Easy interview questions in Growth & Experimentation, page 2
How would you instrument a key activation milestone event?
Tests schema design beyond a bare event name. A strong answer includes the event key, user ID, timestamp, and properties like project_id and is_first_project. Red flag: omitting the user ID or sending only a human-readable label without structured context.
Implement a 10% onboarding tutorial feature flag and track success
Tests lightweight experiment design and metric selection beyond vanity numbers. Strong answers cover user-ID bucketing, conversion tracking, and guardrail metrics like drop-off. Red flag: manual toggles or click-through without downstream outcomes.
What data and approach for a simple 30-day DAU forecast?
Tests forecasting from sessionized logs without overengineering. Cite timestamped events, a 30 min session rule, and a regression baseline with day-of-week, recent totals, scored with MAE. Red flag: deep learning before a baseline or ignoring privacy hashing.
Why is extrapolating 5% weekly growth naive for annual forecasting?
This tests knowledge of extrapolation limits. A strong answer cites market saturation, seasonality, and channel exhaustion as invalidating factors, and notes that compounding 5% over 52 weeks magnifies error.
What differentiates leading and lagging indicators for subscriptions?
Leading indicators forecast; lagging indicators confirm. Subscriptions: activation rate leads, MRR lags.
Trace an event from click to analysis
Client SDK captures and batches, a collection endpoint ingests, a stream and ETL enrich and load into a warehouse for analysis.
How would you implement a simple feature flag system?
Tests runtime config separation and distributed hygiene. Outline: control service, datastore, API, SDK, and update mechanism; local evaluation with cached state; short-lived flags. Red flag: static config files requiring redeployment are not feature flags.
Why consistent user IDs matter in experiments
The user id seeds deterministic bucketing and ties events to one person across devices; achieve it via authenticated ids and anonymous-to-known stitching.
Lifecycle of a feature flag experiment from creation to cleanup
Tests operational rigor across the full flag lifecycle. A strong answer covers six stages: SDK instrumentation with event tracking, phased rollout, monitored experiment, ship/kill decision, and code cleanup.
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