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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. |
| 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. |
