Design metrics and an A/B test for an app

Pick a consumer digital app you love. Assume the interviewer knows nothing about it. 1) Explain the product, core jobs-to-be-done, target audience segments, and top three competitors, including the app’s differentiators. 2) Enumerate all current revenue streams and unit economics; propose one new revenue stream with a six-month ROI model. 3) Define three precise, computation-ready success metrics for the new stream (each with numerator, denominator, event/window definitions) and two guardrail metrics with thresholds. 4) List six concrete product improvements for the app; prioritize one to ship first and justify the choice. 5) Experiment design: run an A/B test for the prioritized improvement—state unit of randomization, eligibility/exclusions, assignment, and bias mitigations. Compute the minimum sample size and test duration using these inputs: daily active users = 500,000; baseline conversion-to-purchase per user-day = 15%; expected absolute lift = +2.0 percentage points; power = 80%; two-sided alpha = 5%; 1:1 split. State assumptions and show the formula you’d use. 6) If finance challenges that the improvement is too costly, present your cost-benefit model, the breakeven point, and the decision you’d make if interim results underperform the MDE after two weeks.