Defining Success for a Pandemic-era Transit App
rideCAT Mobile Fare App Research
A city transit agency launched a mobile fare app mid-pandemic, but they didn't have a plan to measure the launch, or a way to see who it was leaving behind. I interviewed riders and drivers in English and Spanish to find out. Awareness, onboarding, and equity gaps were keeping riders off the app, and drivers had no resources to help. My research gave the agency their first qualitative baseline and KPIs, and four years later, their 2025-2026 fare study tracked the same barriers.
Digital ad via Collier Area Transit
Project Details
Client
Collier Area Transit (CAT)
Team
Myself; a Spanish language translator for in-person interviews and survey translation
Role
User Researcher
Methodology
Field Observations, In-Person Interviews, Paper Surveys
Timeline
Spring 2021, Four weeks
The Problem
Collier Area Transit (CAT) launched a contactless ticketing app during the COVID-19 pandemic as a public-health intervention and a modernization of fare collection. They had analytics on app usage that showed what riders did, but had no way to understand why, and they couldn't see who was being excluded.
There was no meaningful way to set success metrics, prioritize improvements, or understand whether the communities most reliant on public transit were actually being served by this solution.​​
Alex Driehaus/Naples Daily News/USA TODAY - FLORIDA NETWORK
The Impact
I gave CAT its first baseline on how riders, both app users and non-users, experience the app. I also gave them recommendations for closing adoption gaps, including KPIs they could track by comparing fare and ridership data against app usage, and I brought drivers into the picture as an overlooked adoption channel.
Four years later, CAT’s 2025-26 Fare Study asks riders the same awareness and usage questions I asked and found the same barriers: riders who didn’t know about the app or didn’t know how to use it.
What I Did and Why
As a one-person research team, I ran nine days of field research at a major transfer hub and onboard buses, interviewing and surveying app users, non-app users, and bus drivers in English and Spanish.
CAT's analytics only tracked who used the app. Field research found out who didn't, and why.
Midway through the study, I realized that drivers were missing from the picture. They were the riders’ only resource when the app failed, and the app had changed how they collected fares. No one had asked them how it was working, so I added them to the study.
With no budget beyond a part-time Spanish language translator, I couldn’t cover more times or locations, so I paired live interviews with paper surveys to reach more riders in the time I had.
26 App Users
(20 in-person interviews,
6 paper surveys)
56 Non-App Users
(18 in-person interviews,
38 paper surveys)
16 Bus Drivers
across various routes
and times
What I Found
FINDING:
App users loved the app, but they still ran into occasional glitches and the validators failed to scan. They also asked for more language options so they could fully understand what the app could do.
EVIDENCE:
Among 26 app users, several described scanning two or three times before it worked. The failed scans traced back to legacy farebox hardware, which CAT had already flagged in its Ten Year Development Plan, so the app was taking the blame for an infrastructure problem.
RECOMMENDATION:
Post large, clear steps for using the scanner at the farebox, in English, Spanish, and Creole, to reduce failed scans and confusion at boarding while the hardware upgrade was pending, and add Spanish and Creole language options in the app so users could access all of it's features.
FINDING:
Awareness gaps, onboarding friction, and equity barriers kept many riders from adopting the app, and none of these showed up in CAT's analytics.
EVIDENCE:
Across 56 non-app riders, most hadn't heard of the app or didn't know how to set it up. Language was also a barrier, Spanish and Creole support turned out to be essential for reaching the riders who relied most on transit. Many riders had basic phones, or smartphones with limited battery or data, and those without a bank account or card found reloading fares cumbersome.
RECOMMENDATION:
Place marketing posters and takeaway brochures near the farebox and the driver, where riders decide how to pay. I also recommended KPIs that compare fare and ridership data against app usage, so CAT could track who the app was reaching over time.
FINDING:
Drivers were an untapped adoption channel.
EVIDENCE:
All 16 drivers I interviewed liked the app, but none had resources to help riders use it. Drivers were riders' only source of help when the app failed, and the app had changed how they collected fares, yet no one had asked them how it was working.
RECOMMENDATION:
Give drivers training and an FAQ guide, so they could confidently answer riders' questions about the app.
What I Learned
Field research with transit users taught me to scope the population and conditions before finalizing methods, not during the study. Spanish and Creole support turned out to be essential, and that wasn’t apparent at the start. I also learned to adapt quickly, using shorter, more direct questions in plainer language.
Since then, I do preliminary research on who I’ll be talking to and where before designing the study.