This post is a part of the Marketing Cloud Email Specialist Certification Tutorial Series
Drag and Drop Segmentation
Drag and Drop Segmentation works on both lists and data extensions. You can create random segments based on specific subscriber records or a particular percentage of subscriber records. You can also create criteria or rules based on fields in the data extension, or a subscriber attribute or list. When the subscriber meets the criteria, they are placed in the filter or data extension.
When using a list or field in a data extension, drag and drop segmentation will segment subscribers based on their profile data
You can use Measures to create filters based on behavioral data e.g. clicks, opens.
When you want to create a filtered list or data extension based on behavioral or subscriber profile attributes, you will create a rule with the criteria and save the rule. This rule is called a Data Filter.
You can also link up to 3 data extensions together using Data Relationships
Example: By linking 2 data extensions by email address, you can create another filter using any of the fields in the extensions.
Refreshing Segments
Filtered segments are a snapshot in time – therefore when new data is added to the list or data extension, the segments need to be refreshed.
Ways to refresh segments:
-
- Automation Studio Activity
- Manually
Process for creating and automating the refreshing of segments:
- Create the Data filter – Define the rules and conditions (can be done in Subscribers tab in Email Studio)
- Create the filter activity – Creates the Filtered Data Extension or a Filtered List (can be created in Automation Studio)
- Automate via Automation Studio – Place in a workflow to refresh the segments
- Query Segmentation – Activity to retrieve a data extension or system data view information that matches your criteria. System data view tables contain behavioral information such as opens, clicks, and bounces.
Data is retrieved via SQL and results are placed in a resulting data extension. The data extension must be created before defining and executing the query activity. Example of Query Segmentation – Select * from Subscribers where Age > 40 or Salary > 60000
- Query Segmentation – Activity to retrieve a data extension or system data view information that matches your criteria. System data view tables contain behavioral information such as opens, clicks, and bounces.
Examples – if Segmentation is being done on a list based on BOTH Behavioural and Subscriber data (e.g. newsletter subscribers who have purchased something in the last year and clicked an email last month) then QUERY is the best segmentation for this.
A query is used for advanced filtering like querying for multiple data views. Is used to link multiple data extensions for filtering.
Sharing Data across Business Units:
If an account has multiple business units and an Enterprise Account, assets, as well as objects, can be shared across Business Units. This needs to be configured with Business Unit Access Permissions.
Check the other parts of the tutorial series – Marketing Cloud Email Specialist Certification Tutorial Series
sfdcFanBoy 
4) A bank wants to send a series of emails to customers who open a new savings account. The first email is sent immediately after the account is opened to confirm the action. The second email is sent one day after the account is opened. The third email is sent five days after the account is opened only if the customer has not made a new deposit. The final email is sent ten days after the account has been opened and the customer still has not made a deposit, or eight days after the customer opened the account and made a deposit, but has not opened any emails. The data is stored in two data extensions. The bank has two versions of each email: English and Spanish. The bank wants to automate sending the emails. Which process could the bank use? (Choose 2)
A. Create a data relationship and a Measure, use Drag and Drop Segmentation to create data filters, and use Filter activities
B. Use Query Activities
C. Use Drag and Drop Segmentation to create data filters
D. Use Drag and Drop Segmentation to create data filters, and the use Filter activities
Please answer…
LikeLike
B. Use Query Activities
LikeLike