Product Decisions and Business Outcomes Questions

This topic examines how product strategy and decisions drive business metrics. Candidates should show how feature prioritization, pricing, positioning, and go to market choices connect to key performance indicators such as acquisition, activation, retention, revenue, and lifetime value. Expect evaluation of frameworks for prioritization, methods for estimating and measuring product return on investment, experiment and rollout strategies, funnel analysis, and how to set measurable success criteria and objectives for product initiatives. Communication with stakeholders and alignment to company goals should also be covered.

HardTechnical

0 practiced

Implement in Postgres SQL a method to compute time-decayed fractional attribution of conversions across multiple touchpoints per conversion. Given touches(user_id, channel, touched_at) and conversions(user_id, conversion_at, amount), produce channel-level attributed conversions where each touch is weighted by weight = exp(-lambda * hours_since_touch). Show how you normalize weights per conversion and explain how you would pick lambda.

MediumSystem Design

0 practiced

Design an A/B test to increase onboarding completion on a web product. Specify the primary metric, guardrail metrics, sample size estimation approach (inputs and formulas), randomization method, and recommended rollout plan. Assume WAU of 50,000 and current onboarding completion of 20%.

EasyTechnical

0 practiced

You have ten analytics requests from sales, product, marketing, and finance. Describe a simple, defensible prioritization approach (criteria and scoring) you would apply to decide which dashboard/report to deliver first and how you'd communicate the decision to stakeholders.

MediumTechnical

0 practiced

You notice trial-to-paid conversion dropped 8% this month. Create a prioritized six-step analysis plan to diagnose the cause using BI tools and data sources, focusing on fast wins to identify likely drivers quickly.

EasyBehavioral

0 practiced

Tell me about a time you explained a change in a product metric to non-technical stakeholders (e.g., PMs, sales). Describe the situation, the analysis you performed, how you framed the findings to the audience, and the outcome.

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