Entering an Enterprise Eloqua Instance can be an intimidating task, especially when you only have a short amount of time to gain as much knowledge as possible. To correctly target your campaigns and programs, one essential area to understand in the new instance is the database. The instance we entered had multiple programs, auto synchs, rules populating lists, inconsistent naming conventions, and inconsistent data, as well as a lack of understanding of the current segmentation setup.
The goal was to understand the current segmentation setup to continue to deploy campaigns, document the current segmentation to determine where fixes were needed, improve/fix those issues, set up consistent naming/foldering, and create ongoing segmentation documentation.
Documentation of Current State
In order to understand the current segmentation setup, it was critical to document what was currently in place, how/when each list or filter was last updated, and whether it was accurately segmenting the database. Below is an example of the documentation that was created. The key information we included was asset type, accuracy, how it was updated, timeframe of updates, what segmentation it should be used on, and a brief description of the filter/list for someone to easily understand.
To initially create this documentation, it was crucial to check the dependencies for each list. From there we were able to identify where processes and programs were broken, what we could easily fix or modify, and where we needed to create a new process/program.
Note: If you do not see any dependencies for a list, check your auto synchs to see if the list is being populated through a synch.
After documenting the current state of segmentation, we were then able to make the fixes needed, create new templates, shared lists and filters, implement a consistent naming and foldering structure, and document segmentation moving forward.
After checking the dependencies of each shared list, we were able to identify where there were issues, such as missing prospect groups, incorrect match rules, lookup tables, etc.
One example was how National Accounts were being labeled. There was a program that pulled in any new contact to the system and used a match rule to identify if this contact was in a National Account, and then added it to a shared list. However, the prospect group had zero values. After reviewing the broken process, we determined there was a more up-to-date way to identify National Accounts, matching based off Email Address Domain instead of Company.
Working in an instance with high-volume campaigns, segment templates were critical. To create new templates, we reviewed the previous segments for specific campaign types (i.e., events, newsletters, transactional messages, promotional emails) to see where changes were needed. Examples of segment templates to create include customer/prospect newsletters, prospect promotional emails, customer/prospect events, etc.
Note: When creating segments, it is not only important to determine who should receive this type of messaging but also who shouldn’t. Defining who shouldn’t receive the message will help to determine which exclusions need to be applied.
Consistent Naming and Foldering
Creating a naming convention can be challenging, however, investing time to define a consistent naming convention is well worth the effort as your database continues to grow. As the volume of assets increases, having a consistent naming convention will make searching for assets related to a specific campaign very easy.
After you have determined your naming convention, it is critical to consistently apply the convention to hierarchies for folders, emails, forms, landing pages, segments, campaigns, shared lists, etc.
Below is an example of a naming generator that was created for this instance.
To create this naming convention, we looked at:
- What message was being sent
- What geographic or location-specific messaging was deployed
- What date information was important for the company (i.e., year, quarter, month, date)
Creating documentation on your segmentation and counts can be helpful to see the status of your current database, as well as the ability to analyze your segmentation over time. Below is an example of the documentation we created for this instance, which includes the email name, record type, geolocation, message type, inclusion/exclusion criteria, and the approximate send size.
Documenting segmentation information gave us the ability to see how counts fluctuated on a weekly/monthly basis and over message types. This also gave us the ability to identify if there may be an issue with the database if we were to see a large increase or decrease with specific counts. For example, below is a weekly view of segment counts for a specific message type. By documenting this information, we were able to identify a 20K drop in counts quickly and dig into the decrease.
- B2B: Data Cleansing
- B2B: Profile & Target