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.