Adobe Analytics vs. Google Analytics: Keywords, Campaigns, and More!
As a followup to my Visits in Google Analytics and Adobe Analytics (Omniture SiteCatalyst) post, I thought I’d share some other Google Analytics and Adobe Analytics comparisons that I get asked about regularly.
Understanding Keywords (Including Not Provided) in Adobe Analytics
One frequent topic that I get asked about is what the Keyword Unavailable and Unspecified keywords are within Adobe Analytics. To understand this, let’s compare to Google Analytics.
Within Google Analytics, go to Acquisition >> All Traffic >> Source Medium. Then, click the small blue link above the data table that says “Keyword.”
You will probably see data for the keywords “(not provided)” and “(not set)”. Let’s compare this to Adobe Analytics (formerly known as Omniture SiteCatalyst), looking at a search keywords report:
Here you can see Keyword Unavailable and Unspecified. These are the same as the Google Analytics terms we reviewed previously.
Building Dashboards in Adobe Analytics
This is another area where Adobe really differs, but can still be a powerful tool in its own way. Adobe Analytics also has an “Add to Dashboard” button… sort of. You might be familiar with this feature in Google Analytics:
Adobe’s version is just a bit more hidden at the top of your report:
The next screen in Adobe after clicking “Dashboard” looks a bit like this:
Now might be a good time to note that “Reportlet” is the same thing in practical use as a “Widget” in a Google Analytics environment. Some key differences:
- Google Analytics has more visual options for Widgets (geo, trend line, pie chart, etc.)
- Adobe Analytics can mix Reportlets from different Report Suites. This would be like creating a dashboard in Google Analytics that combines widgets from different Views (aka Profiles in GA).
- Adobe Analytics can set different date ranges for each Reportlet. This would be like creating separate Widgets with their own date ranges in Google Analytics dashboards. This can be handy for creating a widget for this month, last month, the same month last year, etc.
- In Adobe Analytics, you can apply separate segments to each Reportlet. In Google Analytics, any segment selected applies to the entire dashboard, you cannot set a segment to each widget. However, in Google Analytics, you can set a filter for each widget. Filters do exist in Adobe Analytics reports, but you cannot apply them to Reportlets.
Let’s review some vocabulary differences:
Campaign Tagging in Adobe Analytics vs. Google Analytics
Campaign tagging in Adobe Analytics is very customized. You could technically use Adobe Analytics’ method in Google Analytics by making smart use of profile filters, but this isn’t the out-of-the-box solution for Google. Historically, Google Analytics URL tagging works one of two ways:
1. Manual URL tagging, resulting in URLs that look like this:
2. Auto tagging, resulting in URLs that look like this:
Adobe Analytics tagging is very different, because literally everything can be customized about it. You don’t have to use a standard naming convention; you (or your client) get to choose the naming convention that makes sense for you. You could have any one of these types of tags, and you could set rules within Adobe Analytics to read them however you would like:
If these URLs were real, the last one might be a case where your (or your client’s) server intercepts the URL with its original tagging and rewrites it as a more private campaign ID. That’s really fancy stuff!
95% of the time, I see URLs that look like this one: example.com?CMP=FB-SM-PM-SUMM-061513
This is along Adobe’s best practices. The analyst/developer responsible for Adobe Analytics then sets rules in Adobe’s data processing rules to determine different dimensions. In this example, they might set a rule saying when the CMP value starts with FB-, set the Referring Domain to facebook.com. Another rule might say, when the CMP value contains –PM-, set the Channel to Paid Media. And so on.
Let’s have some final vocabulary review:
That’s all we’ll cover for today. Any requests for future comparisons? What have you found to be confusing or enlightening when using either of these tools?