Running A/B tests is the surest way to victory.

[Shakil1984]

As discussed, there’s no single, perfect way to measure the efficacy of your marketing efforts, channels, and messages. Nonetheless, A/B testing is the most time-tested way to scientifically and continuously improve your results.

At a high level, A/B testing is about splitting your visitors into two or more groups, showing different content to each group, and then measuring which group results in more conversions.

In the personalization world, you’ll usually have an assumption (or perhaps a groundbreaking idea) for personalization that you want to test—this is called your hypothesis.

Then, you go ahead and sweden consumer email list create your personalized message. In order to see if it works, you’ll split the segment you’re targeting in two—showing your new personalized content to one half (which we call the test group) and the “standard” version to the other half (which is often called the control group).

After you collect enough data about the performance of these two groups (which is usually called statistical significance), you can evaluate the results and decide whether your hypothesis was true or false.

If it was true, your personalized message will result in more conversions or revenue and you can feel confident running this new message variant to 100% of your target audience. If it was false and you’re not making any extra conversions (or money), you can simply cancel it and go back to doing what you were doing before you tried out your groundbreaking idea.

Why? Because you have an extremely limited downside, but an unlimited upside.

If your hypothesis turns out to be false, then you can just simply stop the experiment. The only loss will be (at most) a couple of conversions among the test group who saw the new message during a short period of time.