Context
Turno is a US marketplace that connects cleaners with hosts of short-term rentals, like those listed on Airbnb and Booking. The data showed that of every 100 cleaners who signed up, only 2.5% reached the end of the journey. The team didn’t know why people dropped off at each stage, and had no metric to track the journey.
Research question: why do new cleaners drop off at each stage of the journey, and what should we measure to track it?
Approach
The data showed where and how many people dropped off. To understand the why behind each bottleneck, I split the interviews into groups: people who had dropped off at each stage of the process.
One challenge was the low response rate from one-time users. We addressed it with incentives such as Amazon gift cards.
Findings
Each bottleneck had its own problem.
Split by stage, the interviews made clear the main problems at each point where people dropped off.
Many people stopped right at the start.
At the first stage, people didn’t remember the product well or hadn’t understood how it worked.
The wait between stages reached 25 days.
Between some journey stages, the gap was 25 days on average. The reason was confusion about the next step.
Outcome
The team gained a metric for the journey: the amount of drop-off at each stage and the goal of reducing time at the 80th percentile.
The findings also guided improvements built by the design team: explainer videos and clear, upfront information on how to set up an account.
Some details have been omitted for confidentiality.