AllAround
A Location-Aware Wellness App That Lowers the Barrier to Getting Outside
UX Research · Interaction Design · UI Design
PROJECT OVERVIEW
AllAround is a mobile app designed to help people build sustainable outdoor activity habits — not by pushing harder workouts, but by removing the friction that stops people from starting. The app surfaces nearby routes, outdoor attractions, and activity suggestions tailored to a user's goals, location, and social circle.
I joined AllAround as the sole Product Designer at the early-stage health and wellness startup, working directly with the founding team to take the product from concept to a tested, high-fidelity prototype ready for investor and user validation.
PROJECT DETAILS
Time: 4 Months
Scope: End-to-end: research, strategy, IA, wireframing, visual design, prototyping, usability testing
Target Users: Adults 20–45 who want to be more active but face motivational or logistical barriers
MY ROLE
Product Designer (Sole Designer)
PLATFORM
iOS Mobile App
THE OPPORTUNITY
The founding team came to me with a clear hypothesis: the fitness app market is overcrowded with tools built for people who are already active. The gap — and the business opportunity — was the large segment of adults who want to move more but don't know where to start, lack motivation to go alone, or feel intimidated by traditional fitness apps.
My job was to validate that hypothesis through research, then design a product that genuinely addressed it.
THE PROBLEM
Despite growing awareness of the mental and physical health benefits of exercise, a significant portion of working adults struggle to maintain any consistent activity routine. The barriers aren't primarily about access to information — they're motivational, social, and logistical.
Design challenge
How might we lower the barriers to starting an outdoor activity routine and create a product that keeps people engaged long enough to build a lasting habit?
RESEARCH
Research Goals
Before proposing any solution, I needed to deeply understand the users the founding team believed were underserved. My research focused on three questions:
What are the real emotional and logistical barriers that stop people from being more active?
What motivates people to go outside when they do?
Where do existing apps fall short for non-athletes?
User Interviews
I conducted 8 qualitative interviews with adults aged 22–44 across a range of occupations and activity levels — from sedentary desk workers to occasional weekend walkers. I recruited participants who identified as "wanting to be more active" but not currently maintaining any fitness routine.
Key themes that emerged
Social accountability is a primary motivator. Nearly all participants said they were significantly more likely to commit to outdoor plans if a friend was involved. Scheduling friction — not lack of interest — was the main blocker.
Motivation is episodic, not consistent. Users described feeling motivated after busy or stressful days, but had no accessible way to act on that impulse quickly.
Novelty drives action. Participants noted they were far more likely to go outside when there was a new place to explore — a route they hadn't seen, a park they'd been meaning to visit.
Professional athletes are in the wrong frame. Multiple interviewees said they'd tried fitness apps and felt they weren't "fit enough" to use them. The language, imagery, and metrics in existing apps assumed a level of commitment they hadn't reached yet.
Small wins matter. Several users mentioned feeling genuinely good after short, low-effort outings like dog walks or foot errands — but existing apps dismissed these as non-events.
Secondary Research
I supplemented the primary interviews with secondary research to quantify the problem space and validate the business opportunity. Research from the CDC and peer-reviewed behavioural health studies consistently identified the same barriers:
Perceived lack of time
Low self-efficacy ("I'm not athletic")
Lack of social support
Boredom with repetitive exercise
Financial barriers (gym memberships)
Fear of injury or failure
These confirmed the patterns from my interviews and pointed toward a product strategy focused on accessibility, social features, and progressive engagement — rather than performance tracking for its own sake.
DEFINING THE USERS
Based on my research, I synthesized three distinct user personas representing the core audience segments. Rather than creating generic archetypes, each persona was grounded in specific quotes and behavior patterns from the interviews.
Marie, 38
The Time-Poor Professional Full-time manager and dog owner. Wants to be more active but struggles to justify time away from work and family commitments. Would benefit from short, efficient activity options she could integrate into her existing routine (e.g., dog-friendly parks near the office).
Satwik, 29
The Remote Worker Seeking Structure UX researcher working from home. Spends 8+ hours daily at a screen with no natural reason to leave the house. Needs external prompts and interesting destinations to interrupt sedentary patterns. Highly motivated by discovery and novelty.
Leah, 34
The Lapsed Exerciser Artist and parent. Was more active before having children and wants to rebuild a habit. Motivation is high, but consistency is the challenge. Would benefit from social features and visible progress to maintain momentum.
User Journey Mapping
I mapped the end-to-end journey for each persona — from the moment a motivation trigger occurred (a stressful afternoon, a free Saturday morning) through discovery, planning, execution, and reflection. This exercise revealed the critical drop-off points: users had motivation but no clear next step, and by the time they'd figured out where to go, the impulse had passed.
This insight directly informed the product strategy: AllAround needed to collapse the distance between "I want to go outside" and "I know exactly where to go."
COMPETITIVE ANALYSIS
I audited four direct and indirect competitors: Komoot, AllTrails, Google Maps, and Strava.
