Metrics Tests

A/B Testing + GA4 — Intermediate

Aligning experiment design with GA4: primary metrics and key events, variant tracking, consent gaps, session vs assignment splits, and attribution pitfalls when comparing test results to analytics reports.

A/B Testing — Advanced

Advanced experimentation: interference, switchback/cluster designs, sequential testing, heterogeneous effects, and decision quality under uncertainty. Mix of single-answer and multiple-answer items.

A/B Testing — Intermediate

Power, sample size, novelty effects, SRM, multiple metrics, and interpreting practical vs statistical significance. Mix of single-answer and multiple-answer items.

A/B Testing — Beginner

Basics of experiments: control vs treatment, primary metrics, random assignment, and common beginner mistakes. Mix of single-answer and multiple-answer items.

Funnel Metrics — Advanced

Advanced funnel systems: selection effects, incrementality, multi-sided loops, measurement breaks, and portfolio optimization. Mix of single-answer and multiple-answer items.

Funnel Metrics — Intermediate

Applied funnel analysis: windows, cohorts, activation design, channel mix, and diagnosing leaks with experiments. Mix of single-answer and multiple-answer items.

Funnel Metrics — Beginner

Funnel fundamentals: conversion, activation, retention, drop-off diagnosis, and common metric mistakes. Mix of single-answer and multiple-answer items.

North Star Metric — Advanced

Advanced NSM design: causal loops, portfolio trade-offs, gaming detection, multi-sided products, and executive alignment. Mix of single-answer and multiple-answer items.

North Star Metric — Intermediate

Choosing, validating, and operationalizing an NSM: inputs, guardrails, segmentation, and anti-patterns. Mix of single-answer and multiple-answer items.

North Star Metric — Beginner

What a North Star Metric is, how it differs from vanity metrics, and how teams use it day to day. Mix of single-answer and multiple-answer items.