Grouping Rules
Grouping Rules are a transformation type for rule-based categorization — segment users into groups, classify events, or bucket accounts based on conditions you define.
Create a grouping transformation from Data → Transformations → New Data Model → Grouping.
When to use grouping rules
- Categorize customers by behavior (e.g. “high value”, “at-risk”, “new”)
- Classify events by type or source
- Build rule-based segments without writing SQL
- Convert auto-segmentation clusters into persistent rules
How it works
- Select input data (users, events, or accounts).
- Define rules with fields, operators, and values.
- Set the output group label for each rule.
- Choose an output target — typically a user or event property.
- Schedule or run on demand.
Rules are evaluated in order. The first matching rule wins unless you configure otherwise.
From auto-segmentation
If you use Auto-Segmentation to discover natural clusters, you can convert any cluster into a grouping rule with one click — turning an ML discovery into a persistent, activatable segment.
Related
- Auto-Segmentation — discover clusters, convert to rules
- Segments — activate grouped users to destinations
- Output Targets — where grouping outputs attach
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