Question 1

How do I know if my A/B test result is significant?

Accepted Answer

Use a two-proportion z-test at 95% confidence. Enter sends and conversions for each variant — if the p-value is under 0.05, the difference is statistically significant and you can trust the winner. This calculator does the math instantly.

Question 2

How many emails do I need for an A/B test?

Accepted Answer

Aim for at least 500–1,000 sends per variant before calling a winner. Smaller samples produce noisy results — a variant can 'win' by luck. The lower your baseline conversion rate, the more sends you need.

Question 3

What should I A/B test in cold emails?

Accepted Answer

Test one variable at a time: subject lines first (biggest lever on opens), then the opening line, the call-to-action, and email length. Never test subject + body together — you won't know what caused the difference.

A/B test calculator

When is an A/B test result trustworthy?

Questions, answered

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