Operators Used in Audience Segmentation

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This section helps you understand the different operators to be used while working with the attributes and building the audience.

Logical Operators: AND/OR/NOT

Operators Based on Data Types

Logical Operators: AND/OR/NOT

Logical operators help in defining conditions for audience segmentation.

Operator	Description	OPERATOR IDENTIFICATION
AND	Includes customers only if all specified conditions are met.
OR	Includes customers if at least one specified condition is met.
NOT	Excludes customers who meet a specific condition.

Example: Segmenting Users Based on Conditions

To better understand these operators, let’s consider an example with two conditions:

Condition A – The customer is of the gender male
Condition B – The customer has performed an event in the last 15 days

Logical Operator	Definition	Example Conditions	Customer Profile	Included in Audience?	Reason
AND	Includes customers only if all conditions are true. Excludes if any condition is false.	Gender = “Male” AND Event in Last 15 Days	Gender: Male, Last Event: 10 days ago	✅ Yes	Both conditions are true.
AND	Includes customers only if all conditions are true. Excludes if any condition is false.	Gender = “Male” AND Event in Last 15 Days	Gender: Male, Last Event: 20 days ago	❌ No	The event condition is false.
OR	Includes customers if at least one condition is true. Excludes only if both conditions are false.	Gender = “Male” OR Event in Last 15 Days	Gender: Male, Last Event: 20 days ago	✅ Yes	The gender condition is true.
OR	Includes customers if at least one condition is true. Excludes only if both conditions are false.	Gender = “Female” OR Event in Last 15 Days	Gender: Female, Last Event: 10 days ago	✅ Yes	The event condition is true.
OR	Includes customers if at least one condition is true. Excludes only if both conditions are false.	Gender = “Female” OR Event in Last 15 Days	Gender: Female, Last Event: 20 days ago	❌ No	Both conditions are false.
NOT	Excludes customers who meet a specific condition. Includes those who do not satisfy it.	NOT (Gender = “Male”)	Gender: Male	❌ No	The condition matches, so the customer is excluded.
NOT	Excludes customers who meet a specific condition. Includes those who do not satisfy it.	NOT (Gender = “Male”)	Gender: Female	✅ Yes	The condition does not match, so the customer is included.

Operators Based on Data Types

When applying attributes, use the different data types accepted by the system to provide values for the fields. For example, when providing customer information such as gender, you can only input a string value like male or female. Below, you can find information about the different data types and the operators available for the them in the system.

String Operators

String values store textual information, such as gender (for example “male” or “female”) or city (for example, “New York,” “London”). The following table explains how different string operators work with examples:

Operator	Description	Example Condition	User Profile	Included in Audience?	Reason
Equal	Matches an exact string value.	Gender = “Male”	Gender: Male	✅ Yes	The value matches exactly.
Not Equal	Excludes users with the exact value.	Gender ≠ “Male”	Gender: Female	✅ Yes	The value is different from “Male”.
Contains	Includes users if the value contains a specific substring.	City contains “York”	City: New York	✅ Yes	”New York” contains “York”.
Not Contains	Excludes users if the value contains a specific substring.	City not contains “York”	City: New York	❌ No	”New York” contains “York”, so the user is excluded.
In	Includes users if the value matches any value in a list.	City in (“New York”, “London”)	City: London	✅ Yes	”London” is in the specified list.
Not In	Excludes users if the value matches any value in a list.	City not in (“New York”, “London”)	City: Paris	✅ Yes	”Paris” is not in the specified list.
Begins With	Includes users if the value starts with a specific substring.	City begins with “San”	City: San Francisco	✅ Yes	”San Francisco” starts with “San”.
Not Begins With	Excludes users if the value starts with a specific substring.	City not begins with “San”	City: San Diego	❌ No	”San Diego” starts with “San”, so the user is excluded.
Ends With	Includes users if the value ends with a specific substring.	City ends with “ton”	City: Boston	✅ Yes	”Boston” ends with “ton”.
Not Ends With	Excludes users if the value ends with a specific substring.	City not ends with “ton”	City: Houston	❌ No	”Houston” ends with “ton”, so the user is excluded.
Exists	Includes users if the attribute has a value.	Email exists	Email: user@example.com	✅ Yes	The user has an email value.
Does Not Exist	Excludes users if the attribute has no value.	Email does not exist	Email: (empty)	✅ Yes	The email field is empty, so the user is included.

