Feature Success Measurement Questions
Focuses on measuring the impact of a single feature or product change. Key skills include defining a primary success metric, selecting secondary and guardrail metrics to detect negative side effects, planning measurement windows that account for ramp up and stabilization, segmenting users to detect differential impacts, designing experiments or observational analyses, and creating dashboards and reports for monitoring. Also covers rollout strategies, conversion and funnel metrics related to the feature, and criteria for declaring success or rollback.
MediumTechnical
0 practiced
When reporting experiment results, when would you prefer confidence intervals over p-values? Describe how you would present both in a dashboard tile for product managers and executives, and how to interpret wide vs narrow intervals in the context of decision-making.
MediumTechnical
0 practiced
Given schemas:orders(order_id STRING, user_id STRING, placed_at TIMESTAMP, amount NUMERIC)users(user_id STRING, created_at TIMESTAMP, variant STRING)Write an SQL query to compute revenue per user (RPU) in treatment vs control for the 14-day post-exposure window. Additionally, explain how you would test whether RPU in treatment decreased significantly compared to control and recommend next steps if it did.
MediumTechnical
0 practiced
A feature was launched during a holiday week with known seasonality. How would you adjust your measurement to account for holiday and day-of-week effects when estimating the feature's impact? Describe modeling approaches or controls (e.g., time-series decomposition, regression with day dummies) you would use and how you'd validate your adjustments.
MediumSystem Design
0 practiced
Describe the essential real-time metrics and alerting logic you'd implement in an experiment monitoring dashboard used during feature rollout to quickly detect safety issues. Include technical constraints (latency, noise), guardrail thresholds, and escalation procedures for alerts.
EasyBehavioral
0 practiced
You meet a Product Manager asking 'we launched feature X, has it succeeded?' What structured questions would you ask to clarify success criteria and avoid common pitfalls before starting analysis? Cover scope, metric definitions, unit of analysis, cohort windows, segments, and acceptable trade-offs.
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