Strategy question

Imagine you get user feedback to build a video scrubber on TikTok. 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

Judgment on evaluating a single piece of user feedback against broader product priorities before committing to build it.

Clarify how widespread this feedback is, one user or a recurring theme across many support tickets and reviews.
Assess the underlying need behind the request for a scrubber, likely precise navigation within longer or more complex videos.
Check whether TikTok's short, algorithm driven format actually needs this, since most videos are brief and linear viewing already works.
Weigh the cost of building scrubbing against higher priority needs if video length or format does not commonly warrant it.
Decide with a data backed next step, such as checking average video length trends before committing engineering time.

Does not immediately agree to build it, instead validating the underlying need against actual usage data and video length trends.
Considers that as TikTok videos get longer, a scrubber becomes more valuable, reasoning through the trend rather than reacting to one request.
Proposes measuring interest first, like tracking how often users try to scrub on longer videos today, before full investment.

Building a feature based on a single piece of feedback without checking broader demand.
Ignoring how TikTok's short form format might make this feature lower priority than it seems.

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