How does MVT differ from A/B testing?

A/B testing changes one element between versions, isolating its impact. You learn whether subject line A outperforms subject line B, all else being equal.

MVT changes multiple elements across many versions, measuring how combinations perform together. You learn which overall configuration works best, including how elements interact.

Key differences:

Sample size: A/B needs moderate samples. MVT needs exponentially larger audiences as variables multiply.

Complexity: A/B is simple to design and analyze. MVT requires more sophisticated statistical analysis.

Insights: A/B tells you which single element wins. MVT reveals optimal combinations and interaction effects.

Speed: A/B tests complete faster with smaller audiences. MVT takes longer to reach significance.

A/B testing is a scalpel for precise questions. MVT is a broader instrument for holistic optimization. Most programs should master A/B before attempting MVT.