A recurring question in the Google Tag Manager communities (e.g. product forums) is how to use an Enhanced Ecommerce dataLayer object with the Facebook pixel code? It’s a common question since running a Facebook conversion pixel on a site that also collects data from the store into Google Analytics’ Enhanced Ecommerce reports is probably a very typical scenario. Side note: Since Google+ is about to go the way of the dodo, I’ve created an archive of the entire community which you can browse and make text searches against.
One of the big problems in Google Analytics’ data model is the immutability of historical data. Once a row of data is written into the data table, it is there practically for good. This is especially annoying in two cases: spam and bogus ecommerce hits. The first is a recognized issue with an open and public data collection protocol, the latter is an annoyance that can explode into full-blown sabotage (you can use the Measurement Protocol to send hundreds of huge transactions to your competitor’s GA property, for example).
Enhanced Ecommerce is certainly one of the finest reporting user interface features that Google Analytics has to offer. Enhanced Ecommerce, as the name implies, is a set of dimensions, metrics, and reports, which combine to provide you with a fairly complete view into how users are interacting with your products in your webstore. The main downside of Enhanced Ecommerce is, as with all good things, that it’s complicated to implement.
Enhanced Ecommerce is a very useful set of reports in Google Analytics. They extend the standard Ecommerce funnel, which measures only purchases, and allow you to observe products from the very first impression, through various interactions, all the way to the purchase and even beyond, if the user wanted a refund. Google has some solid documentation on how to implement and interpret Enhanced Ecommerce, but if there’s one area that would deserve more illumination, it’s attribution.
Enhanced Ecommerce is undoubtedly an excellent feature of Google Analytics. It provides us with a set of reports that truly extend the capabilities of funnel-based website analysis. As I’ve shown before, it’s also very useful for tracking other transactional events on your site, such as content engagement. However, here’s the thing. It’s not very easy to implement. Even if you get everything right according to the documentation, there are still quite a number of pitfalls, and many of the learnings emerge only through experience.
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