Metrics question

There is a 15% drop in the open rate of Instagram App. You are the PM. Tell us what could have happened.

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

Structured diagnosis of a metric drop in a consumer app, distinguishing measurement, product, and external causes.

Clarify the metric: open rate likely means sessions per notified or notification-eligible user, so confirm the exact definition first.
Check for an instrumentation change, like a new event schema or a tracking SDK update, before assuming real behavior changed.
Segment by platform, region, and whether the drop correlates with a recent app release or notification permission change (like iOS App Tracking Transparency).
Check push notification delivery rates, since a drop in notifications sent or delivered would look like a drop in opens.
Look at content quality signals, like whether feed content freshness or creator posting volume dropped, reducing the reason to open.

Flags OS-level changes, like notification permission prompts or iOS privacy changes, as a common real-world cause worth checking first.
Separates 'fewer people notified' from 'notified people opening less,' since the fix differs for each.
Gives an illustrative segmentation, e.g. the drop concentrated in one region after a local competitor launch, marked as an assumption.
Proposes a guardrail dashboard split by notification type (post, DM, live) to isolate which trigger underperforms.

Assuming content quality dropped without first ruling out measurement or delivery issues.
Not distinguishing open rate from raw session count, which can mask the real signal.

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