Audience Filters
Last updated
Last updated
Filters are the core of the visual builder. You can mix different conditions to segment your users to a specific audience. The builder provides various types of filters you can use with Boolean (AND / OR) logic:
User properties
Related properties
Events
Audiences
User propeties are the most basic conditions. You can use it to filter audiences based on the column values in your primary table, which contains users.
For example, if your primary table is a table of users for an e-commerce brand and includes columns like device and created at date, you can create an audience of:
All users who have device "iPhone"
AND
All users who got created after 1st Jan 2023.
Here's how it looks in the visual builder:
The related properties filter users based on data in related tables. These tables are any non event table added to the schema.
For example, if your primary table is users for an e-commerce brand and you have related table for their orders and line items, you can create audiences like this:
All users that have order status "Completed"
AND
All users who have a line item that includes "Sunscreen".
The events filter audiences based on what events they've performed. To use it, you need to have set up events. You can check whether event was performed or not performed when building your audience.
For example, if your primary table is users for an e-commerce brand and there is an events table that collects clickstream data, you can create audiences like this:
All users that started checkout between 3rd Oct 2023 to 3rd Nov 2023 with cart value greater than 1000
OR
All users who added an item to cart after 3rd Oct 2023 with item value greater than 500
The audience filters users based on whether they're a part of another audience. This condition helps reuse standard audience groups without creating them again and create complex audiences while ensuring you're not duplicating users across campaigns.
For example, if we take the e-commerce brand, you can create an audience like this:
You can also create nested conditions in audience builders upto two levels. Groups allow you to create independent audience logic which are combined to get final set of users based on Boolean logic (AND/OR).
For example, you're running a campaign to find out users who are probably loyal to your brand. You could create an audience with following filter conditions:
All users who have at most 1 completed after 1st Jan 2023 , who have completed login as guest
AND
All users who have cancelled an order with order amount greater than 1000
OR
All users who are not part of loyal audience
You can toggle group boolean condition by clicking on AND/OR in the query. This makes it easier to organize logic around different groups.
Filter operators allow you to build your filter conditions. For example, you may want to add a related property condition based on users' device or an event condition based on when an action occurred.
The operators depend on the underlying data type you're filtering on—either textual, numerical, boolean, or timestamp. Events have operators for performed and not performed. Audience conditions only provide the operators is included in and is not included in.
When filtering on textual properties, for example on a product's brand or a user's device, you can use these operators:
is null
is not null
is
is not
starts with
ends with
includes
does not include
These operators also get a flag for case sensitivity. While selecting the dropdown, you can choose to make your selections case sensitive based on your use case.
The textual filters allow you to add multiple values. To add multiple values, type a value and press enter. This will allow you to add another value for the same filter condition.
When filtering on numeric properties, for example on a product's price or order amount, you can use these operators:
is null
is not null
is
is not
is less than
is greater than
The textual filters allow you to add multiple values. To add multiple values, type a value and press enter. This will allow you to add another value for the same filter condition.
When filtering on Boolean (true or false) values, you can use these operators:
equals
does not equal
exists
does not exist
When filtering on timestamps, you can use these operators:
is null
is not null
is
is not
in the last
not in the last
in the next
in the current
is before
is on or before
is after
is on or after
is between
