Unlike Google Analytics, which provides generic/multi-purpose tags for any kind of implementation you can imagine, Coremetrics provides a set of single-purpose tags along with an implementation strategy to help businesses get the right data in the right format. For example, there are tags specifically for adding an item of merchandise to a cart. Since this is a fundamental action for most e-commerce sites, the straightforwardness of this tagging (and the subsequent e-commerce reports it populates) is very convenient (and in some cases, where customization is required, very limiting).
As mentioned above, the use case-specific tags populate very specific reports, such as cart abandonment, checkout conversion for e-commerce, etc. These out-of-the-box reports can be very useful if you have a generic implementation that matches Coremetric's expected usage.
Explore reports are powerful because they allow you to create custom reports on practically any data point, enabling you to answer very specific questions.
The Coremetrics implementation guide is a thorough document that explains every aspect of how Coremetrics works and the technology should or could be implemented on your site. For an engineer responsible for implementation, it is immensely helpful.
Compared to Google Analytics, the reporting interface is slower and less user-friendly.
There is no way to easily manage different sites in a single enterprise (though I think this may have been addressed in a newer version).
The Impression Attribution add-on module is quite rudimentary and, compared to an ad-serving platform, very costly per impression. (But if you need impression data populated within Explore and not some other third-party, then it's for you.)
Because our implementation was deep and time-consuming, it doesn't make sense to switch to another vendor that offers incredibly similar capabilities for a similar cost. Plus, all our needs were met with Coremetrics.
We used Coremetrics Web Analytics to measure everything related to online marketing campaigns and customer behavior: visitors, traffic sources, content pathing, ROI for paid ads, checkout conversion rates, email campaign success, and visitor segmentation.
We utilized Explore and Impression Attribution to dig into answers to very specific questions such as, "Which members who were exposed to brand X via step Y of web asset Z in the past 6 months?" These figures were valuable to sell and optimize branded campaigns to partners.
Webtrends and Omniture were on the shortlist. Webtrends tagging implementation seemed a little less flexible than Omniture and Coremetrics. When it finally came down to pricing and desired features, Omniture and Coremetrics were not significantly different, so we based the final call on customer service. Testimonials from current clients and peers using both systems seemed to indicate that Coremetrics had winning customer service.
The implementation guide explains practically everything an implementation engineer needs to know. If said person has the self-discipline to read through this dense document, it will be the best way to learn.