Business Context and Metrics Understanding Questions
Understand the broader business context for technical or operational work and identify relevant performance metrics. This includes recognizing the key performance indicators for different functions, translating technical outcomes into business impact, scoping a problem with success metrics and constraints, and using metrics to prioritize trade offs. Candidates should demonstrate how they would frame a problem in business terms before proposing technical or operational solutions.
HardTechnical
0 practiced
Design a composite 'customer satisfaction' metric that combines NPS survey responses, CSAT scores, product usage signals (time on key workflows), and support ticket sentiment. Explain how you would normalize different scales, choose weights, handle missing signals per customer, validate that the composite correlates with business outcomes (like retention), and how you would present the composite's interpretation to stakeholders.
MediumTechnical
0 practiced
Given tables:users(user_id varchar, acquired_at date, acquisition_channel varchar)transactions(transaction_id varchar, user_id varchar, amount decimal, occurred_at date)Write an ANSI SQL query to compute 30-day LTV per acquisition cohort grouped by week (cohort_week). Output: cohort_week, users_in_cohort, total_revenue_30d, ltv_per_user_30d. Explain assumptions about refunds and timezones in one sentence.
HardSystem Design
0 practiced
Design a metrics pipeline to support near-real-time dashboards for a company ingesting 1 billion events per day. Requirements: under 60-second freshness for key KPIs, support hourly and daily aggregates, allow backfills and reprocessing, provide strong data-quality checks and lineage, and keep costs reasonable. Describe architecture choices (ingestion, streaming vs batch, storage, aggregation), SLAs, and how canonical metrics will be served to BI tools.
HardTechnical
0 practiced
Daily active users are up 25% but average revenue per user (ARPU) is down 18% in the same period. Propose a structured root-cause analysis: list the analyses you would run (segmentation by cohort, acquisition channel, device; cohort revenue curves; price or promo checks), hypothesized explanations, and prioritized actions you would recommend to product and finance.
HardTechnical
0 practiced
Your company plans to launch in Country X in 12 months. As lead data analyst, list the KPIs and success metrics you would set for market entry (e.g., market share targets, CAC, activation rate, payback period), the data sources required (surveys, partners, digital signals), and a 12-month measurement roadmap with decision gates for go/no-go at three milestones.
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