What is A/B/n Testing?
Key takeaway
A/B/n testing is the process of A/B testing with more than two different versions and differs from multivariate testing. The "n" refers to any additional tests. Despite these additional variations, though, A/B/n testing works the same way as standard A/B testing.
What is A/B/n Testing?
A/B/n testing is the process of A/B testing with more than two different versions. The little "n" doesn't refer to a third test, but to any number of additional tests: A/B/n encompasses A/B/C, A/B/C/D, or any other type of extended A/B test.
A/B/n testing is a matter of splitting users into groups, assign variations (typically of landing pages or other webpages) to groups, check the change of a key metric (typically conversion rate), check the test results for statistical significance, deploy the winning version.
A/B/n Testing vs. Multivariate Testing
Though they're often confused, A/B/n testing is not the same as multivariate testing. The key difference lies in how the variations are controlled. Let's use a webpage as an example. Say we have an image and a call to action (CTA) button, and we have three variations of each. If we run a multivariate test, it will automatically test all possible combinations -- in this case, 6. However, if we run an A/B/n test, we hand-select which variations we want to test, which is frequently less than every possible combination. If we had a large number of different resources we wanted to test, the number of different variations in a multivariate test would grow exponentially -- quickly requiring massive amounts of traffic and time it would take to get statistically significant results - but in an A/B/n test, we can manually choose how many variations to deploy.
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