Every email marketer thinks they know what works. Most of them are guessing. A/B testing replaces opinions with data. Here's how to do it right.
What A/B Testing Is (and Isn't)
A/B testing means sending two versions of an email to small portions of your list, measuring which performs better, then sending the winner to everyone else. That's it. It's not complicated. But most people do it wrong.
It's not: Testing 5 things at once. Changing the subject line, the CTA color, the hero image, and the send time simultaneously. If version B wins, you have no idea which change caused it.
It is: Testing one variable at a time. Subject line A vs Subject line B. Everything else identical. Clear winner. Clear lesson.
What to Test (In Priority Order)
1. Subject lines — Highest impact. A good subject line can double your open rate. Test length (short vs long), personalization (with name vs without), emoji (with vs without), tone (urgent vs casual), and specificity ("50% off" vs "Huge savings inside").
2. Send time — Morning vs evening. Tuesday vs Thursday. Test with your specific audience — "best send times" articles are based on averages that may not apply to your subscribers in India.
3. CTA buttons — Button text ("Shop Now" vs "See the Collection"), color (orange vs green), placement (above fold vs below), and size. CTAs directly impact click-through rates.
4. Email length — Short and punchy vs detailed and thorough. This varies dramatically by industry and audience.
5. Personalization — Beyond first name. Test product recommendations based on browse history vs generic bestsellers. Test location-based content vs universal content.
How to Run a Proper Test
Sample size matters. Testing with 50 people per variant is meaningless — random noise will dominate. You need at least 1,000 subscribers per variant for reliable results. If your list is smaller, test over multiple sends.
Pick one metric. For subject line tests, measure open rate. For CTA tests, measure click rate. For content tests, measure conversion rate. Don't try to optimize for everything at once.
Run it long enough. Don't call a winner after 2 hours. Wait at least 24 hours — some people check email at night. 48 hours is better.
Statistical significance. A 51% vs 49% split means nothing. You need at least a 5% difference with a 95% confidence level. Most email platforms (including BestEmail) calculate this for you.
Common A/B Testing Mistakes
Testing too many variables. One thing at a time. Always.
Stopping too early. The first hour's results are misleading. Wait for full data.
Not documenting results. Keep a spreadsheet of every test: what you tested, the results, and what you learned. Patterns emerge over months that single tests can't reveal.
Testing trivial things. Button color (blue vs slightly different blue) rarely matters. Focus on changes that could meaningfully impact behavior.
Ignoring context. A subject line that wins during Diwali might lose in January. Seasonality, day of week, and audience mood all affect results.
Build a Testing Calendar
Don't test randomly. Plan one test per campaign:
- Week 1: Subject line length
- Week 2: Send time
- Week 3: CTA wording
- Week 4: Content format
After a month, you'll have four solid data points. After six months, you'll know your audience better than any competitor who's just guessing.
The Payoff
Companies that A/B test consistently see 20-30% improvements in email performance over 6 months. Not from one magical test, but from dozens of small wins compounding. Each 2% improvement in open rate, each 3% boost in click rate — they add up to real revenue.