Product Manager Metrics & Interview Cases
Build a north-star metrics tree, measure DAU/MAU stickiness, funnels and day-N retention, track feature adoption, root-cause a metric drop with mix vs. rate effects, size a feature's impact and prioritise with RICE, with every cell checked as you go.
The first lesson is free — no account needed.
About this course
A product manager metrics course that prepares you for the analytical part of PM interviews and of the job, on one meal-planning app's data. You compute the north-star metric from its input metrics and find the input that is quietly getting worse, measure DAU/MAU stickiness and blend two platforms correctly, compare onboarding funnels step by step and size the prize of fixing the leak, build day-N retention curves for two install cohorts, measure feature adoption, engagement depth and power users, split a drop in trial-to-paid conversion into a mix effect and a rate effect, size a new feature's yearly revenue in a low, base and high case with its break-even conversion lift and rank a backlog with RICE scores against the team's capacity. The first lab is free.
Lessons
- North-Star Metric and the Input Metrics TreeFree
- DAU, MAU and Stickiness Pro
- Funnel Conversion and Drop-off by Platform Pro
- The Retention Curve: Day-N Retention Pro
- Feature Adoption and Engagement Depth Pro
- Root-Causing a Metric Drop: Mix vs. Rate Effect Pro
- Sizing a Feature's Impact (Estimation Case) Pro
- Prioritisation with RICE Scoring Pro