configuring-experiment-analytics

What problem does it solve?

This skill guides teams through configuring experiment analytics, clarifying exposure criteria, metric setup, and results interpretation to determine impact.

Core Features & Use Cases

• Exposure criteria configuration: choose how users are counted (feature flag presses) or via custom exposure events, and handle test accounts.
• Metric configuration: select metric types (mean, funnel, ratio, retention) and specify steps for funnel metrics with automatic exposure step.
• Interpretation workflow: use project data schema discovery, select primary vs secondary metrics, and follow a decision framework for shipping or ending experiments.

Quick Start

Create an experiment analytics plan by documenting exposure criteria, selecting initial metrics, and outlining interpretation steps.