Personas

Personas

Persona	Key Details	Goals & Needs	Pain Points	Implications for Design
Commuter Carl	Profile: 25–50 years old. Works downtown or takes the train daily from Canora REM station. Drives a sedan or SUV, sometimes an electric car. Fairly comfortable with technology. Says: “If I can’t find a spot quickly, I’ll miss my train.” Goals/Needs: Wants secure daytime parking near transit, quick entry and exit with little waiting, and assurance that building tenants get priority for spots. Frustrations: Parking lots often show as “full” even when spaces are open, long time wasted circulating underground garages, and EV drivers often find charging stations taken. Design Implications: Display predicted availability during commuter hours, allow EV charger reservations with priority rules, and reduce entry steps with tools like RFID, QR access, or live updates.
Resident Rachel	• Age: ~30–60 • Lives in the condo, parks daily or nightly • Drives a compact car, SUV, or EV • Tech level: Low–Medium • Quote: “I pay for my spot—there better be one waiting when I come home.”	• Guaranteed spot when returning at night • Assurance commuters don’t take tenant spaces • Safe and clear navigation inside the garage	• Fear of losing their space to temporary parkers • Confusion about rules or mis-parked cars • Noise or congestion from outsiders	• Predictive algorithm must always protect tenant priority • Section-based signage to avoid mis-parking • Transparent reporting to reassure tenants
Garage Operator Oliver	• Age: ~35–55 • Property manager at Elora MTL • Oversees tenants, garage logistics, and commuter integration • Tech level: Medium • Quote: “I need real-time visibility and minimal complaints.”	• Clear dashboard with occupancy, trends, and system health • Balance tenant satisfaction with commuter revenue • Automated monitoring, minimal manual work	• Sensor or system failures causing complaints • Integration issues between RFID, cameras, and signage • Hard to justify system decisions without data	• Intuitive dashboard with alerts and manual override • Robust fallback procedures (refresh, local storage) • Ability to show tenants live availability data
EV Ellie	• Age: ~28–45 • Early adopter of electric vehicles • Needs reliable charging during work hours • Tech level: High • Quote: “If I can’t charge here, I’ll park somewhere else.”	• Guaranteed access to EV chargers • Non-EVs kept out of charging spots • Clear navigation to EV-compatible sections	• EV chargers blocked by standard cars • Limited infrastructure • Spots appear “available” but unusable	• AI must classify EV vs. non-EV and direct accordingly • Dashboard tracks EV occupancy separately • Alerts for blocked or malfunctioning chargers