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.
Audience size calculation
You can see the audience size based on the currently specified conditions whenever you open a saved audience and after every save.
To see the calculation for any unsaved changes, click Calculate size.
Preview sample audience data
Click Preview to see a sample of the audience data.
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.
Questions? We're here to help.
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