This post was originally published on May 15, 2013. We’ve updated it with the latest information, new content and relevant links.
As a digital analyst, I split my time between two primary tools: Google Analytics and Adobe Analytics (Omniture SiteCatalyst). Using both is challenging because they require different mindsets and skills. Google Analytics could be likened to a chic, suave, easy-to-use product, while Omniture SiteCatalyst is bulkier, yet more powerful. One is easy on the eyes; the other takes a bit longer to love. Distinguishing key differences between these two primary tools gives digital analysts the ability to use the best of what each has to offer.
Omniture SiteCatalyst costs money and requires more in-depth development work. The implementation is always customized and differs depending on specific needs, metrics and goals. The upfront work and investment for Omniture SiteCatalyst is greater than Google Analytics, but if done properly, the information gathered will be more tailored to your specific metric needs. In addition to tracking web actions, the Adobe Marketing Cloud offers various options for data integration across an enterprise’s data infrastructure.
Omniture SiteCatalyst has the advantage of required custom implementation, which provides the option for the creation of custom traffic, event and conversion variables. These are set in advance to give specific information about your visitors rather than looking at all visitors in aggregate. You can see those who clicked through on a campaign versus the ones who purchased a product. Omniture SiteCatalyst allows up to 75 traffic variables, 100 event variables and 75 conversion variables, all of which can capture whatever data you would like.
Google Analytics also has the ability to set custom dimensions and metrics but only allows up to 20 custom dimensions and 20 custom metrics with the free version. Like Omniture SiteCatalyst, these variables can be set to expire after different measurements: a hit, session, user or product. Custom metrics can be set to expire after a hit or product.
Omniture SiteCatalyst variables differ in that they can be set to expire after a specified period of time (i.e., 30 days) and can also be stacked on top of each other, so you can see the sequence of events taking place.
Omniture SiteCatalyst allows for distinctive reporting suites of various data sets. If your company’s website has several sub-sites, Omniture SiteCatalyst allows them to have their own suite for data, which can then get rolled up into one large suite. This allows seeing metrics broken down for each sub-site. Report suites allow you to view the different paths a visitor may take between sub-sites. These reports also allow the creation of one dashboard that can be applied with different report suites.
Instead of reporting suites, Google Analytics allows for the creation of different data profiles, which are versions of your data with permanent filters applied.
Another way that Google Analytics allows a user to look at data in sections is segmentation. A user can apply up to four segments and make comparisons across each one. Omniture SiteCatalyst applies segments in a stacking fashion; for example, applying two segments would find the intersection of the two. In order for a comparison to occur in SiteCatalyst, a user must export the data from different segments and compare outside of SiteCatalyst.
Combining the Two
As a digital analyst, I have to balance the trade-off between ease of use and complexity. There are times when Google Analytics is best to use because the information is gathered quickly and easily. However, in-depth answers often need to be determined by Omniture SiteCatalyst. Limiting yourself to one tool can also be limiting for your business. I’ve found using these tools in tandem gives the greatest value to your analytics work. You can check out a more in-depth dive into what these tools should be calculating by reading our Pace Perspective on measuring the value of custom content.
What tools have you found to be most beneficial for reporting your analytic data? We would love to hear your recommendations or suggestions in the comments below.
By Sarah Ingle