Every auth change raises the same two questions: did we break anything, and how hard can we push? Experiments answers both with a randomized A/B test on your real login traffic.
Completion lift per variant against control
Error-rate guardrail against silent breakage
Health check before you trust the result
Test the change instead of arguing it
Teams A/B test checkout buttons. The login ships on a hunch. Experiments brings the same discipline. Method Uplift shows where to start.
Proving the new thing better comes second. The error guardrail blocks a variant that wins completion but breaks more logins.
Auto-trigger the passkey prompt or let users start it? One dismissed dialog is lost conversion. Test both and ship the winner.
Experiment health checks volume, traffic balance and sample-ratio mismatch. A bad split is flagged before it feeds you noise.
Modal, banner or inline prompt? Auto-trigger or user-initiated? Stop arguing in review meetings. Tag the variants and read the answer.
Completion lift against control, the error-rate guardrail and the probability that a variant truly wins. Experiment health flags volume, traffic balance and a bad split before you read any lift.
Common questions about A/B testing authentication
Your login is the highest-traffic funnel you own. Give it the same experiment discipline. Start by measuring your mix with Method Uplift.