Design and run A/B tests
ab-testingskillsetup L2★24
Infrasity-Labs/dev-gtm-claude-skills ↗What it does
Design and analyze A/B experiments
Best for
When designing statistically valid experiments with pre-committed sample sizes and rigor.
Inputs
- · Baseline metric
- · Hypothesis
- · Expected lift percentage
Outputs
- · Sample size calculation
- · Test design document
Preconditions
- · Baseline conversion rate known
- · Traffic volume sufficient for sample size
Failure modes
- · Peeking at results early causes false positives
- · Sample size insufficient before stopping
Trust signals
- · Sample size tables with baseline/lift combinations
- · Evan Miller + Optimizely calculators linked
- · Peeking problem explicitly named