Integer Operators

Integer values represent whole numbers such as age, purchase count, or event occurrences. The following table explains how different integer operators work with examples:

Operator	Description	Example Condition	User Profile	Included in Audience?	Reason
Greater or Equal (>=)	Includes users if the value is greater than or equal to a specified number.	Age >= 18	Age: 20	✅ Yes	20 is greater than 18.
Lesser or Equal (<=)	Includes users if the value is less than or equal to a specified number.	Age <= 18	Age: 16	✅ Yes	16 is less than 18.
Greater (>)	Includes users if the value is strictly greater than a specified number.	Purchase Count > 5	Purchases: 6	✅ Yes	6 is greater than 5.
Less (<)	Includes users if the value is strictly less than a specified number.	Purchase Count < 5	Purchases: 4	✅ Yes	4 is less than 5.
Equal (=)	Includes users if the value matches exactly.	Age = 30	Age: 30	✅ Yes	The value matches exactly.
Not Equal (≠)	Excludes users if the value matchesexactly.	Age ≠ 30	Age: 25	✅ Yes	25 is different from 30.
In	Includes users if the value matches any number in a list.	Age in (25, 30, 35)	Age: 30	✅ Yes	30 is in the specified list.
Not In	Excludes users if the value matches any number in a list.	Age not in (25, 30, 35)	Age: 40	✅ Yes	40 is not in the specified list.
Exists	Includes users if the attribute has a value.	Order Count exists	Order Count: 10	✅ Yes	The user has an order count value.
Does Not Exist	Excludes users if the attribute has no value.	Order Count does not exist	Order Count: (empty)	✅ Yes	The field is empty, so the user is included.

List of Objects (LOO) Operators

List of Objects (LOO) operators apply when an attribute contains multiple values, such as a list of purchased products, visited locations, or transaction records. The following table explains how different List of Object operators work with examples:

Operator	Description	Example Condition	User Profile	Included in Audience?	Reason
ANY	Includes users if at least one object in the list meets the specified condition.	Purchased Products ANY = “Laptop”	Purchased Products: [“Laptop”, “Tablet”, “Phone”]	✅ Yes	The list contains “Laptop”.
ALL	Includes users only if all objects in the list meet the specified condition.	Purchased Products ALL ≠ “Refurbished”	Purchased Products: [“New Laptop”, “New Phone”]	✅ Yes	All products are not “Refurbished”.

Object/Non-Customer Data (NCE) Operators

Object/NCE Operators In Profile Attributes

When using Object attributes or Non-Customer Entities (NCE) in audience segmentation, you must specify the relevant properties or attributes in the audience criteria. The available operators depend on the data type of these properties, such as String or Integer.

How It Works

If you select an Object, include its properties in the audience criteria.
If you select an NCE, include its attributes in the audience criteria.
Operators vary based on the data type of the chosen properties or attributes.

Object/NCE Operators In Calculated Attributes

When Objects or Non-Customer Entity (NCE) attributes are used in Calculated Attributes, the ANY or ALL operators are available. Based on the data type (String or integer) of the selected Object property or the NCE attribute, different operators are displayed as shown below.

Event Based Operators

Event operators define conditions for audience segmentation based on Event Attributes. Depending on whether you choose Event Name or Event Properties, different operators apply.

Example Scenario

A company tracks user interactions as events. The Event Name could be “Purchase,” “Login,” or “Add to Cart,” while Event Properties could include details like “Category” (Electronics, Clothing, an so on) or “Payment Method” (Credit Card, PayPal, and so on).

Operator	Example Condition	User Activity	Included in Audience?	Reason
Equal	Event Name = “Purchase”	Event: Purchase	✅ Yes	The event name matches “Purchase.”
Not Equal	Event Name ≠ “Login”	Event: Purchase	✅ Yes	The event name is different from “Login.”
In	Event Name IN (“Purchase”, “Checkout”)	Event: Purchase	✅ Yes	”Purchase” is in the specified list.
Not In	Event Name NOT IN (“Logout”, “Cancel Order”)	Event: Add to Cart	✅ Yes	”Add to Cart” is not in the exclusion list.
Exists	Event Property (Category) EXISTS	Category: Electronics	✅ Yes	The event has a “Category” property.
Does Not Exist	Event Property (Category) DOES NOT EXIST	Event: Login (No Category)	✅ Yes	The “Category” property is missing for this event.

Timestamp Operators

Timestamp operators filter users based on when an event occurred. These operators apply after selecting an Event Attribute (such as “Add to Cart,” “View Page,” or “Checkout”).

Example Scenario

A company tracks customer interactions using events like “Purchase”, “Login”, and “Abandoned Cart”. The system records a timestamp for each event.

