Google Experiments is an A/B testing tool that is available within Google Analytics interface. This post is not about what A/B testing is, why you should conduct A/B tests and what other tools are available but really to make a case for using Google Analytics as your testing platform. I am not getting paid to write this or have any affiliation with Google. This post is in response to a question I received from a reader of my blog.
- Free –There is absolutely no cost for the Tool. You can’t beat Free, it is a great way to start with A/B testing and learn about how testing works. I strongly recommend that you try this tool before moving to more sophisticated paid tools. Additionally, if you are just trying to make a case for Testing within your organization then cost does become a barrier and this tools removes that barrier.
- Easy To Setup – Easy to use wizard allows you to choose the pages to test and setup test parameters.
- Easy Implementation – Once you are done with setting up (point 2 above) the page(s) you want to test, you have to implement some code on your site. It may sound daunting but that code is very easy to implement. Google provide you the code after your setup is done and all you have to do is stick that on your pages. Since you already have Google Analytics installed, you are already half way through. Easy setup makes it easy for you to cross the IT/development team barrier.
- Setting up Objective– If you have already defined the Goals in Google Analytics, you can use them as the objective of your test. During your setup you can pick a goal that you have already defined in Google Analytics as your desired optimization objective. If you have not defined them already then you can quickly define them while setting up your test.
- Segments – Many tools just gives you the final results based on the data of entire population or based on some predefined segments. In case of Google Experiments, you can pick Segments that you have defined in Google Analytics and see how each variation is performing for each of your segment. Since not all segments behave in similar fashion this kind of analysis helps you drive even more conversion by understanding which variation of your pages(s) work better for which segments.