Metrics question

What metrics would you track to measure the success of ChatGPT Projects?

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 the candidate can define metrics for an organizational feature where success means sustained use, not one-time novelty.

Clarify the feature's job: Projects lets users group conversations and files around an ongoing task, so success means it reduces friction for recurring work.
Propose adoption metrics: percentage of active users who create at least one Project, and percentage who return to a Project after the first session.
Propose depth metrics: average number of conversations and files per active Project, showing it is used as intended, not just created once.
Propose a guardrail: churn rate of Projects, meaning created but abandoned within a set window, say two weeks.
Tie to business outcome: whether Project users show higher overall retention or upgrade rate than non-Project users.

Distinguishes creation from sustained use, since a Project created once and never revisited is not a success.
Proposes a concrete return metric, like percentage of Projects with a second session within 7 days, as the real signal of habit formation.
Connects Project usage to a business-level outcome, hypothesizing that Project users retain or upgrade at a higher rate, and proposes testing that correlation.
Flags a guardrail against a misleading vanity metric, like total Projects created, which could rise even if most are abandoned.

Measuring only Project creation count without checking whether Projects get revisited.
Ignoring the connection between this feature and broader retention or monetization outcomes.

What would you do if Projects are created often but rarely revisited?
How would you segment Project usage between individual and team-oriented use cases?