Metric Selection & Product Instrumentation Questions
Techniques for turning vague business questions into measurable, actionable product metrics. Includes identifying leading vs. lagging indicators, upstream vs. downstream metrics, aligning metrics with company strategy, balancing multiple stakeholders (user satisfaction, business growth, content value), and recognizing when metrics can be misleading or require multiple signals to capture impact.
EasyTechnical
0 practiced
A/B test designers often pick 'click-through-rate' as a metric for content changes. Propose two alternative metrics that may better capture long-term content value and explain the instrumentation required to support them.
HardSystem Design
0 practiced
Propose a mechanism to attribute revenue lift in a multi-touch product where users interact with email, push, and in-app recommendation systems. Describe required instrumentation, attribution windows, and how you'd handle overlap and carryover effects.
EasyTechnical
0 practiced
Define the difference between a leading indicator and a lagging indicator in the context of product metrics. Provide two concrete examples of each for an e-commerce mobile app, and explain why each example fits its category.
HardTechnical
0 practiced
You are asked to build a small model that predicts whether a daily-active user will become a long-term retained user. Describe the metric selection process for features (which product metrics you would include and why), how you would instrument them, and how you'd evaluate model utility beyond AUC.
HardTechnical
0 practiced
A marketplace product tracks transactions to measure liquidity. Propose a metric suite that captures both short-term transactional health and long-term marketplace quality. Include definitions, how to handle multi-sided attribution, and what instrumentation is necessary.
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