Multivariate Testing

Test multiple variables simultaneously to determine optimal combinations for achieving specific goals.

Research Classification

Research Type

Attitudinal Behavioral

Behavioral: Focuses on what people do: their actual behaviors and actions.

Data Type

Qualitative Quantitative

Quantitative: Collects numerical data that can be measured and statistically analyzed.

Requirements

Budget

high

Significant investment required

Timeline

long

4-8 weeks

Team Size

small

Works with 2-3 people

Research Goals

evaluation

Pros & Cons

Pros

  • ✓ Tests multiple variables simultaneously
  • ✓ Identifies optimal combinations of elements
  • ✓ Reveals interaction effects between variables
  • ✓ Provides comprehensive optimization insights
  • ✓ More efficient than sequential A/B tests

Cons

  • × Requires very high traffic volumes
  • × Complex to set up and analyze
  • × Longer time to reach statistical significance
  • × May be difficult to interpret results
  • × Resource-intensive implementation

Use Cases

Example Scenario

Testing different combinations of headline, image, and call-to-action on a landing page to find the highest-converting combination.

Additional Applications

  • • Landing page optimization
  • • Form design optimization
  • • Pricing page testing
  • • Product page layout testing
  • • Email campaign optimization