5 Tips for Setting Up Adobe Analytics as a Tool in DTM
There are a lot of moving parts to hook up when you’re working with such big systems as Adobe Analytics, or frankly any of the Adobe Marketing Cloud Solutions. While working on various analytics projects, there have been times when we’ve come across various implementation steps that needed refining.
In an effort to continue finetuning our process, we’ve developed a better understanding of the necessary steps. Dave Chabries has been instrumental in shedding light on what some of those steps are. As a member of the Axis41 analytics development team, he put together some key points to consider when setting up Adobe Analytics as a tool in Dynamic Tag Manager (DTM) that I would like to share with you.
1. Make sure the proper tracking server is in place for the cookie type being used.
Because some browsers are designed to reject third-party cookies, it is important to circumvent these tracking limitations by implementing first-party cookies. Doing so will help limit the presence of inflated visitor counting and other data issues.
2. Make sure to test in a development environment to eliminate coding issues.
It’s always important to remember that putting code in one place can affect code in other places. If you were to break something in the custom code that causes analytics to stop running, other rules that are in place might malfunction also. What’s important to remember is that the code needs to remain as clean and concise as possible. Always test in a development environment first in order to eliminate any coding issues that may present themselves in production. Continue testing until it works, as the development environment ordinarily mirrors the production environment.
3. Make sure the collected data is going to the correct report suite.
The report suite is where the data goes, so the environment needs to be set up so that the data goes to one place. If it is not going to the correct report suite, data can become faulty because accuracy in reporting is threatened. Though you can have multiple report suites for different environments, it is critical that you place the data in the accurate report suite. This is especially important when presenting to a client as “mixed” data will prevent you from having accurate results to show. If you’re not seeing data show up in the right place, check to make sure you put it in the right report suite.
4. Make sure values sent to report suites are in lowercase type to ensure accuracy in data.
What’s important to remember is that the system is designed to be case sensitive, so make sure that there is consistency in setting values so that you do not end up with multiple line items in your report (which really are the same thing). Adobe recommends using lowercase values to avoid duplicate values for two items that should ultimately be one reporting item.
For example, the following two cases would count as two separate line items in your report:
s.pageName = “home”;
s.pageName = “Home”;
5. Make sure there is consistency in naming data elements.
Though there is no “correct” way to name your data elements, what’s important is that all team members use the same naming convention for consistency purposes. In addition to having a uniform naming strategy, it’s also important that the name signifies to the reader what the data actually is (so do not simply name it a number, for example). It’s also a good idea to document this process somewhere.
For example, here are some different (but completely appropriate) options that could be used as a basis for your naming convention.
- Page Name
- page name
Here is a screenshot of some examples of the analytics data elements mentioned above with a consistent naming convention applied. In this example we chose to use the “page_name” option from the choices shown above.
As you can see in the Name column, all of the items have a descriptive name, sharing the same structure and process. They are all lowercase and use the underscore (_) to separate each of the parts.
Please also note that that naming of the data elements and the values named and sent to your report suite are different (#4).
We hope you found these tips helpful as you go through your Adobe Analytics implementation process. If you have any other considerations that you think would be a great addition to this list, please feel free to reach out and let us know at [email protected]. We also invite you to share this post with your social networks.
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