One of the most effective ways to improve the performance of your website or online marketing campaigns is through A/B testing. A/B testing, also known as split testing, involves comparing two versions of a webpage or campaign element to see which one performs better. By testing different variations, you can gather valuable data on user behavior and preferences, allowing you to make informed decisions on how to optimize your content for better results.

Google Ads supports different kinds of experiments.

In each one you have different variables to test out and Google's idea behing them is to prove each product they are promoting works above others.

When conducting A/B tests, it's important to focus on one variable at a time to accurately measure the impact of changes. In each experiment that you launch inside Google Ads you need to select one Control group and one treatment. Making sure each one has comparable variables so you can test the uplift (or which one is working better)

Inside of Plai things are much simpler:

You can do pure AB testing as our reporting hub will show the metrics of each one alongside another. If you want to test a very specific variable then you need to duplicate your campaign and then just change the selected variable.

And now, with our Optimization folders you don't have to worry about manually changing things.

All you need are two campaigns (at least), think of control and treatment. You just have to put them inside the folder and our AI algorithm will take care of the rest. You can keep an eye on results in that same dashboard.

The 15 day cycle is ideal for the algorithm to gather basic concepts, and you can watch the different optimizations as they go.

Make sure to collect your results after the first 2 weeks have passed.

Key Lesson Concepts:

• A/B testing allows you to compare two versions of a webpage or campaign element to determine which performs better.
• Focus on testing one variable at a time to accurately measure the impact of changes.
• Analyze the results of your tests to gain insights and make data-driven decisions to optimize your content.