Behavioral question

You are a product manger at Facebook. You want to build a Yelp-like restaurant search product. How will you convince your engineering team and product manager team to build it? (use existing metrics on the platform).

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

Cross-functional influence and data-driven persuasion skill, pitching a new feature to skeptical peers.

Situation: set up the real ask, proposing a local restaurant-search and reviews feature to skeptical engineering and product peers.
Task: state the expected resistance, limited engineering capacity, competing roadmap priorities, and doubt about differentiation from existing search products.
Action: describe using existing platform metrics as evidence, for example Local or Events engagement, or Page check-ins and reviews already showing organic demand.
Action: describe building a lightweight prototype or data-backed proposal projecting engagement lift, to de-risk the ask before requesting a full build.
Action: describe aligning incentives, tying the pitch to an existing team OKR, like local commerce growth, rather than a brand-new initiative.
Result: state the outcome, securing a scoped pilot with clear success criteria and the actual or projected metric movement.

Uses real existing signals, Page reviews, check-ins, Events engagement, as evidence rather than asserting the idea is good on intuition.
Shows a concrete de-risking step, a prototype or pilot, instead of asking for a big commitment outright.
Ties the pitch to already-existing team priorities, a realistic and effective influence tactic.

Relying purely on personal conviction with no data brought to the table.
Asking for a full build commitment without proposing a smaller, lower-risk first step.

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