Here’s the scenario: You’re using Google Analytics and have been assigned the task of separating a slew of different traffic sources. This includes PPC, Organic, Direct, and Referral. The first three are very straight forward: a new profile with a basic include filter. However for referral, you need to get more specific. In this case, you want to breakdown individual affiliate referral sites. Once you’ve done that, you want to categorize them based on Daily Deal sites, coupon sites, etc.
You have a couple options. One option is to tag the URL’s using the utm method. This allows you to add extra information to the destination URL which then shows in the traffic sources report. Adwords already does this and Google has a great resource for generating them for your campaigns.
One drawback to this method is if you are running many campaigns, you would need to ask each individual affiliate to change the destination URLs for your ads. This could take a long time and could lead to plenty of user error. Another issue is after you’ve tagged the URL’s you need to create advanced segmentation to track them in your profile. Because of the way Google collects their data, you are unable to view certain metrics for advanced segments including Absolute Unique Visitors, Keyword Positions, Goal, Funnel and Benchmarking reports.
Advanced Segmentation is convenient and I love it for breaking down data (especially historical data), but some of the above drawbacks have forced me to explore an alternate method for collecting and analyzing specific affiliate data.
If advanced segmentation won’t show me everything I need, I need to create a new profile and implement filters so I only see the data I came to look at. Here’s a step by step process to do just that:
1) Identify/categorize the specific sites you want to track. Work with the marketers/consultants/whomever to single out the specific affiliates you want to track as well as how they should be categorized. Start with an export of referral source data. This way you are selecting sites using the way Google Analytics displays them in the reports. This will be important when you set up the filters.
2) Backup. Using filters is a very, very powerful way to manipulate data collection, but you should take some precautions before ever implementing a single one. Ensure you have a backup profile off all raw data that will never be touched or manipulated. Create this and never worry about it again.
3) Create a new Affiliate profile. In an example like this when you’re tracking a specific traffic source, it’s better to start fresh than use an existing profile. This way all of the data ever viewed in this profile is representative of the sources you’ve specified.
4) Use advanced filters to rename affiliate traffic. What makes the affiliate traffic a unique problem is there’s no inherent way to separate it from other referral traffic. Meaning you can’t filter them simply based on a characteristic of the URL. Using a combination of UTM and filters would be the one exception to this because it allows you to create a unique characteristic for the URL that you can then use to filter. But by default, you won’t have this so you need to do it yourself. Below is an example.
Site.com is considered a deal site affiliate, so in field A I extracted the URL then renamed it placing the “- deal site” at the end. Note: Be sure to double check the format Google Analytics uses in its referral report when filling out Field A.
Once you’ve done this, site.com shows as “site.com – deal site” in my referral reports. Do this for every affiliate and then create an include filter that only allows sites with the new extension into the reports. Be sure the include filter is at the bottom as filters are implemented in the order in which they are listed.
Now you have a Google Analytics Profile exclusively showing your hand picked affiliate sites.
