Community-Powered Workspace Finder
Helping students and remote workers find productive spaces with live, community-driven updates.
Role
UX/UI Designer
Tools
UX Research Wireframing Prototyping Design Systems
Date
Sept 2022 - Dec 2022
Overview
What is Study Spot?
StudySpot is a mobile application designed to help students, freelancers, and remote professionals find the best nearby spaces to study or work, based on real-time conditions like crowd level, noise, seating availability, and Wi-Fi quality. Developed in response to shifting post-pandemic work habits, StudySpot acknowledges that many people no longer rely on one consistent location to get work done. Users can explore options through an interactive map, view live updates, and share feedback with others—creating a community-driven way to discover productive environments.
The Problem
Finding a workspace shouldn't feel like a gamble.
Following the COVID-19 pandemic, more people began adopting hybrid lifestyles—working and studying across various environments. While flexibility increased, so did the uncertainty of finding a suitable workspace. Cafés were often crowded, campus spaces filled up quickly, and coworking venues were inconsistent or costly.
Existing tools like Google Maps or Yelp offer location information but fail to capture the real-time usability of a place—such as whether it's currently quiet, has open seating, or offers stable Wi-Fi. This often leads to wasted time, frustration, and disrupted focus.
User Research
How are people currently finding workspaces?
I wanted to gain a better understanding of how students, freelancers, and remote workers feel about navigating their workspace options. Flagstaff presented an interesting case study—a college town of about 75,000 people with a significant student population from Northern Arizona University, a growing remote work community attracted by the mountain lifestyle, and limited workspace options compared to larger cities.
After interviewing 10 users across three key demographics—NAU students, freelancers, and remote workers—I identified several common grievances and key insights. These conversations revealed patterns in how people currently make workspace decisions and where existing tools fall short.
The "Wasted Trip" Problem
The most striking finding was what I started calling the "wasted trip" problem. In a town like Flagstaff, this wasn't about having dozens of options—it was about the handful of good spots filling up fast and unpredictably. NAU students reported that campus library spaces would be empty at 9am but completely full by 10:30am. Freelancers described how their go-to café downtown might be perfect on weekdays but packed with tourists on weekends. Remote workers talked about the frustration of driving across town during winter weather only to find nowhere to work.
The altitude and seasonal weather added unique challenges that made the problem more acute than in other college towns. One remote software developer told me:
The primary frustrations centered around unexpected crowding, noise levels that made concentration impossible, and arriving to find zero available seating after already committing to the drive across town.
Why Existing Tools Fall Short
When I examined how people currently solved this problem, I found they were cobbling together information from multiple sources and still coming up short. Google Maps could show business hours and historical "busy times" graphs, but users reported these patterns had become completely unreliable after the pandemic changed behavior patterns. A café that used to empty out after lunch might now stay packed until closing. Yelp reviews might mention "quiet atmosphere," but that review could be from a summer tourist who visited during off-peak hours, not a local trying to work during the academic year rush.
In a smaller town where workspace options were limited, this information gap felt even more critical—every location mattered.
Information Gap: Google Maps and Yelp provided static information like hours and reviews, but users reported these patterns had become completely unreliable after the pandemic changed behavior patterns. Reviews might mention "quiet atmosphere," but that could be from a summer tourist who visited during off-peak hours.
Trust in Community: Most participants told me they would trust real-time updates from other users if the
information was recent (within the last hour), showed how many people were currently at the location, and built up over time so they could spot patterns like "always busy after football games."
Understanding Our Users
In analyzing user research, I developed three main user personas that best embodied our target audience's needs, pain points, and goals. Rather than designing for generic users, these personas reflected Flagstaff's specific demographics.
Ideation
Exploring features to solve the workspace discovery problem
Upon taking our user research and noting key pain points to address, I brainstormed and mapped out the preliminary information architecture through which the product would be structured. With research insights in hand, I began structuring the app around three core user needs that emerged consistently across all three user groups: quick discovery of suitable spaces, access to live and accurate conditions, and the ability to both contribute to and benefit from community knowledge.
