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Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.
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ab-test-setup.SKILL.md
---name: ab-test-setup
description: "Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness."
risk: unknown
source: community
date_added: "2026-02-27"
---# A/B Test Setup
## 1️⃣ Purpose & Scope
Ensure every A/B test is **valid, rigorous, and safe** before a single line of code is written.
- Prevents "peeking"
- Enforces statistical power
- Blocks invalid hypotheses
---## 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
---
- **Multivariate Test (MVT)** – interaction effects, very high traffic
- **Split URL Test** – major structural changes
Default to **A/B** unless there is a clear reason otherwise.
---
## 6️⃣ Metrics Definition
#### Primary Metric (Mandatory)
- Single metric used to evaluate success
- Directly tied to the hypothesis
- Pre-defined and frozen before launch
#### Secondary Metrics
- Provide context
- Explain _why_ results occurred
- Must not override the primary metric
#### Guardrail Metrics
- Metrics that must not degrade
- Used to prevent harmful wins
- Trigger test stop if significantly negative
---
## 7️⃣ Sample Size & Duration
Define upfront:
- Baseline rate
- MDE
- Significance level (typically 95%)
- Statistical power (typically 80%)
Estimate:
- Required sample size per variant
- Expected test duration
**Do NOT proceed without a realistic sample size estimate.**
---
### Tracking Verification (Required before Gate 8)
Before entering the Execution Readiness Gate below, run through this checklist to make "Tracking is verified" mean something concrete:
1. **Event firing:** Trigger each event the primary and secondary metrics depend on (sign-up, add-to-cart, custom event) on staging or a debug page, and confirm it lands in your analytics destination within 30 seconds.
2. **Variant attribution:** Verify that the variant assignment ID is attached to every fired event — not just the entry event. Use your analytics' raw event view to compare a sample of 5+ events per variant.
3. **De-duplication:** Confirm that a user reloading the page does not cause double-counted events. If your stack uses client-side de-duping, the variant ID must be part of the dedup key.
4. **Sample randomization:** Pull the first 100 assignment records from your assignment table; the variant split should be within ±5% of the configured allocation.
5. **Guardrail metric pipeline:** Each guardrail metric defined in §6️⃣ must have a working dashboard or alert by the time the test launches.
If any of the above fails, stop and resolve it before Gate 8.
---
## 8️⃣ Execution Readiness Gate (Hard Stop)
You may proceed to implementation **only if all are true**:
- Hypothesis is locked
- Primary metric is frozen
- Sample size is calculated
- Test duration is defined
- Guardrails are set
- Tracking is verified
If any item is missing, stop and resolve it.
---
## Running the Test
### During the Test
**DO:**
- Monitor technical health
- Document external factors
**DO NOT:**
- Stop early due to “good-looking” results
- Change variants mid-test
- Add new traffic sources
- Redefine success criteria
---
## Analyzing Results
### Analysis Discipline
When interpreting results:
- Do NOT generalize beyond the tested population
- Do NOT claim causality beyond the tested change
- Do NOT override guardrail failures
- Separate statistical significance from business judgment