Key finding: Every existing solution was built for a user who already knows what they want to do and needs help executing it. None addressed the earlier stage of the journey — the user who is motivated but undecided, or the user who doesn't identify as a "hiker" or "runner."
This gave the founding team a clear strategic position: AllAround would own the entry-level outdoor wellness market that competitors had left unaddressed.
PRODUCT STRATEGY & VALUE PROPOSITIONS
Working with the founding team, I translated the research into a clear set of value propositions that would guide all design decisions:
Personalised activity discovery — Surface routes and attractions based on a user's location, preferences, and available time — not generic lists
Smart, contextual notifications — Prompt users at moments when they're likely to be receptive (end of workday, good weather, nearby friends) rather than on a fixed schedule
Social coordination — Make it easy to plan activities with friends directly in the app, removing the back-and-forth that kills spontaneous plans
Progress tracking for all levels — Track distance, time, and calories in a way that celebrates small wins, not just athletic achievements
Accessible activity levels — Every suggestion is tagged by effort level, so users never feel out of their depth
IDEATION & PRIORITISATION
Using a Crazy 8s session, I generated over 16 distinct feature concepts across three focus areas: motivation mechanics, discovery, and social coordination. I then used an Impact–Effort matrix to identify the highest-value features for the MVP — prioritising the ones that directly addressed the drop-off moments identified in the journey mapping.
MVP features selected
Location-aware activity and route discovery
Personalised onboarding to capture goals, fitness level, and preferences
In-app social planning and friend invitations
Activity tracking (distance, duration, calories)
Achievement sharing (in-app and social media)
Smart notification system
DESIGN & PROTOTYPING
Story Boarding
Big picture Scenario
Close up Scenario
Information Architecture
I designed the IA around a single core principle: the path from "I want to go outside" to "I know where to go" should take under 30 seconds. This meant surfacing personalised suggestions immediately on the home screen, with filtering as a secondary action rather than a required first step.
Lo-Fidelity Prototyping
I used paper prototypes for early-stage concept validation, testing the core flows — discovery, trip planning, and activity tracking — with 5 participants before committing to digital wireframes. This allowed rapid iteration on the structural decisions before any visual design investment.
Usability Testing — Round 1 (Lo-Fi)
Testing the paper prototype surfaced three critical issues:
1. Filter friction on the Explore screen
Users had to apply filters every time they opened the Explore tab to see relevant activity types. This created unnecessary cognitive load and slowed the path to discovery. Fix: Surfaced the user's preferred activity types by default, with filters as an opt-in refinement.
2. Ambiguous "Favourites" placement
A Favourites icon in the navigation bar was consistently misunderstood. Users either ignored it or tapped it, expecting a different outcome. Fix: Moved Favourites into contextual save actions within activity cards, removing it from primary navigation.
3. Overly structured trip editing
The trip editing flow assumed users would plan ahead in detail. Testing revealed that most users were spontaneous — they wanted to modify plans in the moment, not in advance. Fix: Redesigned the editing experience around real-time, in-activity adjustments rather than pre-trip configuration.
UI Design
The visual design direction was informed by the brand positioning: approachable, active, and grounded in the natural world. The palette draws from outdoor environments — deep forest greens, warm amber, and clean neutrals — deliberately avoiding the neon-and-black aesthetic of performance fitness apps.
Typography choices prioritised legibility during activity (larger touch targets, high-contrast text) while maintaining a design language that felt premium enough to justify a subscription model.
Usability Testing — Round 2 (Hi-Fi)
I tested the high-fidelity prototype with 8 participants representing all three persona types, measuring task completion and collecting qualitative feedback on key flows.
Results
Task completion rate (finding and saving a nearby activity): 87.5% (7/8 users completed without assistance)
Task completion rate (planning an activity with a friend): 75% (6/8 users completed; 2 required prompting on the invite flow)
Average perceived ease of use (1–5 scale): 4.2
Top-rated feature: Personalised activity suggestions based on location and preferences
Most requested addition: More activity types (outdoor yoga, group fitness classes, surfing)
OUTCOMES & REFLECTIONS
What the prototype validated
The research hypothesis was confirmed: users in the 20–45 age bracket who don't identify as athletes responded strongly to activity suggestions framed around discovery and social connection rather than performance and metrics. The social coordination feature, in particular, was cited by 6 of 8 test participants as the primary reason they would use AllAround over existing alternatives.
What I would do differently
Push harder on the notification design
Smart notifications were a core value proposition, but they were the least developed feature in the prototype. I would invest more time designing and testing the notification logic — when to send, how to phrase prompts, and how to avoid notification fatigue — as this is likely the highest-leverage mechanism for driving habit formation.
Validate the social graph earlier
The friend-planning feature assumed users had friends to invite. I'd want to explore network-effect mechanics (e.g., discovering other users nearby, joining group activities) earlier in the process to ensure the social features work for users who join without an existing network.
Define business metrics from day one
While the product design was user-centric throughout, I'd now ensure that key business metrics — retention at day 7 and day 30, conversion from free to paid, session length — were defined upfront and mapped to specific design decisions, making it easier to evaluate success post-launch.
PROTOTYPE
