Estimation question

How will you measure the impact of cancellation fees?

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

Estimation and metrics design: structuring how to isolate and measure the causal impact of a specific policy change.

Clarify the policy: a new or changed cancellation fee on bookings, and confirm what 'impact' means, e.g. revenue or booking behavior.
Identify the metrics to track: direct fee revenue collected, and secondary effects like changes in booking or cancellation rates.
Propose a measurement method, such as an A/B test comparing markets with and without the fee, or a before-and-after comparison with controls.
Address confounding factors, like seasonality or unrelated pricing changes that could distort a simple before-and-after comparison.
Define the final read-out: net revenue impact after accounting for any drop in bookings caused by the new fee.

Proposes a controlled comparison (A/B test or matched control group) rather than a naive before-and-after look.
Names a specific secondary effect to watch, like customers avoiding bookings altogether to dodge the fee.
Addresses confounding factors explicitly, like seasonal demand shifts that could bias a simple comparison.
Frames the final metric as net impact, combining fee revenue gained against any booking volume lost.

Measuring only direct fee revenue and ignoring behavioral side effects like reduced bookings.
Using a naive before-and-after comparison with no control for confounding factors.
Not defining what 'impact' means precisely before proposing a measurement method.

How would you isolate the fee's effect from seasonal booking trends?
What would you do if the fee increases revenue but also increases cancellation-avoidance behavior?
How long would you wait before drawing conclusions from this data?