Cold email A/B testing guide (what to test and how)
Test one variable at a time — subject, first line, CTA, or send time — measure on reply rate (not opens), and give each test enough volume to be real. Here's a disciplined A/B testing approach.
Short answer: A/B test cold email by changing one variable at a time (subject line, first line, CTA, or send time), measuring on reply / positive-reply rate rather than opens (which Apple MPP inflates), and giving each variant enough volume to be statistically meaningful before you call a winner. Test the highest-leverage element first — usually the first line and the CTA, not the subject.
What to test (in order of impact)
- First line / hook — relevance drives replies most.
- CTA — low-friction ask vs direct ask.
- Subject line — short/specific vs curiosity.
- Send time / day.
- Length — shorter usually wins.
How to test properly
- One variable per test — or you can't attribute the result.
- Measure replies, not opens.
- Enough volume — a 20-email test proves nothing; aim for hundreds.
- Kill the loser, scale the winner, then test the next variable.
Autocloz A/B-tests variants per step and reports reply + positive-reply rate, so you optimise on the metric that books meetings.
> Start free — A/B test on replies and compound the wins.