Use when designing an A/B or split test: define the hypothesis, control and variants, estimate sample size, verify tracking, and predeclare metrics and stopping rules.
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What the file says
# A/B Test Setup
## 1️⃣ Purpose & Scope
Define an experiment that can answer a specific product question, and verify its assumptions before exposing users. This procedure cannot guarantee validity by itself.
- Documents the stopping rule
- Estimates sample needs under stated assumptions
- Makes the hypothesis and decision criteria reviewable
---
## 2️⃣ Pre-Requisites
You must have:
- A clear user problem
- Access to an analytics source
- Roughly estimated traffic volume
### Hypothesis Quality Checklist
A valid hypothesis includes:
- Observation or evidence
- Single, specific change
- Directional expectation
- Defined audience
- Measurable success criteria
---
## 3️⃣ Hypothesis Lock (Hard Gate)
Before designing variants or metrics, you MUST:
- Present the **final hypothesis**
- Specify:
- Target audience
- Primary metric
- Expected direction of effect
- Minimum Detectable Effect (MDE)
Use the hypothesis already agreed in the task. If a launch-critical choice is missing, present the concrete choice for confirmation while continuing independent analysis. Do not repeatedly request approval for a decision already authorized.
---
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