Create Filtered Segments

Learning Objectives

After completing this unit, you’ll be able to:

  • Identify filtering options.
  • Evaluate container path scenarios.

Containers, Operators, and Logic 

As you get comfortable with your data, you also need to get comfortable with containers, operators, and filtering logic. These are the building blocks of segmentation within Customer 360 Audiences. We mentioned these in the first unit, but let’s break them down even further. Remember our yellow scarf example from before?  Let’s take a closer look at the components that make up the filter. 

  1. Aggregation
  2. Operators
  3. Value
  4. Logic

Container example with callouts for aggregation, operators, value, and logic.


Let’s start with aggregation. For a new container attribute, you must select aggregation for an entity based on count, sum, average, or maximum and minimum, along with an operator and value. This creates the base of your filter and sets the standard of the results you are looking for, whether they are a specific count or based on a calculation.





Entities selected for the segment based on how many times the criteria must be met. 

  • At least 5 purchases
  • No more than 2 complaints


Entities segmented based on a chosen attribute to be summed across all data values.

  • Lifetime purchase value of $1500


Entities segmented based on a chosen attribute to be averaged across all data values.

  • Individual average lifetime value of $500
  • Customer satisfaction average of 3.5


Entities chosen based on the chosen maximum of a specific attribute. 

  • Maximum purchase amount < $1000


Entities chosen based on the chosen minimum of a specific attribute. 

  • Minimum purchase amount > $5


Count is available for any data type, while the remaining aggregation types can only use numeric data.


Next, you must select an operator. The operator in a filter is like the verb in a sentence. Operators specify how filter criteria relates to the value entered. For Customer 360 Audiences, operators apply to filters in three forms: date, numeric, and alphabetic. Let’s review the operator options. 

Type Options Use Case


  • Is Anniversary Of
  • Is Not Anniversary Of
  • Is On
  • Is Before
  • Is After
  • Is Between
  • Last Year
  • This Year
  • Next Year
  • Last Number Of Days
  • Next Number Of Days
  • Last Number Of Months
  • Next Number Of Months
  • Day Of Week
  • Day Of Month
  • Not Day Of Month
  • Before Day Of Month
  • After Day Of Month

To set up a batch email that sends to profiles on their birthday, you might use:

Attribute: Birthdate

Operator: Is Anniversary Of

Value: Today’s Date


  • No Value
  • Is Equal To
  • Is Not Equal To
  • Is Less Than
  • Is Less Than Or Equal To
  • Is Greater Than
  • Is Greater Than Or Equal To
  • Is Between
  • Is Not Between

You want to use an attribute like total purchase amount to create a segment. The segment can be used to send a special email offer to customers who spend more than $100.

Attribute: Grand Total Amount

Operator: Is Greater Than 

Value: 100


  • Is Equal To
  • Is Not Equal To
  • Contains
  • Does Not Contain
  • Begins With
  • Exists As A Whole Word
  • Is In
  • Is Not In

You want to send an email to customers who live in a certain state.

Attribute: State

Operator: Is In (which allows for comma separated values)

Value: IN, Indiana  


Values are pretty straightforward. They are the thing you want your filter to find. And there’s good news! Values are not case sensitive. So if you type the subject line text as TENT SALES, tent SALES, or even TeNt SaLes, your results are still the same. 


Finally it’s good to refresh yourself on the filtering logic of AND versus OR. To determine which to use, ask yourself: Am I looking for any or all?

Any of these can be true = OR

I like peanut butter or jelly on a sandwich, not both. 

All these things need to be true = AND

I like peanut butter and jelly on a sandwich. 

Container Paths

Now that you have the basics, let’s discuss what happens when you have multiple options for data sources. For example, an email address attribute could link to many different data sets. A container path needs to be selected when a container has multiple access paths back to the segmentation entity (remember this is called Segment On). Selecting one container path helps Customer 360 Audiences understand how to build your segment. 

Let’s review a scenario where NTO needs to select a container path. NTO has data about product purchases in two different data streams. One is a data stream that has retail purchases. The other is case data from Service Cloud. So when adding a product-based attribute to a segment, it’s important for the marketer to choose which data source to use for their segment based on their marketing campaign’s goal. 

If NTO wants to send an email to a customer because they complained about a product and created a case, the marketer would want to use the path that originated from Service Cloud data. If the marketer wants to simply send an email to individuals who bought a specific product, they would choose the attribute connected to retail purchases. 

It’s important to know that after you select the container path, you can’t change it. To change the path, you must delete the container and create another one with a different path. 



If you have questions about which path to use, talk with your data aware specialist.

Filter Examples

There’s a lot you can do with filtering logic, but sometimes it takes trial and error to get the exact results you are looking for. Reviewing examples can help you get started. Let’s see how Northern Trail Outfitters (NTO) creates three different segments in Customer 360 Audiences. 

Filter Example 1: NTO wants to send an offer to customers who have opened more than five of their emails with the subject line “Tent Sales.”  

  • Container: Email Engagement | Count | At Least | 6
    • Engagement Channel Action | Is Equal To | Open
    • AND
    • Subject Line Text | Contains | Tent Sales 

Filter example 1.

Filter Example 2: NTO wants to send an email to their August big spenders (with at least one purchase over $1,000) based in San Francisco or New York City.

  • Container: Device Application Engagement | Count | At Least | 1
    • City Name | Is In | New York, NYC, San Francisco, San Fran
    • AND
  • Container: Sales Order | Count | At Least | 1
    • Purchase Order Date | Is Between | AUGUST 1, 2020 to AUGUST 31, 2020
    • AND
    • Grand Total Amount | Is Greater Than | 1000

Filter example 2 in two containers.

Filter Example 3: NTO wants to see which SMS subscribers opted in to their recent SMS campaign for their hiking contest.

  • Container: SMS Engagement | Count | At Least | 1
    • Engagement Channel Action | Is Equal To | Opt In
    • AND
    • Engagement Date Time | Last Number Of Days | 30
    • AND
    • Keyword Text | Is Equal To | HikingContest

Filter example 3



Want more example filters? Check out the help document, Examples of Segmentation Filters.

Now that you have a good idea of considerations when building your filter, get ready to build, publish, and activate segments in the next unit.  


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