Metrics question

There is an issue in a sign-up flow, users are no longer signing up for our service, what would you do?

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 diagnosis of a funnel drop, prioritizing quick, high confidence checks before deep investigation.

First check whether this is a tracking or measurement issue, like an analytics event firing incorrectly, since a sudden drop is often not organic.
Check for a recent change: a code deployment, a third party dependency like an email verification or SMS OTP provider going down, or a new sign up flow design.
Segment the drop: is it uniform across platforms and markets, or isolated to one, like a specific browser or country, pointing to a technical cause.
Look at the funnel step by step to find exactly where users are dropping off, not just that overall signups fell.
Check for external causes, like a payment or verification provider outage, or a competitor promotion pulling users away.
Once isolated, define the fix and a recovery target, like signups returning to baseline within a defined number of hours or days.

Leads with ruling out tracking and dependency issues before assuming organic user behavior changed.
Segments the drop by platform and geography systematically instead of guessing at a single cause.
Walks the funnel step by step to find the exact drop off point rather than treating signups as one black box metric.
Considers third party dependency failures explicitly, a common and often overlooked cause of sudden sign up drops.

Assuming the drop reflects a genuine shift in user interest before ruling out technical causes.
Not breaking the sign up flow into steps, missing exactly where the drop is occurring.

What would you check first in the initial hour after noticing the drop?
How would you communicate urgency to engineering if you suspect a third party outage?