Metrics question

What metric would you track for Lyft's debit card program?

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

Whether you can pick a metric tree for a financial product that captures both adoption and the deeper behavior change it needs to drive.

Clarify the debit card's goal: likely driving Lyft earnings usage and building a sticky financial relationship with drivers.
Prioritize activation first: percent of eligible drivers who sign up and activate the card, since adoption is the foundation.
Track usage depth: percent of earnings loaded onto the card and spent through it, since a signed-up but unused card delivers no value.
Track a retention metric: percent of active cardholders still using it after 3 months, since the real goal is habitual use, not a one-time signup.
Add a guardrail metric: driver complaints or disputes related to the card, since financial products carry real trust risk if something goes wrong.
Tie the metrics back to Lyft's business goal, likely driver retention or reduced payout costs, not just card usage in isolation.

Builds a funnel from activation to usage depth to retention, instead of stopping at signup rate alone.
Prioritizes usage depth, earnings actually loaded and spent, since a dormant card provides no real value.
Names a trust-related guardrail, complaints or disputes, appropriate for a financial product's higher stakes.
Ties the metric choice back to Lyft's underlying business goal, driver retention, rather than treating the card as a standalone feature.

Tracking only signup rate, ignoring whether drivers actually use the card on an ongoing basis.
Ignoring the trust and dispute risk that comes with a financial product touching drivers' earnings.

Chapters of the AI PM course that teach what this question tests.