colorado · usa · 2021
adventure safely
ux case study
Role
Lead UX Researcher
Scrum Master, Design Studio Facilitator
Team
2 UI Designers
2 UX Researchers
Methods
In-Depth Interviews
Usability Testing
Landscape Analysis
Google Playstore Review Analysis
Project Overview
Adventure Safely is an outdoor recreational safety app. It helps adventurers find small levels of cell coverage that are just enough to send a text message to a chosen contact.
Working with coverage from cell towers, SMS texts to designated contacts serve as "check-ins" and contain the time, longitude, and latitude of the cell service found and information on the adventurer's location.
In the case of an emergency, these 'check-in' texts provide authorities with a great starting place to find a hurt or lost adventurer. It was the most affordable and reliable remote communication solution on the market.
So why was everyone uninstalling it?
Motivation
AdventureSafely was designed with the noble intent to keep outdoor explorers connected and safe. However, it wasn't living up to that mission. The app was experiencing high drop-off rates.
Our client suspected that users were uninstalling due to Android permissions-enabling pop-ups, as well as confusion when sending "check-in" texts and not getting confirmation of the action. This led users to think the app was broken, when it was simply working on finding cell service.
Early users described moments of panic, uncertainty, and frustration during this flow, which made many of them give up quickly and delete the app.
Our client wanted to understand why users weren't trusting the app, and how to design a more intuitive, reassuring experience that could increase retention and engagement.
Final Prototype
The final prototype was developed through multiple iterations of data-backed wireframing, allowing for more frictionless flows and intuitive signaling, especially in emergency or low coverage scenarios. To get here, we had to ask some important questions.
Key Research Questions
01
System Status Clarity
What elements were miscommunicating actions when sending 'check-in' texts and how might this flow be reimagined to communicate system status (success, fail, in-progress) with absolute clarity?
SURVEY
02
Coverage Navigation
How might we help users feel safer and more oriented in the app during its core, MVP flow (quickly finding or backtracking to cell coverage when service drops)?
METHODS
03
Contact Communication
How might our setup and notification models be refined to keep designated contacts informed without annoying pop-ups?
FORMATIVE TESTING + SURVERY
Methods
We used a mixed-methods evaluative research approach that combined behavioral metrics, attitudinal insights, and comparative market context. Our methodology was deliberately lightweight but analytically rigorous enough to surface patterns, validate solutions, and measure improvement across iterations.
In-depth Interviews
(n=10)
DEMOGRAPHIC
Outdoor enthusiasts aged 25-45 who frequently adventure outdoors in remote areas
APPROACH
We conducted semi-structured interviews to uncover adventurers' mental models around safety, check-ins with loved ones, and communication expectations in low-service environments.
RATIONALE
Interviews allowed us to go on an adventuring journey with our participants, surfacing individual idiosyncrasies, underlying assumptions, emotional drivers, and trust signals that quantitative metrics alone could not reveal.
ANALYSIS
We applied rapid affinity mapping to identify recurring patterns, then lightly segmented findings by adventure type and frequency, surfacing key mental-model gaps around coverage search and check-in confirmation. Insights were used to formulate our persona, Brian, and his annotated user journey, allowing us to immerse ourselves in his world using the app in a typical adventuring scenario.
Baseline Usability Testing
(n=6)
DEMOGRAPHIC
U.S. adults, outdoor enthusiasts aged 23-41
APPROACH
Scenario-based tasks across 3 core flows:
-
electing an emergency contact and setting up communication preferences
-
confirming that the message was sent
-
identifying a viable cell service location.
RATIONALE
Baseline testing enabled us to identify existing friction points, triangulating with findings from client interviews, landscape analysis, and Play Store reviews to solve for the right problems.
ANALYSIS
We measured time-on-task, misclicks, completion rate, and subjective ease. Cross-task comparison determined which flows carried the highest cognitive load, with micro-interaction analysis for error recovery patterns.
Lo / Mid / Hi-Fidelity Usability Testing
(n=5) / (n=10) / (n=10)
DEMOGRAPHIC
U.S. adult outdoor enthusiasts (23-41)
APPROACH
After compiling interview findings and holding a design studio session, low-fidelity wireframes were developed and tested. As the fidelity level increased, the design was iterated on after each round of testing. During testing, participants completed core scenarios as similar to the baseline round as possible, to allow for direct comparability and enable a three-point longitudinal comparison. Emphasis was placed on evaluating the redesigned feedback loop and refined SOS interaction sequence.
RATIONALE
Testing phases allowed us to validate revised navigation, clarity of feedback, and new information hierarchy, confirming design improvements and measuring success rate improvements across gradual stages.
ANALYSIS
Same metrics as baseline, using descriptive statistics to calculate average time on task, misclicks, and subjective ease ratings between each fidelity level. Simple effect deltas tracked improvements.
.png)
Landscape Analysis
5 competitor products
DEMOGRAPHIC
N/A
APPROACH
We compared key features across Garmin InReach, SPOT Gen3, GoTenna Mesh, AllTrails, and Cairn, examining coverage detection, SOS workflows, offline maps, and device requirements.
RATIONALE
This helped us understand industry standards and pinpoint where AdventureSafely aligns, differentiates, or falls short relative to user expectations shaped by competitors.
