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Email Marketing Glossary.

Clear, no-fluff definitions of every email marketing term that matters—from open rates to double opt-in. 

 

Multivariate Testing

Multivariate testing (MVT) tests multiple email elements and their combinations simultaneously to find the best-performing mix — a more complex alternative to single-variable A/B testing.

Also known as: MVT, multivariate test

Where A/B testing compares two versions differing in one thing, multivariate testing examines several elements at once and how they interact — revealing the winning combination, not just the winning variable.

How does multivariate testing work?

You vary multiple elements (say, subject line, hero image, and CTA), generate combinations, and measure which combination performs best. It requires a large audience to reach reliable results.

Multivariate testing vs. A/B testing

A/B testing isolates one variable and needs less traffic; MVT tests many variables and their interactions but demands a much larger sample for statistical significance.

When should you use multivariate testing?

Use it when you have high volume and want to optimize several elements together. For most senders and quick wins, A/B testing is more practical.

Frequently asked questions

What is multivariate testing?
Multivariate testing (MVT) tests multiple email elements and their combinations at once to find the best-performing mix. It's a more complex alternative to A/B testing, which changes just one variable.
How does multivariate testing work?
You vary several elements — such as the subject line, hero image, and CTA — generate combinations, and measure which combination performs best. It requires a large audience to produce reliable results.
What's the difference between multivariate and A/B testing?
A/B testing isolates a single variable and needs less traffic to reach significance. Multivariate testing examines many variables and their interactions but requires a much larger sample size.
When should I use multivariate testing?
Use it when you have high send volume and want to optimize several elements together. For most senders and faster wins, single-variable A/B testing is more practical and reliable.
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