Operator	Example Condition	User Activity Timestamp	Included in Audience?	Reason
Within the Last	Event: Purchase within the last 7 days	Purchase on Feb 15 (Today: Feb 20)	✅ Yes	The event happened within the last 7 days.
Within the Next	Event: Subscription Renewal within the next 5 days	Renewal on Feb 25 (Today: Feb 20)	✅ Yes	The event is scheduled within the next 5 days.
Between the Last	Event: Checkout between the last 10 and 30 days	Checkout on Feb 1 (Today: Feb 20)	✅ Yes	The event happened within the past 10–30 days.
Between the Next	Event: Trial Expiry between the next 3 and 10 days	Expiry on Feb 25 (Today: Feb 20)	✅ Yes	The event is set to occur in the next 3–10 days.
Between Dates	Event: Login between Jan 1 and Jan 31	Login on Jan 15	✅ Yes	The event occurred within the specified date range.
Before	Event: Account Created before Jan 1	Account created on Dec 20	✅ Yes	The event happened before the specified date.
After	Event: Upgrade after Feb 1	Upgrade on Feb 10	✅ Yes	The event occurred after the specified date.
On Date	Event: Payment on Feb 10	Payment made on Feb 10	✅ Yes	The event date matches the specified date.
Not on Date	Event: Refund not on Feb 5	Refund on Feb 7	✅ Yes	The event date is different from the specified date.
Anytime	Event: Login anytime	Login on any date	✅ Yes	The event has no time restrictions.
Did Not Happen	Event: Subscription Renewal did not happen	No renewal event recorded	✅ Yes	The user has no recorded event for renewal.

Consent operators filter customers based on their consent status. These operators help segment users based on whether they have agreed to data processing or other terms.

Operator	Example Condition	User Consent Status	Included in Audience?	Reason
Consent Given	Users who have given consent	✅ Consent Given	✅ Yes	The user has provided consent.
Consent Not Given	Users who have not given consent	❌ Consent Not Given	✅ Yes	The user has explicitly denied or not provided consent.
Information Not Present	Users with missing consent data	❓ No Consent Data	✅ Yes	No consent information is available for the user.

Marketing Preference Operators

Marketing preference operators filter customers based on their opt-in status for marketing communications.

Operator	Example Condition	User Marketing Preference	Included in Audience?	Reason
Preference Given	Users who have opted into marketing	✅ Subscribed	✅ Yes	The user has opted into marketing.
Preference Not Given	Users who have not opted into marketing	❌ Not Subscribed	✅ Yes	The user has opted out or not subscribed.
Information Not Present	Users with missing marketing preference data	❓ No Preference Data	✅ Yes	No marketing preference information is available for the user.

Operators Used in Audience Segmentation

Logical Operators: AND/OR/NOT

Operators Based on Data Types

Logical Operators: AND/OR/NOT

Example: Segmenting Users Based on Conditions

Operators Based on Data Types

String Operators

Integer Operators

List of Objects (LOO) Operators

Object/Non-Customer Data (NCE) Operators

Object/NCE Operators In Profile Attributes

How It Works

Object/NCE Operators In Calculated Attributes

Event Based Operators

Example Scenario

Timestamp Operators

Example Scenario

Marketing Preference Operators

Create an Audience

Apply Attributes to Your Audience

Activate Your Audience

Logical Operators: AND/OR/NOT

Operators Based on Data Types

​Logical Operators: AND/OR/NOT

​Example: Segmenting Users Based on Conditions

​Operators Based on Data Types

​String Operators

​Integer Operators

​List of Objects (LOO) Operators

​Object/Non-Customer Data (NCE) Operators

​Object/NCE Operators In Profile Attributes

​How It Works

​Object/NCE Operators In Calculated Attributes

​Event Based Operators

​Example Scenario

​Timestamp Operators

​Example Scenario

​Consent Information Operators

​Marketing Preference Operators

​Related Topics

Create an Audience

Apply Attributes to Your Audience

Activate Your Audience

Logical Operators: AND/OR/NOT

Example: Segmenting Users Based on Conditions

Operators Based on Data Types

String Operators

Integer Operators

List of Objects (LOO) Operators

Object/Non-Customer Data (NCE) Operators

Object/NCE Operators In Profile Attributes

How It Works

Object/NCE Operators In Calculated Attributes

Event Based Operators

Example Scenario

Timestamp Operators

Example Scenario

Consent Information Operators

Marketing Preference Operators

Related Topics