Checking an A/B test daily until the p-value drops below 5 percent can inflate the false-positive rate to almost 28 percent. A simulation of identical A/A tests (10% conversion, 1,000 visitors per arm, 30 days) found that peeking daily raised false positives from the nominal 5% to 27.7 percent. Among tests that crossed the threshold, half did so by day five—when the sample is most fragile.

Even when a real effect exists (e.g., 10% true lift), stopping at first significance overstates the lift by about a quarter, because crossing early requires an unusually favorable swing. This inflated number then drives revenue forecasts and roadmap decisions, risking disappointment.

The fix is to use methods that account for repeated looks. Options include a fixed-sample design (hold to pre-planned end), group-sequential Pocock boundary (stricter threshold, e.g., z=2.73), or always-valid p-values that remain reliable no matter when you peek. Each preserves validity while allowing practical monitoring.