A/B testing involves comparing two versions (A & B) of a marketing asset, such as an email, landing page, or ad copy, to see which will be the most effective at achieving a specific goal.

When A/B testing, it's important that you look at a large enough sample size that your data becomes meaningful. A/B testing with a small audience can lead misleading results as just one or two people can throw off your conclusions.

It's also crucial to establish upfront what you're measuring. All-too-frequently, marketers will suggest running an A/B test to prove an idea, but if you don't know what success looks like, no amount of testing will give you an answer!

Great A/B tests are run when there's a large enough sample size to make the testing worthwhile and meaningful, and a clear understanding of what the desired successful outcome looks like.