| name | ab-testing |
| description | Use when designing experiments for subject lines, offers, cadences, or journeys. |
Experimentation & A/B Testing Skill
When to Use
- Validating new subject lines or creative.
- Testing segmentation hypotheses (persona vs behavior).
- Optimizing cadence, timing, or automation triggers.
Framework
- Hypothesis – define expected uplift + rationale.
- Metric Selection – primary (open/click/conv) + guardrails (unsubs, spam).
- Sample Sizing – ensure stat significance (min 500 recipients per variant or use power calculator).
- Execution – randomize, keep variants isolated, limit simultaneous tests.
- Analysis – use z-test or Bayesian uplift; document learnings.
Templates
- Experiment brief (hypothesis, segments, KPI, risk guardrails).
- Variant table (control vs test inputs, creative asset links, owner).
- Calculator sheet for minimum detectable effect + sample size.
- Post-test debrief doc capturing learnings + rollout plan.
Experiment Ideas
- Subject line vs preview text combos.
- CTA placement (hero vs footer).
- Personalization depth (basic vs dynamic modules).
- Wait times between touches.
Tips
- Run no more than two tests per journey simultaneously.
- Recycle learnings into playbooks + automation templates.
- Segment results by persona to catch hidden signals.