Metrics and KPI Fundamentals Questions

Core principles and practical fluency for defining, measuring, and interpreting metrics and key performance indicators. Candidates should be able to select meaningful metrics aligned to business objectives rather than vanity metrics, explain the difference between a metric and a target, and distinguish leading indicators from lagging indicators. Coverage includes decomposing complex outcomes into actionable component metrics, writing precise metric definitions such as what counts as a daily active user and monthly active user, calculating common metrics such as engagement rate, churn rate and conversion rates, establishing baselines and sensible targets, and interpreting signal versus noise including awareness of statistical variability. Also includes using segmentation and cohort analysis to diagnose metric movements and recommending two to three meaningful metrics for a hypothetical problem with justification and action plans.

MediumTechnical

0 practiced

Design a precise metric definition for 'engagement rate' for a news app where engagement might include article opens, time spent, shares, and comments. Specify numerator, denominator, time window, and how you would weight different actions (if at all). Explain trade-offs of a simple count-based metric versus a weighted engagement score.

EasyTechnical

0 practiced

Write an SQL query to compute monthly churn rate per acquisition cohort given a subscriptions table. Schema:

subscriptions(user_id bigint, start_date date, end_date date null)

A user is 'churned' in month M if end_date is within month M. Define cohorts by the user's start_date month. Compute churn rate per cohort for the first three months after acquisition.

MediumTechnical

0 practiced

Create a prioritized action plan (2–4 steps) for product and engineering after you detect a sustained negative trend in user retention in a key segment. For each action state the owner, data needed, metric to watch for improvement, and how you'd measure impact reliably.

HardTechnical

0 practiced

Write an SQL query to compute 30-day rolling churn rate for active subscribers using a table subscriptions(user_id, active_date, is_active boolean). The churn rate on day D should be (number of users who were active at any time in the prior 30 days but became inactive on day D) / (number of active users in prior 30 days). Clarify assumptions in your query.

MediumTechnical

0 practiced

Write an SQL query to compute a 7-day rolling average of daily DAU given an events table (events(user_id, occurred_at)). The output should be: date, dau, dau_7day_avg. Use ANSI SQL and ensure deduplication per user per day.

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