How KINTO Join Found the Real Drop-off in Its Carpool Flow
KINTO Join is a mobile app for sustainable commuting. Its Booked Carpool feature lets drivers plan a carpool in advance and record the journey on the day of the trip, so it counts.
91%
of drivers who opened their booking on the day recorded the journey
1 in 3
drivers never came back to the app on departure day
1 afternoon
from setup to pinpointing the drop-off
The Challenge
When Booked Carpool shipped, the demo went smoothly and the team moved on to the next item on the roadmap. Weeks later, a simple question came up. Is anyone actually using it?
The team could see how many people opened the screen and how many taps it got. But those numbers couldn't show whether drivers got what the feature promised them. That promise was certainty, a trip secured in advance and a journey recorded without extra effort.
The flow also doesn't happen in one sitting. A driver might book on Monday evening and record the trip on Tuesday morning. To see the whole picture, the team needed measurement that follows drivers across sessions and days.
We can usually say how many people opened the screen. We can pull a chart of taps. But those numbers rarely tell us the thing we actually care about: whether the feature is solving the problem it was meant to solve, for the person it was meant to help.
The Solution
Sima Ercevic, UX Lead Designer at KINTO Join, pointed three UXCam tools at the same flow. Funnels showed where drivers dropped off. Session replay showed why. Heatmaps showed what caught their attention on the screen.
He set up a three-step funnel. Drivers created a reservation, opened it on the departure day and started recording the journey. Over one month, about 64% of drivers who booked a carpool went on to record it.
The funnel showed where the loss happened. About 91% of drivers who opened their booking on the day recorded the journey, so the final step worked. The real gap came earlier. Nearly a third of drivers never came back to the app on the day at all.
Session replays added the why. In one session, a driver opened the ride details, swiped and checked again before starting the journey. That small double check is invisible in a funnel, but it shows a person making sure they picked the right trip.
The heatmap of the bookings screen confirmed the rest. Taps clustered on the booking cards, visits lasted only a few seconds and rage taps appeared in under 1% of visits. Once drivers reached the screen, the experience worked.
Setup was light. Sima marked a handful of key moments in the flow and went from a question to a clear answer in the same afternoon.
What made it click for me wasn't any single feature but that connection: the numbers and the human behaviour behind them live one click apart.
What’s next?
The data pointed the team away from redesigning the bookings screen. The opportunity sits before drivers open the app, in the moment they need a nudge to come back on the day of the trip.
Sima also wants measurement to become a habit. Instead of saving analytics for flagship launches, the goal is to define a few key moments for nearly every feature the team ships.
You can learn more about the app on the KINTO Join product page.
Read Sima’s full write-up, Measuring Feature Success Without Losing Sight of the User, on Medium.
If defining a few key moments is cheap, the question stops being “is this feature important enough to measure?” It becomes “why would we ship anything without knowing whether it worked?”