Metrics question

Let's say you notice a 50% increase in customer support tickets. 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

Triage skill for a support volume spike, connecting it back to a likely product or operational root cause.

Confirm the spike is real and check the timeframe against historical support ticket baselines.
Segment tickets by category, like billing, bugs, or account access, to find which topic is driving the increase.
Check for a recent change: a new release, a pricing change, or an outage that coincides with the spike.
Check external factors: a viral social post, a press mention, or a competitor issue driving unusual traffic.
Prioritize the top category by volume and severity, then loop in the relevant team to address root cause.
Propose a short term mitigation, like an FAQ or in-app banner, while the underlying fix is developed.

Segments tickets by category first rather than treating the 50 percent increase as one undifferentiated blob.
Names a concrete first hypothesis, a recent release or outage, as the most common real world cause of sudden spikes.
Proposes an immediate mitigation, like an FAQ banner, to reduce user frustration while the real fix is built.
Prioritizes by both volume and severity, not just ticket count, since a small but severe category matters too.

Jumping to a fix before segmenting tickets to find the actual driving category.
Ignoring the possibility of an external cause like a viral post or press mention.

How would you prioritize between a high-volume minor issue and a low-volume severe issue?
How would you prevent a similar spike from support volume in the future?