Business Problem Solving and Recommendations Questions

Frameworks and skills for taking ambiguous business questions through analysis to clear, actionable recommendations. Includes decomposing complex problems into analyzable components, identifying key drivers, selecting focused analyses, synthesizing data backed findings, and articulating specific next steps and implementation considerations. Emphasizes communicating recommendations in business terms, estimating potential impact when possible, acknowledging trade offs and limitations, prioritizing among multiple actions, and tailoring communication to different stakeholders. Covers translating research or analytic results into feasible product or operational changes and defending choices with evidence.

HardTechnical

0 practiced

Design an A/B/n test with five variants for a homepage redesign. Explain how you would calculate required sample sizes accounting for multiple comparisons, how to pre-register primary and secondary metrics, which alpha-adjustment or sequential testing method you'd use, and what monitoring and stopping rules you'd enforce to prevent false positives.

EasyTechnical

0 practiced

An executive asks simply: 'Improve retention.' Describe step-by-step how you would convert this ambiguous request into a clear analytics brief. Include clarifying questions you would ask, hypothesis generation, the minimal data required, prioritized analyses, proposed deliverables, and estimated timelines for quick wins vs deeper studies.

HardTechnical

0 practiced

Discuss the trade-offs between precision and speed in BI analysis when leadership needs a rapid decision. Propose a policy that specifies acceptable levels of precision, confidence, and time-to-deliver for three decision categories (operational, tactical, strategic). Provide concrete examples or thresholds for each category.

MediumTechnical

0 practiced

Given two tables:

users(user_id INT, created_at TIMESTAMP)
orders(order_id INT, user_id INT, order_date DATE, total_cents INT)

Write a SQL query to compute monthly cohort retention: for each signup-month cohort, report the percent of users who made at least one order in month 0,1,...,6 after signup. Use window functions and explain how you treat users with no orders and timezone assumptions.

MediumSystem Design

0 practiced

Outline a plan to automate a weekly executive report that includes revenue summary, top customers, and churn signals. Include pipeline steps (extract/transform/load), schedule/cron strategy, data quality checks, notification or distribution method, and retry/rollback strategies so the report is robust and auditable.

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