Marketing Cloud Target Audience Cheat Sheet

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If you already have detailed subscriber profiles, the data segmentation tool in Salesforce Marketing Cloud can assist you in narrowing down the audience for your campaign. The process of applying filter criteria and examining the results could take a significant amount of time if you are unable to provide answers to some of your questions.

  • Is there anyone else except this person who you ought to be pursuing? Your retargeting or nurturing campaign should have the following people as its target audience: No, I’m afraid I don’t know how to exclude those who have recently made a purchase.
  • Is it reasonable to expect some time to be lost each day? Within the Salesforce Marketing Cloud, the essential methods for customer segmentation include the following: Make use of this guide as a quick reference to determine how to portion your food into appropriate portions.

SQL Queries

Create your SQL queries to sort your consumers into the appropriate categories. This is the most challenging approach to segmenting your consumer base, yet, it offers you the most significant degree of freedom. SQL queries can be used to retrieve the data. How about zeroing in on a specific population segment instead? Simply creating a query will return the consumers that match your criteria.

A high level of technical expertise is required for this task since you must be able to write SQL queries quickly and effectively. You might also need to work with the IT or BI teams to acquire your target list. Because of your SQL query, a list of customers will be saved in a specific data format. Using Automation Studio to automate your SQL queries will allow you to compile a daily list of customers who have purchased in the last twenty-four hours.

Pros & Cons


  • Absolute conformity to the requirements of the user
  • Make sure that your filter criteria take into account data from all of the available data extensions.


  • Demands specific expertise or the ability to rely on the assistance of other employees.
  • After thirty minutes, the execution of SQL queries will time out.

Data filter

Using data filters to segment your customer base may be “easier” (meaning it requires less sophistication), but SQL queries offer more flexibility. Visual interfaces can be used to develop data filters. As you use the drag and drop segmentation marketing cloud to put different fields into your filter, you can combine them by using the “AND” and “OR” operators and taking only a tiny amount of the data extension into consideration.

This indicates that you are only able to access the contents of the data extension. Because you can only filter using these columns, you can’t use any additional customer data.

It would be helpful to see an example of this. Let’s say you want to focus your efforts on those between 18 and 25 who bought something in the past 24 hours. This segment can be constructed using a data filter if your “Sales data extension” contains a column labelled “AGE,” even though this scenario is quite unlikely (you don’t ask a customer their age when they make a purchase, right?). There is a high probability that AGE is present in the ‘Client data extension’ you provide. Because it is impossible to search for the AGE variable in the “Client data extension,” it is challenging to generate that segment using a data filter. Execute some SQL queries to produce this segment.

Pros & cons

Data filters make it easier for marketers to divide up their customer base. You are only permitted to target a single data extension, which is, unfortunately, the case. SQL queries are what are utilised in the process of developing complex filters.


  • Manageable user Interface
  • Lacking in technicality


  • The criteria for the filter are confined to the column headings.
  • It is not possible to use complex filters.

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