As digital marketers, we can no longer rely on JUST our intuition when deciding what will resonate with our audience. Instead, we need hard facts and in-depth analytics to point us in the right direction for the best conversion optimization — and that’s where A/B testing comes into play.

So what is an A/B test? A/B testing is a simple way to test your current design (A) against changes to your page/email/ad (B) and determine which one produces the most positive results.

If you have a website, you have activities that you want your users to complete (e.g., make a purchase, sign up for a newsletter) and/or metrics that you want to improve (e.g., revenue, session duration, bounce rate). With Content Experiments, you can test which version of a landing page results in the greatest improvement in conversions (i.e. completed activities that you measure as goals) or metric value. You can test up to 10 variations of a landing page.

Content Experiments uses a somewhat different approach than standard A/B and multivariate testing. Content Experiments uses an A/B/N model. You’re not testing just two versions of a page as in A/B testing, and you’re not testing various combinations of components on a single page as in multivariate testing. Instead, you are testing up to 10 full versions of a single page, each delivered to users from a separate URL.

What you can do with Content Experiments in Analytics

With Content Experiments, you can:

Compare how different web pages or app screens perform using a random sample of your users
Define what percentage of your users are included in the experiment
Choose which objective you’d like to test
Get updates by email about how your experiment is doing
An example of using experiments to improve your business
Let’s say you have a website where you sell house-cleaning services. You offer basic cleaning, deep cleaning, and detailed cleaning. Detailed cleaning is most profitable of the three, so you’re interested in getting more people to purchase this option.

Most users land on your homepage, so this is the first page that you want to use for testing. For your experiment, you create several new versions of this web page: one with a big red headline for detailed cleaning, one in which you expand on the benefits of detailed cleaning, and one where you put an icon next to the link to purchase detailed cleaning.

Once you’ve set up and launched your experiment, a random sample of your users see the different pages, including your original home page, and you simply wait to see which page gets the highest percentage of users to purchase the detailed cleaning.

When you see which page drives the most conversions, you can make that one the live page for all users.