ParkShare
The Airbnb for Parking. A peer-to-peer marketplace transforming unused driveways and private lots into bookable parking spaces—solving the parking crisis in university campuses, major cities, and high-demand event venues.
For students circling campus lots and urban drivers navigating downtown Chicago, parking is a daily lottery—10–30 minutes of searching, ambiguous rules, and safety fears that erode time and wellbeing. Through 6 in-depth interviews, 5 research-backed personas, and mid-fidelity usability testing with 4 participants (SEQ 6.23/7, 100% task completion), I synthesized findings into a predictive, trust-centered platform concept.
Coming Soon: Iowa State Fair 2026 pilot partnership • World Cup venue preparation
Project Ongoing — advancing into high-fidelity prototyping and pilot deployment.
- Role UX Researcher, Product Strategist, Prompt Engineer
- Timeline Oct 2025 – Present
- Methods Contextual Inquiry, Thematic Analysis, Usability Testing, AI-Augmented Coding
- Tools Figma, GPT-5, Notion, Miro
- Status Mid-Fidelity Complete • Pilot Planning
6.23/7
Overall SEQ Score
100%
Task Completion
4
Usability Testers
6
In-Depth Interviews
5
Research Personas
5
Tasks Tested
The Story: A Daily Lottery Nobody Wants to Play
"If you get a parking spot, it's like lottery."
— Participant
"As a girl, I feel safer when the lot is more full and there's more light."
— Participant
Picture a student circling a campus lot at 8:47 AM, watching the clock tick toward a 9:00 class. Permits sold out months ago. Event-goers face even higher stakes—forced to move cars before midnight to avoid towing, or walking 10+ minutes in sub-zero temperatures.
The frustration isn't just about scarcity—it's about information, rules, and trust. Street-level signage is ambiguous; participants feel in the clear but still fear boots and tickets.
ParkShare's Systematic Response
Reallocate unused private driveways and small lots into a trusted, bookable network. Aligns with sustainability (less circling, lower CO₂), equity (more access to safe parking), and resource optimization (using underutilized spaces near campus and events).
Research Methodology
Research Goals
- • Understand how drivers search for, select, and pay for parking
- • Identify pain points, safety concerns, and rule confusion
- • Evaluate trust in peer-to-peer private driveway model
- • Test core ParkShare flows with scenario-based tasks
- • Translate findings into product strategy and HMWs
Participants
6 interview participants: students, commuters, urban drivers across Ames, Des Moines, Chicago, and Massachusetts. Ages early 20s to mid-30s.
3 usability test participants for mid-fidelity prototype—smartphone users comfortable with navigation and parking apps like ParkMobile.
Methods Applied
Contextual and semi-structured interviews • Codebook development and applied coding • Thematic analysis (6 key themes) • Insight statements with impact/confidence rankings • HMW generation and opportunity–solution tree • 5 research-backed personas • Mid-fidelity usability testing with SEQ ratings • Bias and rigor audit
Early Sketches & Ideation
Before moving to digital wireframes, I explored concepts through rapid paper sketching—mapping out screen flows, testing layout hierarchies, and iterating on information architecture. These sketches helped identify core interaction patterns and surfaced early usability considerations before committing to higher-fidelity designs.
Search & Discovery Flow Exploration
Booking & Confirmation Concepts
Host Onboarding Flow Sketches
Navigation & Arrival Experience
Key Findings: Six Themes from the Field
1. Reliable Spots Beat the Lottery
Drivers need predictable access to nearby spots, especially during events and peak hours. They adjust schedules, arriving 1–2 hours early to secure spaces.
2. Users Pay for Proximity & Time
Drivers are pragmatic: they will pay higher rates to avoid missing events. "If it's near to that event, I'm willing to pay for it."
3. Trust Rises with Safety Signals
Lighting, occupancy, neighborhood context, and host verification heavily shape perceived safety. P2P parking must feel culturally "normal."
4. Rule Clarity Reduces Anxiety
Ambiguous signs and event-based restrictions cause constant low-grade fear of tickets, boots, or towing.
5. Frictionless Flow = Value
Users avoid lots that are "more fuss than it's worth" and optimize for easy exits and no parallel parking.
6. Emotional Fatigue Is Real
Repeated hassles produce exhaustion. Users crave calm and assurance. "Why should this be a hassle for me?"
Research-Backed Personas
Lena
Time-Pressed Commuter
Minimize time hunting; ensure consistent access. Values reliability over savings. High tech comfort.
Opportunity: Predictive map, "Guaranteed Spot" reservations, auto-reserve weekdays.
Caleb
Budget-Conscious Student
Avoid fees when possible; find safe, affordable options. Walks long distances; sometimes risks restricted areas.
Opportunity: Transparent pricing, legality indicators, student discounts.
Maya
Cautious Night Driver
Feel physically safe at night. Checks reviews; avoids dimly lit or isolated areas.
Opportunity: Safety score, "Host Verified" badges, nighttime photos.
Ryan
Weekend Event-Goer
Park close to venues; avoid towing and long post-event exits. Proximity plus fast exit and clear enforcement windows are key.
Opportunity: Event-specific alerts, "Fast Exit" routing, towing timers.
Denise
Reluctant Host Homeowner
Earn passive income with minimal hassle; maintain control and safety. Needs clear liability coverage and community legitimacy.
Opportunity: Host Protection dashboard, verified renter identities, earnings projections.
User Flow Diagrams
Visualizing the complete user journeys for both drivers and hosts helped identify friction points and optimize the experience architecture.
