experimentation-and-ab-testinglisted
Install: claude install-skill social-media-skills/skills
# experimentation-and-ab-testing
The **causation engine** — manipulate one variable under controlled conditions to learn what actually
moves a KPI. This skill **designs** the test and drafts variants; **scheduling-and-queue → WoopSocial**
publishes them; **analytics-and-reporting** reads the result.
## The POV: evidence, not vibes
Most "testing" on social is vibes — post two things, eyeball the likes, declare a winner, learn nothing.
Real experimentation turns guesses into evidence: change **one variable**, control everything else, set
the **decision rule before you publish**, and run it **long and often enough** to separate signal from
noise. Organic can't give clean statistical significance (small samples, an algorithm in the middle), so
you compensate with tighter controls, a **~20%+ effect threshold**, **guardrail metrics**, and **3–5
repetitions** — and treat a single viral post as **noise, not a strategy.**
## Read these first
1. **brand-profile** — voice/format constraints for the variants.
2. **goals-and-kpis** — the **KPI/primary metric** the test must move.
## The framework: TEST
(Depth: `references/the-test-framework.md`.)
- **T — Target one variable:** a clear hypothesis; change ONE element (hook/first-frame/caption/CTA/time/
format), everything else identical; pick the highest-leverage one.
- **E — Establish the decision rule first:** set the **primary metric + win threshold + guardrail** before
publishing ("B wins if reach +15% and saves/reach not worse"