Get-e driver app

The first driver app, launched in 2019, struggled to gain traction. Drivers had to keep it open on screen, adoption was low, and key features were missing, such as flight tracking, vehicle identification, reliable updates. In 2024 we released a redesigned version with a cleaner experience, verified driver and vehicle profiles, and effortless ride tracking. This time, drivers wanted to use it.

As the sole product and UI designer, I was responsible for shaping the new features and redesigning the experience. My focus was on simplifying the driver flow while ensuring tracking and reliability for passengers.

To understand the pain points, I interviewed drivers, gathered feedback from our ops team and customers, and studied mobility apps like Uber and Bolt, plus logistics tools. Three big issues stood out:

These insights showed us that the app was asking too much from drivers while giving too little in return, and that the tracking experience on the customer side was unreliable.

The vehicle identification flow was one of the trickiest features. Drivers confirm the vehicle for each ride by selecting model and colour and uploading up to three photos. Before the ride starts, the app validates this information and displays it to the passenger.

The design challenge was balancing detail with speed: capture enough data to help passengers, but keep the flow short and clear for drivers. We tested variations, built shortcuts, and allowed a way out if details could not be provided immediately.

One of the hardest problems in this project was how to keep passengers reliably informed about their ride: on one side, we introduced automated ride updates based on speed and location. But determining exactly when to update a ride is not simple. Conditions change constantly, and a threshold that works in one situation may be wrong in another.

On the other side, we needed to give drivers a way to communicate directly with passengers without relying on phone calls. In many cases, language barriers or international numbers made calling ineffective. A lighter, contextual way of signalling delays or sharing status was essential.This tension between automation and communication became a central design challenge, and solving it required multiple iterations.

Another big challenge was deciding when the app should automatically progress a ride. Speed and location data were not always enough. For example, a driver slowing down near an airport could mean they were arriving, stuck in traffic, or taking a wrong turn.

To make this more reliable, we designed an area-based logic. Each airport or hotel location was mapped with an inner zone and an outer zone, defined according to the size of the airport or the position of the hotel. Entering or exiting these zones would trigger status updates more accurately, while still leaving drivers the option to adjust if something was wrong.

This approach reduced errors, gave passengers more consistent tracking, and took pressure off drivers to manually update their status.

The redesigned driver app replaced a clunky tool with a clear, reliable experience. Drivers now receive contextual guidance at every step, can confirm their vehicle and upload photos, and have quick options to notify passengers of delays without the need for a call. Ride statuses progress automatically based on location and speed, with the driver able to step in when needed. For passengers, this means accurate live tracking and clear identification of their driver and vehicle.