Audience Builder Reference Private Beta

Complete reference for the Audience Builder’s condition types, operators, and system limits.

Available Plans

growth
enterprise

3 minute read

For a step-by-step walkthrough, see How to Create an Audience.

Condition types

Type	What it filters	Example
Properties	Columns on the data source	`lifetime_value >= 5000`
Relations	Related records (existence or aggregate)	Customers who placed 3+ orders in the last 90 days
Events	Timestamped event tables (with time windows)	3+ `Add to Cart` interactions in the last 7 days
Audiences	Membership in other saved audiences	Not in `Recently Contacted`

Relations

Relationship conditions combine:

A path of one or two relationship hops
An optional condition on the final entity (for example, store_type = "Flagship")
A quantifier (any / all / none) or aggregate (count, sum, avg, min, max), or both
An optional time window (when the related entity is an event model)

Events

Events use the same structure as relations but also support time windows:

Mode	Description
Any time	No time filter (default)
In the last	Relative window, for example In the last 30 days
Between	Absolute date range
After	On or after a specific date
Before	Before a specific date

AND / OR logic

Conditions inside a group are joined with AND by default
Toggle to OR to match any condition instead of all
Combine groups for mixed logic: (A AND B) OR (C AND D)

Operator reference

The operators available depend on the column’s data type.

Label	Operator	String	Number	Boolean	Datetime
equal	`eq`	✓	✓	✓	✓
not equal to	`neq`	✓	✓	✓	✓
greater than	`gt`	—	✓	—	✓
greater than or equal to	`gte`	—	✓	—	✓
less than	`lt`	—	✓	—	✓
less than or equal to	`lte`	—	✓	—	✓
between	`btw`	—	✓	—	✓
not between	`nbtw`	—	✓	—	✓
in	`in`	✓	✓	✓	✓
not in	`nin`	✓	✓	✓	✓
containing	`like`	✓	—	—	—
not containing	`nlike`	✓	—	—	—
set	`nnull`	✓	✓	✓	✓
not set	`null`	✓	✓	✓	✓
in the last	`inlast`	—	—	—	✓

Aggregates: Compare COUNT, SUM, AVG, MIN, and MAX with eq, neq, gt, gte, lt, and lte.

Preview and size estimation

Automatic preview: A preview runs when you open a saved audience and after every save.
Manual preview: Use Calculate size to preview unsaved changes.

Examples

The following examples use a typical ecommerce Data Graph where Customers is the data source, related to Accounts, Sales, Customer Interactions, Products, and Stores.

High value customers

Properties: LIFETIME_VALUE >= 5000

Frequent buyers (last 90 days)

Events: Customers → Sales, COUNT(Sales) >= 10, time window in the last 90 days

Churn risk: High value but lapsed

Group 1 (Properties): LIFETIME_VALUE >= 500
Group 2 (Events): Customers → Sales, quantifier none, time window in the last 90 days
Combine with: AND

Current limitations

Relationship hops: Up to 2 hops. Deeper traversal will be supported in a future release.
Logical nesting: Up to 2 levels deep.
Predicates per audience: Up to 100 (configurable per workspace).
Audience reference depth: Up to 2 levels deep.
Time windows: Apply only to event models. Entity relationships query across all time by default.
Aggregates on multi-hop paths: Allowed only when the path contains a single 1:many edge.

FAQ

How do I use AND and OR?

Each group is all-AND or all-OR. Click the AND/OR label between conditions to switch. To combine both, create separate condition groups.

What’s the difference between a quantifier and an aggregate?

A quantifier answers yes/no, for example, Do any matching records exist?
An aggregate answers a numeric question, for example, What’s the count/sum/avg? (count, sum, avg, min, max).

Use a quantifier for existence and an aggregate for counting or summing values.