Prompt
Your team sees strong trial activity during week one, but very few users come back in week two. What metric view do you build first, and what would you recommend?
Answer shape
- Name the decision: onboarding, activation, acquisition quality, pricing, or product promise.
- Cut cohorts by source, role, team size, first successful action, and time to first value.
- Separate wrong-fit demand from product friction before you recommend a fix.
- End with one action, one risk, and the metric that would change your mind.
Need worked answers?
The Product Analytics packet includes case prompts, follow-up challenges, and scoring rubrics for this exact answer style.
Healthcare or insurance SQL?
If your product case uses claims, providers, billed amount, paid amount, or rejection rates, run the healthcare claims SQL rep first so the metric grain is not vague.
Direct purchase note
This is the public $59 self-guided packet path. If a coaching or mock-interview session already gave you access, use that access instead of buying the same packet again.
Need a 24-hour prep decision?
Run the self-check to choose the next rep from the real risk in your loop: SQL/OA, product case, metric debugging, or leadership story.
Public checkout is for self-guided packet buyers.
If a coaching, mock-interview, or private session already gave you packet access, use that private access and do not buy the same packet again. The public $59 checkout is for candidates buying the self-guided Product Analytics or Leadership packet directly.
Use Product Analytics for SQL, metrics, experiments, and product cases. Use Leadership for conflict, failure, ambiguity, influence, and final-round stories.
Run one timed rep before checkout.
Pick the risk you can fix today. Do the rep, then buy the packet only if it matches the round in front of you.
- SQL or OA: say the row grain first, solve one baseline query, then name the edge case that could break it.
- Product case: start with the decision, then give the metric view, segment, risk, and recommendation.
- Leadership loop: choose one conflict, failure, or ambiguity story and name the operating change you owned.
Last-mile check: pick the packet for the round you could lose.
Use the rep on this page first. If the weak spot is SQL, metrics, experiments, or product cases, get Product Analytics. If the weak spot is conflict, ambiguity, or final-round stories, get Leadership. Public checkout is $59 and separate from any private session access.