Sample size and duration fixed before launch
Calculated from your baseline rate and the smallest effect worth detecting. Stopping when a result looks good is the single largest source of fake wins in this discipline.
A running experimentation programme: hypotheses from the audit, sample sizes calculated before launch, and results recorded whichever way they go.
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The problem
Most testing programmes produce false wins. The test is stopped the day it looks significant, four metrics are checked until one moves, and the "27% uplift" does not survive into the quarterly numbers.
Calculated from your baseline rate and the smallest effect worth detecting. Stopping when a result looks good is the single largest source of fake wins in this discipline.
Secondary metrics are monitored for harm, not for a win. Checking enough numbers guarantees one of them will look significant by chance.
Traffic behaves differently by day of week. A test run Tuesday to Friday measures Tuesday-to-Friday visitors, not your customers.
A negative result is information about your customers and it is worth as much as a win. Without a record, teams re-test the same idea every eighteen months.
Tools we use
The questions we get asked most, answered without the sales gloss. If yours is not here, ask us directly — you will get a straight answer either way.
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