experiment-brief

An A/B test requires a clear hypothesis, a single north star metric, and concrete guardrails with thresholds before statistical design work begins. Defining these elements upfront ensures your experiment is powered and defensible.

State your experiment intent in plain language to generate a structured brief. This brief automatically formulates your hypothesis, identifies a north star metric, and establishes pre-registered success criteria.

Yes, you can validate baselines against live data when provided. This validation ensures all decisions in your experiment brief are concrete with no placeholders before proceeding to statistical design.

The best way is to generate an experiment brief that defines concrete guardrails with specific thresholds before testing begins. This prevents unintended negative impacts on your north star metric during product validation.

Generate an experiment brief to obtain a concise feasibility estimate alongside your hypothesis and success criteria. This assesses whether your planned A/B test is practical before handing off to statistical design.

Avoid using an automated experiment brief if you cannot provide baseline data for validation or if your product change lacks a clear intent to test. The brief requires concrete inputs to enforce no placeholders.