feature-metrics

Define success metrics for a product feature experiment using the STEDII framework to ensure your metrics are sensitive, timely, easy to understand, directional, implementable, and independent. This guarantees experiment results are well-defined and interpretable.

The STEDII framework for product metrics is a quality validation structure ensuring your experiment metrics are Sensitive, Timely, Easy to Understand, Directional, Implementable, and Independent. It guides the selection of primary metrics, guardrail metrics, and kill criteria.

Set up guardrail metrics and kill criteria for feature launches by analyzing product context, business information, and historical data. This ensures the feature is successful without causing negative side effects like increased error rates or page load delays.

You can use existing product documents to inform experiment metric selection by integrating business information and historical data into the STEDII framework. This contextualization facilitates the selection of trustworthy primary metrics and guardrails.

Use primary metrics versus guardrail metrics in product management when you need to measure the main success of a feature, while guardrails ensure no negative side effects occur. Defining both using the STEDII framework ensures trustworthy experimentation.