How to define a north star metric and supporting KPI tree for improving Uber Eats, covering orders per user, delivery time p50/p95, restaurant NPS, and gross merchandise value.
A step-by-step framework for answering 'a metric dropped 20%, why?' interview questions, covering 5 whys, funnel analysis, segmentation, and hypothesis testing.
A structured product sense framework for the classic 'Design a product for blind users' interview question, covering accessibility, screen readers, voice interfaces, and haptic feedback.
A full, structured walkthrough of the 'design a product for senior citizens' product sense interview question, from clarifying questions to prioritized solutions.
A calibration rubric interviewers actually use to score 'design a product for senior citizens' answers, with dimension-by-dimension breakdowns of great vs. good vs. poor responses.
How to choose a defensible north star metric, supporting input metrics, and counter metrics for a senior-focused product, plus A/B testing pitfalls specific to this population.