A/B Testing

An A/B test splits your live traffic between two versions — a control (A) and a variant (B) — and measures which produces more of the action you want. It replaces "I think this is better" with "the data shows this is better".

Change one meaningful thing at a time so the result is interpretable, and decide your sample size and success metric before you start. Respect the statistics: calling a winner before you reach adequate volume and significance is how teams confidently ship changes that quietly hurt. Watch the downstream metric, not just the immediate click — a variant that lifts signups but tanks paid conversions is not a winner.

The senior skill is knowing when A/B testing is the wrong tool. Many B2B pages simply do not get the traffic to reach significance in a reasonable time, and waiting for it stalls progress. In those cases, sequential testing, painted-door tests, qualitative research, or a confident redesign backed by strong reasoning are more honest than a test that will never conclude. Testing is a means to learn, not a ritual to perform.