ANALYSIS
Defined scoring index between key features and manually analyzed each product. Hardware-based tools offer reliability but require costly devices; app competitors provide offline maps but struggle in remote areas. AdventureSafely positioned as accessible, phone-only middle ground.
Google Play Store Analysis
Body of user reviews
DEMOGRAPHIC
Google Play Store reviewers
APPROACH
We systematically coded user reviews to extract themes around trust, clarity, technical reliability, and check-in visibility. Subtle sentiment scoring applied to categorize pain points by emotional intensity.
RATIONALE
Reviews offered unfiltered, real-world feedback that captured edge cases and failure scenarios not always reproducible in structured testing, bridging the gap between client anxieties and actual customer complaints.
ANALYSIS
Used summative content analysis, quantifying frequency of themes (e.g., 'didn't get confirmation,' 'couldn't figure out where to start'). Triangulated review themes with interview and usability breakdowns.
How We Solved Each Research Question
Making System Status Unmistakable
WHAT WE LEARNED
Users consistently struggled to tell whether a check-in or SOS message had been sent. Across all testing rounds, participants searched for confirmation and expressed uncertainty when no feedback appeared. Play Store reviews echoed this confusion, citing a lack of visible status indicators and 'silent' progress that made the app feel unreliable and broken.
.png)
.png)
DESIGN IMPLICATIONS
We redesigned the system feedback loop to include clear success, fail, and in-progress states using motion, color, and concise microcopy. SOS became an active sequence with step-by-step visibility, replacing the previous passive, ambiguous interaction. We also replaced unclear icon choices in the existing app with more universal and intuitive icons. These changes provided more direction in how to get started and more immediate reassurance in moments where clarity is critical.
Help Users Find or Backtrack to Coverage
WHAT WE LEARNED
Our landscape analysis showed that competitors consistently use map-based interfaces for orientation to cell coverage, reinforcing an industry mental model that AdventureSafely was not meeting. Once we developed this screen at the mid-fidelity level, users struggled to locate coverage and often didn't know which direction to travel. Multiple entry points and inconsistent map cues created hesitation. Participants instinctively looked for a single, prominent action to 'find coverage,' and wanted clearer guidance once service was located.
DESIGN IMPLICATIONS
We shifted the interface to a clearer map-based layout, aligning with familiar patterns from tools like AllTrails and Cairn. We consolidated pathways into one 'Find Nearest Coverage' CTA and added directional guidance, distance indicators, and a clearer visual distinction between personal and community coverage zones. This reduced cognitive load and helped users move confidently toward service in high-stress moments. We analyzed improvements in each gradation with simple effect deltas (e.g., ↓ average time on task, ↑ success rate).
Reassure Designated Contact Without Pop-ups
WHAT WE LEARNED
Users wanted their emergency contact included but were wary of spamming them with frequent or redundant notifications. Interviews revealed that these designated contacts needed a single, reliable point of truth, instead of the ongoing pings like the existing app was sending. Usability tests showed confusion around where the trip setup lived and how much information would be shared.
DESIGN IMPLICATIONS
We streamlined trip setup into one flow capturing trip details, ETA, and the chosen contact. The system now sends a single confirmation message with a map link, and only alerts buddies if the user is overdue. This model supports transparency without creating noise or fatigue.
Outcomes
83%
TASK SUCCESS RATE
Outcomes
100%
COVERAGE TASK
Completion with 34s avg. time
92%
SOS FLOW SUCCESS
Users could articulate each stage
Usability Testing Results: Baseline vs. Final Design
Our redesign produced measurable improvements in clarity, confidence, and task success across the core safety flows. Users verbalized more confidence during SOS interactions and spent significantly less time searching for confirmation states or coverage paths.
Strategically, the research helped the team clarify AdventureSafely's market position and informed several product decisions. The client adopted a freemium model, offering basic personal coverage mapping for free while reserving community-sourced coverage zones for premium users.
We also established new ongoing UX KPIs (e.g., task success, retention, conversion, and session duration) to guide future product evaluation. Together, these outcomes positioned AdventureSafely as a more trustworthy, accessible, and scalable safety tool.
Future Directions
Our research surfaced several opportunities to further strengthen trust and usability in safety-critical moments:
Error & Recovery States
Introduce clear error and recovery states for failed check-ins or SOS attempts.
Buddy Dashboard
Expand into a dedicated 'buddy' (designated contact) dashboard for real-time trip visibility.
CTA Optimization
A/B test CTA placement and labeling on the coverage map to optimize discoverability.
Diverse Participant Pool
Recruit a more diverse participant pool, including broader age and gender representation for increased generalizability.
Offline Maps
Further explore support for the offline map feature to better match industry expectations and fill a key feature gap.
Broader Reflection
This project transformed how I think about the concept of trust in design in how it is earned through reliability which is a gradual feeling built through small, consistent signals.
Leading the research on this study reinforced for me that good UX research is as much about reducing anxiety as it is about improving metrics.
Every insight we gathered and mobilized shaped a calmer, more confident user experience that truly supports people when they're off the grid.
Closing Note
This case study presents the polished outcomes of a post-launch research initiative, but as with any project, the process included iterations, messy data, and behind-the-scenes decisions that can't all be captured here.
If you'd like to hear more about how we turned our multi-round usability data into a clear product direction, how we decided on which features we implemented, the ups and downs of our persona and his user journey, or about the challenges and trade-offs we faced along the way, I'd be happy to walk you through the full story in a presentation or live conversation.