314,552 interview questions from 6,000+ companies.
Define campaign success using business KPIs, funnel conversion, acquisition cost, and leading indicators tied to outcomes.
Explain how visualization tools help analysts track KPIs, spot patterns, and support decisions.
Explain SQL window functions and when to use ROW_NUMBER() versus DENSE_RANK() for ranked ticket analysis.
Calculate CAC and compare it with LTV to decide whether an acquisition campaign is economically viable.
Reason about sample size, power, and minimum detectable effect before launching an experiment.
Explain how you run user research and convert feedback into clear, prioritized product requirements.
Explain how you use visualization tools to report KPIs clearly and connect leading and lagging indicators for decision-making.
Framework for segmenting users so personalization reflects distinct needs, intents, and product value.
Explain when to use first-touch, last-touch, or multi-touch attribution based on business goals, funnel structure, and measurement limits.
Decide which features belong in an initial launch versus a later phase.
Evaluate whether a campaign is reaching the right user segment and driving the intended behavior.
Explain how to clean messy campaign data using SQL with validation, NULL handling, and structured transformation steps.
Compare ROAS measurement methods across digital and offline channels, including attribution, cost treatment, and conversion linkage.
Quantify statistical power for an email A/B test and explain why a small sample may miss a real 2-point lift in open rate.
Explain how to validate dashboard metrics by reconciling source data with SQL aggregations and grouped checks.
Investigate why FinFlow's CAC rose 31% while conversion stayed flat by decomposing spend, traffic mix, and acquisition efficiency.
Define and calculate LTV for a subscription business, separating monthly and annual plans and accounting for churn and costs.
Determine whether a higher email campaign conversion rate is statistically significant using a two-proportion z-test.
Use joins, a CTE, and aggregation to compute 30-day conversion rate by acquisition channel and customer segment.
Design an A/B experiment for a promotional email and test whether a 1.0 percentage point lift in 7-day conversion is statistically significant.
23 total questions
