I’ve written a few articles before about the power of integrating Google Website Optimizer with Google Analytics, but the landscape has changed considerably in the past few months. I thought it would be a good idea to provide an update as to how you can view Google Website Optimizer and other kinds of experiment data within Google Analytics as it has become much easier with the addition of a magnificent feature called Advanced Segments.

As the title implies, this article will focus on finding data quickly and easily for A/B (or A/B/C/D, etc.) experiments, whether they be Google Website Optimizer experiments, or just some testing that you’re doing on your own.

First, why would you want to do this? Doesn’t Google Website Optimizer (or AdWords, etc.) provide you with Conversion Rate already? Sure it does! But I maintain that an aggregated Conversion Rate (for a single goal no less) is simply not enough. I demand more from my experiments, and by looking at my experiment data within Google Analytics, I can get a great idea of how the experiment is working for different segments of visits and for every goal on my site. What’s even better is that by using Google Analytics, I’ll also have access to transaction and revenue data, along with any powerful customizations that I’m already using to get the most out of my tracking.

Here are some of the benefits to using Google Analytics to measure your A/B experiment results:

I hope you’ll agree there these are some pretty massive benefits. So enough of my gabbing, here’s how to do all of this for an A/B test in two simple steps:

1. Create your Advanced Segments

This is the step that has made examining A/B tests within Google Analytics a joy instead of the awkward wobbling toddler of a process that it used to be.

Fortunately, now that Google Analytics has put on its big boy pants, creating these Advanced Segments is a relatively simple task. You can access Advanced Segments from one of two places. The most common place is in the top-right corner of the Google Analytics interface:


You can also access Advanced Segments from the link on the left-hand side of the interface:


Once you choose to create a new Advanced Segment, you’ll be taken to a screen that looks like this:


Since we’re looking at the efforts of landing pages here, you’ll want to select either Page or Landing Page from the list of dimensions on the left. You can simply type in ‘Page’ into the search bar to find them a little more easily.


Once you’ve done than, you can start typing the name of the page into the input bar and a list of the pages that match your string will pop up, allowing you to easily select the page you are looking for. If your site uses query parameters or URL variations, you may want to change the match type to ‘Contains’. You can even use Regular Expressions if you have more advanced needs.


Once you’ve created both segments, you’re ready for step 2.

2. Apply your Advanced Segments

The easiest way to apply the segments that you created is to use the dropdown menu in the top-right of the Google Analytics UI. You’ll see something like this:


Simply check the new segments that you’ve made and click on the Apply button. The report that you are looking at within Google Analytics will change to feature the new segments:


As you can see, there is some pretty powerful information here. The above report is an example of the AdWords Campaigns report that’s been enhanced with our Google Analytics Report Enhancer tool. As you can see, sometimes a page may be winning in one campaign and losing in another.

Also, you can see how conversions are faring for multiple steps in a single funnel, and you can segment the data even further by Ad Group, keyword, ad version, geographic location, and anything else you may need. You can even set the report up to show up in your inbox every morning!

The other great thing about looking at this data within Google Analytics is that you’ll have a record of the entire test’s performance over time. You can see how overall fluctuations in the marketplace, or snags with your server’s load times have impacted your test over time, and can exclude irrelevant data. I really can’t stress enough how powerful this kind of analysis can be.

That’s all there is to it! Please feel free to try this method out and leave comments – I’d love to hear your feedback or if you’ve found a better way to do this.