Behavioral question

Can you give me an example where you made changes to your app based on user feedback?

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 actually close the loop with users, turning feedback into a shipped change and a measurable result.

Pick a specific piece of user feedback, ideally with a direct quote or a clear pattern across several users.
State the Situation and Task: what the feedback revealed and why it mattered enough to act on.
Describe the Action: how you validated the feedback was representative, not just one loud user, before building anything.
Explain the change shipped and why that specific version, not a bigger feature, addressed the root complaint.
Give the Result: the metric that moved, such as complaint volume dropping or a rating improving, after the change shipped.
Note what you would ask the interviewer if they want a case with quantified impact specifically.

Shows the feedback was validated as a pattern, not acted on from a single anecdote.
Describes a scoped fix tied directly to the root complaint, not a broad reimagining of the feature.
Quantifies the result, for example a support ticket category dropping by a stated percentage after launch.
Shows the loop closed with users, such as informing them the feedback led to the change.

Acting on one user's complaint as if it represented everyone, without checking for a pattern.
Describing the change but never stating a result or metric that moved afterward.

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