Driver Journey: Search → Compare → Reserve → Navigate
Navigating to Spot Flow
Host Journey: Onboard → List → Manage → Earn
Rebook & Favorites Flow
Concept Development + Experience Strategy
Flow 1: Find & Reserve
User enters destination + arrival time; sees predictive availability map with confidence scores; results color-coded by trust level. Spot cards show proximity, price, safety score, and legal status badges.
Flow 2: Navigate & Park
From Booking Dashboard, tap "Navigate to Spot" for turn-by-turn directions. Arrival zone notification at ~50m. Final instructions provide access details and host confirmation.
Flow 3: Host Listing
Income-focused pitch ("Earn $200+/month"). Flow: address → photos + spot type → safety/availability → pricing/protection → publish with projected earnings.
Flow 4: Rebook & Auto-Reserve
"My Bookings" surfaces favorites, offers one-tap "Book Again," and "Auto-Reserve Weekdays" for commuters. Reduces friction for repeat users.
Value Proposition Framework
Predictability: confidence meter, guaranteed spots • Trust & Safety: safety scores, verified hosts, host protection dashboard • Legal Clarity: legality overlay, towing countdown timers • Frictionless Flow: fast exit, skill-based filters ("no parallel parking"), one-tap rebooking. Design frames price as time saved ("You're saving 12 minutes vs nearest garage").
Lo-Fi Prototype
The mid-fidelity prototype was built in Figma to test core flows with real users. These wireframes prioritize information hierarchy, interaction patterns, and content placement over visual polish—allowing validation before investing in high-fidelity design. Each flow tested with 3 participants, achieving SEQ 6.23/7 with 100% task completion.
Onboarding Flow: Welcome → Account Setup → Preferences → Ready to Park
Flow 1: Find & Reserve a Guaranteed Spot (Driver Journey)
Flow 2: Navigate & Park (Directions → Arrival → Confirmation)
Flow 3: Host Lists a New Space (Onboard → List → Publish)
Flow 4: Rebook & Smart Scheduling (Favorites → Auto-Reserve)
Usability Testing Results
4 participants tested 5 core tasks: Reserve a spot, Navigate and confirm arrival, List a parking space as host, Rebook a favorite spot, Set up automated weekday parking. Each task followed by SEQ (1-7) ratings.
Task-Level SEQ Scores (P4)
What Worked
- ✓ "The UI is simple" — P4
- ✓ "It met my expectations... similar to Google Maps and Apple Maps, no learning curve" — P4
- ✓ Navigation feature: "Navigator is going to be so useful because sometimes you forget where you're parked" — P4
- ✓ Host listing rated 7/7: "Clear prompts that told the user what next to do"
- ✓ Large CTA buttons guided actions: "literally guided me to what I need to tap next"
- ✓ Map showing spots within vicinity made selection easy
Design Changes Needed
- ✗ Search should allow destination entry, not just current location — "You could be going to a different place"
- ✗ Rebook flow felt incomplete: "I feel like there's a whole path that's missing"
- ✗ Auto-reserve should pre-fill previous booking info: "having to repeat information"
- ✗ Add search filters: price (high/low), distance, nearby facilities
- ✗ Generate booking receipt/ticket as proof of payment
- ✗ Simplify photo upload at arrival: "Taking an image, going back to the app... that's a lot of stress"
Feature Suggestions from Testing
Book for a Friend: "Can you book for someone? That would be nice."
Nearby Facilities: "Show facilities within that vicinity—food, gas stations."
Confidence Meter Clarity: Users initially confused about what it measures.
"It's a nice app... saves so many people the stress of having to find parking. People with free spaces could rent out and earn money. It's a win-win situation... especially in a place where they have bad parking. Iowa State—your parking system sucks. This would really help."
— P4, Usability Testing Session
AI Collaboration as Research Accelerator
As both UX researcher and prompt engineer, I orchestrated structured prompts to turn raw interviews into a full research stack. GPT-5 served as a research augmentation tool—accelerating coding, surfacing patterns, and maintaining analytical consistency while final decisions remained human-led.
Prompt 1: Codebook
Generated initial codebook with 12–20 codes including definitions, inclusion/exclusion criteria, and example quotes.
Prompt 2: Applied Coding
Applied codebook across 6 transcripts, proposed new codes like Lot_Egress_Friction and P2P_Cultural_Legitimacy_Barrier.
Prompt 3: Themes
Synthesized codes into 6 overarching themes: Scarcity, Cost Trade-offs, Trust & Safety, Rule Anxiety, Mobility UX, Emotional Fatigue.
Validation & Rigor
Cross-checked AI-generated codes against raw transcripts and my own notes. Used bias and rigor audit to identify sampling skew and avoid analytical overreach. AI was not a shortcut, but a research augmentation tool.
Product Vision + Roadmap
Phase 1 (Current)
Research & Mid-Fidelity: interviews, personas, codebook, themes, insights, HMWs, prototype with usability validation (4 participants).
Phase 2 (Next)
High-Fidelity: refined design system, search filters, destination entry, booking receipts, simplified photo capture.
Phase 3: Iowa State Fair 2026
Official pilot partnership with Iowa State Fair—testing with real hosts and event-goers at scale. High-stakes validation.
Phase 4: World Cup Ready
Preparing platform for FIFA 2026 World Cup venues. Scaling to handle major international event demand.
Long-Term Vision: The Airbnb for Parking
Scale to a nationwide marketplace connecting drivers with homeowners and businesses. Dynamic pricing tied to demand patterns, AI-powered availability prediction, trust scoring with host verification, legality engine with sign interpreter, and partnerships with municipalities and sustainability initiatives. ParkShare reduces cruising time, emissions, and stress while unlocking underused private infrastructure—creating value for drivers, hosts, and cities alike.