A method of testing two variants of something, like a web page, marketing campaign, or even just the label on a login button (or maybe that's Sign In, instead?).
Use Interana’s A/B view to understand the results of your A/B tests. For example, you can examine the results of tests for new layouts, user flows, email subjects, recommendation algorithms, colors, rankings, or new features. Then use filters to drill down into your data and identify the statistically significant results.