Daily A/B Test Checks Inflate False Positives, Study Shows

Repeatedly checking an A/B test's p-value each day dramatically increases the chance of declaring a false winner, according to a statistical analysis published on DEV Community. A standard p-value threshold of 0.05 is only valid when data is collected to a fixed sample size and tested once, not monitored continuously. Simulations show that checking results 20 times — equivalent to four weeks of daily weekday monitoring — produces a false positive roughly 25% of the time, even when both variants are identical. Experts recommend fixing a sample size in advance, using sequential testing methods like O'Brien-Fleming boundaries, or reporting confidence intervals instead of binary significance calls. The core advice is to define a stopping rule before any data is collected, and to run fewer, larger experiments on changes substantial enough to reliably detect.