Metrics question

There is a data point that indicates that there are more Uber drop-offs at the airport than pick-ups from the airport. Why is this the case and what would you do within the product to change that?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Root cause reasoning about a real supply demand asymmetry and proposing a product lever to correct it.

State the likely cause, many airport arrivals choose other options, taxi lines, transit, or being picked up by friends, more than they choose this service for departure trips.
Consider driver behavior too, drivers may avoid airport pickups due to long queue times or per ride pay not covering the wait.
Separate the two possible root causes, rider preference on arrival versus driver supply reluctance, since the fix differs for each.
Propose a fix for the rider side, promotional pricing or guaranteed short wait times for airport pickups.
Propose a fix for the driver side, a queue time adjusted pay bonus for airport pickup trips.

Separates the two sides of the marketplace clearly, riders not choosing this service for arrivals versus drivers avoiding the queue, rather than one undifferentiated problem.
Names a specific driver side lever, a small guaranteed bonus for airport pickups to offset queue wait time, a known real practice in ride hailing.
Proposes measuring the fix by watching airport pickup fill rate and driver queue wait time together, not just total trip count.

Assuming the imbalance is purely a rider behavior issue and ignoring driver supply incentives.
Proposing a fix with no clear metric to measure if the gap actually closes.
Treating the imbalance as unsolvable rather than a normal marketplace balancing problem.

How would you balance the bonus cost against the extra revenue from closing this gap?
How would this differ at an airport with a designated rideshare pickup zone versus one without?