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type StopItProps<T> = {
  items: T[]
  callback: (item: T, index: number) => JSX.Element
}

const stopIt = <T,>(items: StopItProps<T>['items']) => (
  callback: StopItProps<T>['callback']
): JSX.Element[] =>
  items.map((item, i) => (
    <React.Fragment key={`corey-was-here-${i}-${Date.now()}`}>{callback(item, i)}</React.Fragment>

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A/B Testing: "Chance to Win" for Revenue Per User

Overview

Pack's A/B testing calculates a "Chance to Win" metric for each variant — the Bayesian probability that a variant outperforms the control. For revenue-based goals, this tells you the likelihood that a variant generates more revenue per user than the control.

The calculation happens in two stages:

1. BigQuery aggregates raw event data (total revenue, visitor counts, etc.) per variant
2. Bayesian Engine computes the probability that each variant beats the control