concept 01
Setting Daily Habits
Small steps tied to the user’s patterns, surfaced at the right moment of the day. Reduces effort, keeps guidance simple, supports daily consistency.
Small steps tied to the user’s patterns, surfaced at the right moment of the day. Reduces effort, keeps guidance simple, supports daily consistency.
Concept 02
Deep Sleep Goal
One outcome to aim for. Users set a deep-sleep target and the app adapts advice to their trends, direction instead of more charts.
One outcome to aim for. Users set a deep-sleep target and the app adapts advice to their trends, direction instead of more charts.
05
The work
Two flows, one principle: guide the next step.
Two flows, one principle: guide the next step.
The feature ships as two connected flows. Both keep the data quiet and the next action loud — shown here as annotated walkthroughs.
The feature ships as two connected flows. Both keep the data quiet and the next action loud — shown here as annotated walkthroughs.
Flow A
Setting daily habits
A plateau alert invites small, snooze-able habits that drop straight onto the timeline.
A plateau alert invites small, snooze-able habits that drop straight onto the timeline.
Daily habits — alert → select → confirm
Daily habits — alert → select → confirm
Flow B
Setting a deep-sleep goal
A guided, quiz-like set-up produces a personalized plan, a target, and a check-in rhythm.
A guided, quiz-like set-up produces a personalized plan, a target, and a check-in rhythm.
Guided set-up — expectations → outcome → lifestyle
Guided set-up — expectations → outcome → lifestyle
06
Outcome & reflection
Less data on a screen. More rest in real life.
Less data on a screen. More rest in real life.
Testing & iteration cycle
Pain point
Why it happened
Iteration made
Pain point
Pain point
High misclick rates (62–85%)
Why it happened
Users didn’t know where to go next
Users didn’t know where to go next
Iteration made
Simplified UI with visual hierarchy
Simplified UI with visual hierarchy
Pain point
Pain point
Unclear terminology (“Micro Actions”)
Why it happened
Term wasn’t self-explanatory
Term wasn’t self-explanatory
Iteration made
Added tooltips and refined wording
Added tooltips and refined wording
Pain point
Pain point
Flat information hierarchy
Why it happened
Critical actions buried in clutter
Critical actions buried in clutter
Iteration made
Prioritized next steps
Prioritized next steps
01 / Visualizing
Simplify to engage
Simplify to engage
Stripping the dashboard back to one clear signal improved engagement far more than another graph ever did.
Stripping the dashboard back to one clear signal improved engagement far more than another graph ever did.
02 / Personalized
Tailor to the person
Tailor to the person
Recommendations mapped to individual sleep patterns not generic hygiene rules earned trust.
Recommendations mapped to individual sleep patterns not generic hygiene rules earned trust.
03 / Actionable
Motivation over metrics
Motivation over metrics
Behaviour change depends on motivation, not numbers. Plain-language micro-actions carried the feature.
Behaviour change depends on motivation, not numbers. Plain-language micro-actions carried the feature.
What's next
Pressure-test the micro-action engine over a longer window. Does guidance still feel fresh after week three? And explore an adaptive cadence that quietly recedes once a habit sticks. Building better sleep through small, consistent changes is the whole thesis; the design just has to keep earning its place each night.
What's next
Enrich the context around decisions, destination photos, sample costs, activity previews and grow the AI Concierge from budget tips toward fully personalized trip suggestions.