Split Testing
Testing two or more email variations with different audience segments to determine which performs better.
Definition
Split testing (also called A/B testing) is the practice of sending different email variations to separate audience segments to determine which version performs better. You might test subject lines, content, CTAs, send times, or design elements. Statistical analysis determines the winner, which can then be sent to the remaining audience or inform future campaigns.
Why It Matters
Split testing removes guesswork from email optimization. Instead of assuming what works, you gather data on actual performance. Even small improvements compound over time - a subject line that performs 5% better delivers significant additional engagement across all future campaigns using that learning.
How It Works
Divide your audience into equal segments. Send each segment a different variation (changing only one element at a time). After sufficient data (usually hours), compare performance metrics. The variation with better results wins. Apply learnings to future campaigns.
Example
Subject line A/B test example:
Test audience: 10% of list (5% get A, 5% get B) Remaining audience: 90%
Version A: "Your weekly marketing tips" Version B: "5 tips that increased our conversions 40%"
Results after 4 hours: Version A: 18% open rate Version B: 27% open rate
Winner: Version B sent to remaining 90%
Best Practices
- 1Test one variable at a time for clear learnings
- 2Ensure test groups are large enough for statistical significance
- 3Wait for sufficient data before declaring a winner
- 4Document and apply learnings to future campaigns
- 5Test continuously - audiences and best practices evolve