I mapped the primary user flow to understand exactly how Maya, James, and Priya would move through the app from the moment they need a workspace to the moment they arrive—or decide to check in and help the community.
Feature Prioritization
I made the critical decision early on to prioritize features. This meant focusing on an interactive map with location pins, clear real-time indicators for crowd level, noise, Wi-Fi quality, and seating availability, basic filtering capabilities, and a quick check-in system for users to provide updates. However, features like saved favorites, historical data patterns, and social features would wait for future phases after validating the core concept with users.
Iteration
Designing with the goal of real-time confidence
After sketching preliminary wireframes, I created mid-fidelity prototypes to develop flows, build the vision of StudySpot, and conduct user testing. During this process, I explored various approaches to displaying location information, condition indicators, and the check-in experience.
Map View Iterations
When creating iterations of the map view, I explored how location pins should behave and what information should be immediately visible. Because users think about workspace location geographically first—especially in Flagstaff where downtown, campus, and residential areas are distinct zones—the map needed to be the default view.
I ultimately chose the design where tapping a pin triggers a smooth bottom sheet animation that maintains map context while revealing detailed information. When someone finds the right spot, prominent "Get Directions" and "Check In" buttons provide clear next actions.
Location Detail Iterations
While iterating on the location detail sheet, I analyzed how much information was necessary for decision-making without overwhelming users.
I ultimately chose the design where tapping a pin triggers a smooth bottom sheet animation that maintains map context while revealing detailed information. When someone finds the right spot, prominent "Get Directions" and "Check In" buttons provide clear next actions.
Filter System Iterations
The filter system went through several iterations before landing on progressive disclosure. Initially showing all filter options upfront overwhelmed users who just wanted "somewhere quiet right now."
The final design uses three persistent quick filters (Quiet Only, Fast Wi-Fi, Open Now) that cover the majority of filtering needs. Users who need more specificity can tap the filter icon to reveal advanced options, but testing showed most never need to.
Final Round
After many rounds of ideation, iteration, and testing, we present StudySpot!
Reflections
Lessons in community-driven design
The design journey is far from linear, yet I enjoyed every step!
This project marked my first deep dive into designing for community-driven platforms, and the biggest lesson was understanding the delicate balance between consuming and contributing. Users loved accessing real-time data but were initially reluctant to provide it themselves. The breakthrough came from reframing check-ins not as a favor to others but as participating in a reciprocal community.
Testing actual behavior rather than stated preferences proved invaluable. While users claimed they needed extensive filters and features, most testing participants never touched advanced options. This taught me the power of progressive disclosure—start simple and reveal complexity only when users seek it out.
If I had more time...
I would have validated the business model earlier in the process. I focused intensely on user needs and design craft but waited too long to test whether users would actually pay for premium features. Some assumptions about monetization only got tested after significant design work was complete.
I also wish I'd engaged with location operators (café owners, coworking spaces, libraries) sooner. Several expressed interest in a business dashboard where they could see patterns and even communicate capacity directly to users. This B2B opportunity emerged late but could have influenced the product roadmap from the beginning.
Finally, I'd build analytics infrastructure on day one rather than treating it as "nice to have." The insights from tracking feature usage, navigation patterns, and conversion funnels would have accelerated iteration cycles significantly.
Looking Forward
StudySpot addresses a genuine, growing need in our post-pandemic world where location flexibility has shifted from perk to expectation. The most satisfying aspect of this project was hearing users describe specific moments when StudySpot saved them from a wasted trip or helped them find a new favorite workspace they'd never known existed. That tangible impact on daily life—reclaiming time, reducing frustration, enabling better work—represents the ultimate success metric.
The long-term vision extends StudySpot beyond Flagstaff to other college towns and smaller cities where workspace options are limited but crucial. Phase 2 would introduce social features like seeing which locations friends are at and coordinating study sessions, while Phase 3 could integrate historical data patterns and predictions. As hybrid work becomes permanent, workspace discovery becomes a universal need, and StudySpot is positioned to become the default tool for this daily decision.
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