How do A/B tests differ from multivariate tests, and when would you use each?

• A. A/B tests are less reliable than multivariate tests and should always be used together.
• B. A/B tests compare two page variants; multivariate tests analyze multiple elements simultaneously; use A/B for simpler changes, multivariate for complex page optimizations.
• C. A/B tests compare two page variants; multivariate tests analyze three variants.
• D. A/B tests measure time-to-conversion, while multivariate tests measure click-through.

Answer: (B)

A/B testing compares two versions of a page to isolate the impact of a single change, while multivariate testing looks at several page elements at once to understand how different combinations interact and what mix performs best. Use an A/B test when you want a simple, clear answer about one specific change and you have enough traffic to detect a difference. Opt for multivariate testing when your goal is to optimize a page holistically by evaluating how multiple elements work together, which requires more traffic to reliably identify the best combination. The option described captures these ideas by noting two variants versus multiple elements analyzed together and by recommending A/B testing for simpler changes and multivariate testing for more complex page optimizations. The other statements don’t fit because reliability rules aren’t universal for A/B vs multivariate, multivariate isn’t limited to exactly three variants, and the distinction isn’t primarily about different metrics like time-to-conversion versus click-through.