Comparing Data: Adobe Analytics vs. Google Analytics

by | Apr 2, 2015

This post was updated on Septem­ber 21, 2017 for accu­racy. 

We get this ques­tion all the time: why is my Adobe Analyt­ics data differ­ent from the data I’m collect­ing in Google Analyt­ics? There are a lot of obvious answers out there: actions may not be tagged in both plat­forms, Adobe auto­mat­i­cally collects down­load and exit links, a Tag Manage­ment System may be used for one and not the other, etc. But we wanted to walk through some of the more tech­ni­cal reasons why even simple, stan­dard metrics like visits, pageviews, and bounce rate will be differ­ent. And yes, these differ­ences will occur even if both tools are deployed from the same Tag Manage­ment System!

Different algorithms for post-processing

Adobe and Google use very complex algo­rithms to calcu­late sessions, time spent, and many other simple and stan­dard metrics within their plat­forms. They also use differ­ent method­olo­gies when it comes to attribut­ing these metrics to dimen­sions within the plat­form. Adobe even allows for addi­tional customiza­tion depend­ing on the vari­able type that allows for Most Recent, Orig­i­nal, Linear, and Partic­i­pa­tory allo­ca­tion.

Different visitor session length

The “end” of a session is always a very diffi­cult event to capture in a web analyt­ics plat­form. Since we cannot track browser window or tab closing actions nor website exits via URL address changes it is diffi­cult to know the exact end of the session. Both plat­forms gener­ally consider the end of a session to be the time­stamp of the last tag called. Google will also close your session earlier than Adobe if it detects UTM para­me­ters in the URL, or if the refer­ring domain has not been added to your refer­ral exclu­sion list.  


Google analyt­ics typi­cally fires at the page top and Adobe at the page bottom

When it comes to website track­ing, timing is every­thing. The Google Analyt­ics pageview is gener­ally called asyn­chro­nously at the top of the page (i.e. in the <head> of the page). Adobe Analyt­ics, however, is instead called synchro­nously at the bottom of the page. This often means that page views will get called at differ­ent times depend­ing on how that page is coded. If there is a script on the page that is of high prior­ity and synchro­nous, then the Google Analyt­ics code will wait for it and some­times even wait until after the Adobe Analyt­ics tag is called. However, since the GA tag usually lives at the top of the page it is often called before the Adobe tag. Finally, if a user navi­gates quickly through your site it is possi­ble that only one or neither tag will be called before the user clicks to the next page. This will, unfor­tu­nately, result in data loss since the pageview will not be captured by all plat­forms.


Different custom tracking methods

Although we often compare Google Analyt­ics events to when teach­ing Adobe Analyt­ics to GA users (or vice versa) they are not the same. They are clearly differ­ent in terms of the dimen­sions that can be tied to the metrics captured and the imple­men­ta­tion of them is obvi­ously differ­ent too.

Different custom filtering methods

Adobe and Google both have the ability to adjust the data flowing into their plat­forms pre-process­ing. Google profiles have the concept of “Filters” whereas Adobe has “Process­ing Rules”. Both of these tool features are power­ful and useful, but beware that they both have caveats. For example, Adobe Process­ing Rules cannot be used to move data from one report suite to another, whereas Google Filters can filter data to a specific View. In addi­tion, Google Filters can also be applied to completely remove data from a specific View. There are more differ­ences between capa­bil­i­ties, but it’s impor­tant to remem­ber that these differ­ences will affect change in data when compar­ing plat­forms.

Different bot lists

Adobe and Google both have bot filter­ing plat­forms. Unfor­tu­nately, this is a neces­sary require­ment in analyt­ics plat­forms these days as bots are getting smarter and running javascript, chang­ing user-agents, and even refresh­ing IP addresses. Web analyt­ics plat­forms are doing what they can to keep up, but there is no sure­fire way to remove that data. Adobe uses the IAB (Inter­ac­tive Adver­tis­ing Bureau) list of spiders and bots by default. These bots still send data to your report suite, but the data is filtered into the “Bots and Bot Pages” reports found in the Site Metrics folder. Google Analyt­ics also subscribes to the IAB list and is enabled via the Report­ing View Settings section of the admin console. In addi­tion, both plat­forms allow for custom IP-based filter­ing. Adobe also allows bot filter­ing at the user agent level. Unfor­tu­nately, it’s a cat and mouse game for both plat­forms. As an analyst for a company that uses both plat­forms, be sure to keep your rules in sync.

Time Zone / Definition of End of Day

Time zone is one of those really subtle settings that you enable early on in the data capture process and forget about. Unfor­tu­nately, once you’re compar­ing data between plat­forms it can have a huge effect on data dispar­ity. If Google Analyt­ics is set to the Pacific Time Zone and Adobe is set to Eastern, then looking at data on the same day between plat­forms is guar­an­teed to be differ­ent. Time Zone is set in the View Settings for Google Analyt­ics and the General Account Settings for report suites in Adobe.

In Summary

So as you can see, there is going to be some vari­ance between your analyt­ics plat­forms, but this is okay! Most of our customers that have both tools imple­mented are using Google Analyt­ics as a backup system or simply because it inte­grates well with their data. Search Discovery recom­mends defin­ing one and only one system of record, one source of truth. This single system of record will always provide the best answer when answer­ing ques­tions, and your backup data is just that—backup data. If you spend too much time compar­ing plat­forms, you’ll be missing out on the oppor­tu­nity to take action on your data. Isn’t that the goal in the first place?