For about 5 years now, marketing professionals have been using Google’s Website Optimizer to run A/B tests and Multivariate tests on webpages. Google recently announced that Website Optimizer will be replaced with Content Experiments. Content Experiments offers similar functionality as Website Optimizer with a few limitations; however, I’ll highlight the top features that I think Content Experiments offers. Here are my top 5 features for Content Experiments when compared to Web Site Optimizer:
Content Experiment’s integration within Google Analytics is much improved compared to Web Site Optimizer. Web Site Optimizer did not integrate with Google Analytics, which limited a user’s ability to obtain additional information about the test variations for each experiment such as time on site, bounce rate, or the possibility of segmentation.
The simplistic workflow to implement an experiment is streamlined as well. The process went from 5 basic steps to 4 basic steps. The set-up wizard for the experiment clearly identifies where you are within the set-up process and the next steps. In addition, there are icons to help you throughout the process to understand what you’re doing.
The simple workflow is enhanced with visuals of the experiment variations, which was not part of Web Site Optimizer. Within the console of Google Analytics Content Experiments, you can see exactly what your original design vs. the variation(s) will look like prior to launching the experiments.
In my opinion, the reporting in Content Experiments is much better than before. Content Experiments provides high-level experiment detail at a glance (visits, days of data, status of the experiment, and percentage of included visitors). The conversion data is also much improved by providing separate columns for visits, conversions, conversion rates, and basic green & red arrows to compare the variation(s) to the original page. Finally, the look of the reports is now more consistent with the newer Google Analytics interface.
By selecting to rewrite the URL variations, you can consolidate all of the traffic to your original and variation pages. These URLs will appear under the original page within your Content Reports. This ability makes the Content Reports easier to read and streamlines the analysis of the experiment’s impact on page metrics in addition to its data. This provides increased functionality with custom reporting and experiment segmentation.
The simplified shift from Web Optimizer to Content Experiments will save companies and marketers’ time, money, and allow them to easily create testing experiments. Ideally, Content Experiments will reduce the amount of time to create experiments and simplify their data, making them easier to understand as well as more actionable. With more actionable information, companies and marketers should be able to improve their users’ online experience and generate higher conversions.