How to Create a Content Experiment in Google Analytics

http://www.morevisibility.com/analyticsblog/how-to-create-a-content-experiment-in-google-analytics.html July 24th, 2012 by

In my last post, I discussed the deprecation of Google Website Optimizer and Google’s Announcement of Content Experiments in Google Analytics.  As a quick reminder, Website Optimizer is a testing tool that automates A/B and multivariate experiments.  Content Experiments is an A/B testing tool that is integrated into Google Analytics.  The benefits of such integration are many:

  • Less code to implement
  • Analyze and test from the same interface
  • Easier to deploy (See the first bullet above)

Creating A Content Experiment in 7 Easy steps.

So you may be thinking, “Seven steps?  In the GA interface there are only 4 steps!”  And you are correct, there are four steps to creating an experiment, but there are three critical prerequisites.

  1. As you have probably discerned, a Content Experiment is for testing another version of content. You will need to have already identified a critical page in your conversion funnel or an underperforming landing page to test.
  2. After selecting your test case or “A” page, you need to have a hypothesis to test.  For example, if you move the shipping cost calculations to this page/step in the checkout flow, more visitors will proceed to the next step and purchase your products.
  3. Once you have your hypothesis of how to make your conversions jump, you’ll need someone (creative team, vendor, freelancer) to create the new design/ functionality etc. of the B page that incorporates your great new idea(s).
  4. Once you have the prerequisites complete; drill into the GA Interface and go to Content>Experiments and enter the location of the page you want to improve.
  5. Enter the location of the “B” version of the page that you’d like to test.
  6. Set your options.  Remember that you must have goals configured and the larger the audience, the faster you’re likely to have a winner declared.
  7. Add extra, system generated coding to the “A” Page and have GA verify that all elements are in place.

So the final step is to launch your experiment.  In our next post, we’ll explore some next steps and best practices once the experiment is complete.  For now, you should know that once you’ve launched the experiment, GA will dynamically serve your “B” page instead of the original page at the rate that you’ve determined in step 6 above.  Once the system has enough data to determine which page (A or B) is more effective; it will declare a winner and you’re on your way to more conversions!

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