Creating Segments
How to use the Audience Hub visual builder to create and update segments
Segments are built on top of entities, the core models set up for a data warehouse connection. Typically a member of the data team will need to first set up the entities for your warehouse connection before getting started. Take a look at Defining Your Data Model for details.
To create your first segment, click on Audience Hub in the left-hand navigation of Census and then click Add a New Segment in the top right.
To start, you'll need to select the data set you're segmenting in the top left. This will determine the type of records your segment contains, the conditions you'll be able to filter on, and what data will eventually be available to sync to your destination tools.
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Example of a segment with conditions on the User's email and their events
At any point, you can press Preview Results to get a look at a sample of the data that will be available in your segment. When you're happy with your segment conditions, give you segment a name and press Save.
The basis of any segment is adding new conditions. Clicking Add Condition to select an attribute or related data from the Details List on the right hand side. It contains all the available attributes for the selected entity, as well as any related entities or segments which can be used for additional conditions as well.
On the left side, you'll see the And / Or condition combination control. You can use this to change how conditions are combined. And meaning all the conditions must be met; Or meaning any of the conditions can be met. You can also make combinations of ands and ors by adding Condition Groups which can have their own conditions and combination control.
In addition to creating conditions about attributes on the entity you're segmenting, you can also filter based on other data related to this entity.
- Related Entities is the list of other entities connected to the entity you're segmenting. You can also create conditions on any related entities and your segment will only include records that are related to entities that meet those conditions. Census will take care of building the association between those data sets.
- Inclusions and Exclusions - Allows including or excluding members from a segment if they appear in some other segment of the same entity data. This enables creating sub segments of common shared definitions like Paid Customers, excluding segments that should never be targeted, as well as creation unions and intersections of of multiple other segments.
Census supports a wide variety of operations that can be used to filter segments. The types of operators available are dictated by the types of the data warehouse columns being filtered. Selecting a column with a different type will change the types of operators available.
Operator | Column Type | Description |
|---|---|---|
is null / is blank | All | Column is NULL (or the empty string if given a text column) |
is not null / is not blank | All | Column contains any value other than NULL (and not the empty string, if given a text column) |
is | All except boolean | Exactly matches the given value (case sensitive) |
is not | All except boolean | Does not match the given value |
starts with | Text | Starts with the given value |
ends with | Text | Ends with the given value |
contains | Text | Column contains the given value |
doesn't contain | Text | Column doesn't contain the given value |
more than | Number | Column is larger than the given value |
less than | Number | Column is smaller than the given value |
is true | Boolean | Column is true |
is false | Boolean | Column is false |
more than | Datetime | Column's value is more than ___ days ago |
less than | Datetime | Column's value is less than ___ days ago |
exactly | Datetime | Column is exactly ___ days ago |
after | Datetime | Column is after the given date |
on | Datetime | Column is exactly the given date |
before | Datetime | Column is before the given date |
between | Datetime | Column's value is between ___ days and ____ days ago |
contains any of | Array | Array column contains any of the provided values |
When the Entity you're segmenting has a related events entity, those events have even more conditions available, powered by the schema columns defined on the event entity.
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Type | Operator | Description |
|---|---|---|
Event Name | Any Event | Entity has any event matching the other conditions |
| No Event | Entity has no event matching the other conditions |
| Event Name is | Entity has an event with the given name |
| Event Name is one of | Entity has an event with any of the given names |
| No Event Named | Entity has no event with the given name |
| No Event Named any of | Entity has none of the given events |
Engagement | At least | Entity has at least x matching events |
| At most | Entity has at most x matching events |
| Exactly | Entity has exactly x matching events |
| Any number | Entity has any number (> 0) of events |
Time Period | Between | Events occurred between ___ and ___ days ago |
| Prior To | Events occurred before a date ___ days ago |
| Within Last | Events occurred within the last ___ days |
| Between dates | Events occurred between two fixed dates |
| After date | Events occurred after a fixed date in time |
| Before date | Events occurred before a fixed date in time |
| Any time | Entity has match dates regardless of time |
Though Census's visual segment creator is designed to be used without knowing any SQL, it works by generating SQL underneath the covers and running that against your data. You can actually view this SQL at any point by pressing the View SQL button.
Additionally, if you're trying to create a condition that Census doesn't support, you can still add conditions to your segment by selecting the SQL Condition in the Attribute menu. The SQL you provide will be added as an additional condition alongside any other conditions you've added to your segment. Think of it like formulas in Excel: it's a powerful tool in your toolbelt that can let you express very complex concepts, but it can break the segment so use with care!
Which string comparison operators are case sensitive and insensitive?
Case sensitive: Census will consider the "is" and "is not" operators to be case sensitive.
Case insensitive: Census will consider the "contains", "does not contain", "starts with", and "ends with" operators to be case insensitive.
Last modified 1mo ago