Running effective tests with multiple variants
Multivariant testing, similar to a/b/n testing, is often used when a change can be adapted into a single variable—operational parameters, text copy, colors, images—rather than a binary state, such as on or off.
It’s distinct from multivariate testing, where multiple variables are simultaneously being evaluated.
Statistical rigor is important with multivariant testing to ensure that the sample size is large enough and that the sample ratio is correctly split between each variation.
Multivariant testing with an experimentation platform
Split combines feature flags with your existing data pipelines to provide a comprehensive experimentation platform for frontend, backend, and mobile applications.
Split includes statistically rigorous analytics to ensure your sample sizes, sample ratio, and review period are properly aligned to your experiment.
Dynamic configurations make it even easier to run multivariant tests, allowing your team to adjust the variations without changing your code. Simply change key-value pairs or JSON and you can iterate on your experiment fast.