Proper A/B test setup: clear hypothesis, single variable, sufficient sample.
Tests need enough data for statistical significance. Below that, you're looking at noise.
95% confidence is the standard. Below that, your result is likely noise.
Shipping more tests = more learning. Velocity compounds over quarters.
Prioritize tests by potential impact × ease. Here's the priority order.