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.
MediumTechnical
0 practiced
You're scoping a 6-week pilot to reduce cart abandonment by 10% in a mobile app. Define the primary success metric and supporting metrics, specify target thresholds, describe how you'd estimate sample size or minimum detectable effect, list constraints (budget, time, traffic), and outline a roll-back and scale plan based on results.
EasyTechnical
0 practiced
When scoped for a new reporting request from a non-technical stakeholder, outline the key questions and steps you would use to gather requirements. Include sample clarifying questions about audience, decision cadence, desired frequency and format, required data sources, and success criteria.
HardSystem Design
0 practiced
Design an enterprise metric governance process and a metric catalog: include roles (metric owner, steward), canonical metric definitions, versioning, code-of-record, automated tests, documentation standards, and mechanisms to enforce adoption across analytics teams and dashboards.
HardSystem Design
0 practiced
Design a measurement strategy to compute unique users and cross-device engagement metrics under GDPR constraints while minimizing PII storage. Describe approaches such as salted hashed identifiers, differential privacy, or aggregated bucketing, list trade-offs between accuracy and privacy, and explain how you would validate measurement accuracy.
HardTechnical
0 practiced
Design an approach to measure the incremental impact of a large marketing campaign when seasonality and overlapping promotions exist. Describe experimental design (randomized holdouts or geographic holdouts), analysis methods such as difference-in-differences or uplift modeling, operational constraints, and how you would allocate budget for testing.
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