What should I use for multivariate testing?

If by multivariate testing you mean testing multiple variables at once to see which combination performs best, you’ll usually want a platform that can do MVT/experimentation, not just basic A/B testing.

Good options depending on your setup

For websites / product experiments

• Optimizely – strong enterprise-grade experimentation and true multivariate testing
• VWO – good for web optimization, easier to use, supports MVT
• Adobe Target – powerful, especially for larger organizations
• Google Optimize – was a common choice, but it has been discontinued

For app / product analytics + experiments

• Split.io – feature flags and experimentation
• LaunchDarkly – feature management with experiments
• Statsig – very strong for product experimentation and analysis
• Eppo – experimentation platform with good statistical tooling

For data science / custom analysis

• Python with libraries like:
  • statsmodels
  • scikit-learn
  • pyDOE / doepy for design of experiments
  • pandas + scipy
• R with:
  • DoE.base
  • FrF2
  • lm / aov

If you mean “what statistical method?”

For multivariate testing, you’ll usually use:

• Factorial design / ANOVA for analyzing effects and interactions
• Regression models if you want flexibility
• Bayesian experimentation if you want continuous decision-making or smaller-sample efficiency

Quick recommendation

• If you want an out-of-the-box tool: VWO, Optimizely, or Statsig
• If you want to build it yourself: Python + statsmodels
• If you only need simple UI tests, consider A/B testing first instead of full multivariate testing, since MVT usually needs much larger sample sizes.

If you tell me your context—website, app, email, pricing page, or analytics stack—I can recommend the best specific tool.