Data Driven Decision Making Questions

Using metrics and analytics to inform operational and strategic decisions. Topics include defining and interpreting operational measures such as throughput cycle time error rates resource utilization cost per unit quality measures and on time delivery, as well as growth and lifecycle metrics across acquisition activation retention and revenue. Emphasis is on building audience segmented dashboards and reports presenting insights to influence stakeholders diagnosing problems through variance analysis and performance analytics identifying bottlenecks measuring campaign effectiveness and guiding resource allocation and investment decisions. Also covers how metric expectations change with seniority and how to shape organizational metric strategy and scorecards to drive accountability.

MediumTechnical

31 practiced

Given a funnel: Visit -> Signup -> Activation -> Paid, describe how you would compute conversion rates at each stage and perform an attribution analysis to identify which step loses the most users. Explain how you would use stratified segmentation (by source, country, device) to prioritize interventions.

HardTechnical

27 practiced

You are building an attribution model across web and mobile app that must be computed nightly and fed into dashboards. Explain the key data engineering and modeling steps you would take to ensure deterministic, auditable attribution outputs, and how you would version and test metric calculations.

MediumTechnical

28 practiced

Create a plan to measure the effectiveness of a referral program where users invite friends and both parties receive rewards. Include how to track referred users, avoid fraud, define success metrics, and compute incremental lift over a reasonable attribution window.

HardTechnical

30 practiced

A senior leader requests a new company scorecard with five top-level KPIs. Explain the process you would follow to select those KPIs, how you would align them to teams, and how you would design the scorecard to prevent perverse incentives or metric gaming.

MediumTechnical

36 practiced

Write a SQL query to compute churn rate for a subscription product where churn is defined as no activity and no renewal within 30 days after subscription end. Table: subscriptions(subscription_id, user_id, start_date, end_date, auto_renew boolean). Return monthly cohort churn rates. State assumptions about overlapping subscriptions and data gaps.

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