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Cohorts are saved audience segments that persist across your Trig instance. They represent groups of organisations or people who share common characteristics, defined by filters on attributes, behaviours, stage membership, or job history.

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What are cohorts?

Think of cohorts as named bookmarks for audiences you care about repeatedly:
  • “Commercial license holders in teams of 5+”
  • “Self-serve accounts”
  • “Strategic customers”
  • “At-risk renewals”
Rather than recreating the same filters every time, you define a cohort once and reference it wherever needed.
Key distinction from behaviours: Cohorts have dynamic membership—customers can enter and leave multiple times as their attributes change.

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Why cohorts matter

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Reusability

Without cohorts, every job, behaviour, or stage requires manual filter configuration. With cohorts, you define the audience once and reference it anywhere.

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Consistency

When filters are defined ad-hoc in multiple places, inconsistency creeps in. One job might define “enterprise” as ARR > £100K, another as ARR > £150K. Cohorts enforce consistency. The definition lives in one place.

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Dynamic membership

Cohorts are dynamic. As organisations meet criteria, they automatically become members. When they no longer match, they automatically leave. Your cohorts always reflect current reality.

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How cohorts work

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Filter-based definition

A cohort is defined by one or more filter groups: Single filter group:
Multiple conditions (AND logic):
Multiple filter groups (OR logic):

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Organisation vs people cohorts

Cohorts can be created for either entity type: Organisation cohorts:
  • Enterprise accounts (ARR-based)
  • Self-serve vs sales-led
  • Product tier segments
  • Geographic regions
People cohorts:
  • Admin users vs regular users
  • Power users (high activity)
  • Inactive users
  • Users with specific roles

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Filter logic

| Within a filter group | AND — All conditions must be true | | Between filter groups | OR — Any group can be true | This allows complex logic:

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Creating cohorts

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Where cohorts live

Navigate to Audience > Cohorts to create and manage. Once created, cohorts become available:
  • As audience filters in jobs
  • As entry criteria for stages
  • As targeting for behaviours
  • As filters when viewing data
  • As conditions in completion criteria

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Configuration

1

Create new cohort

Click Create Cohort and choose organisation or people
2

Define filter groups

Add conditions using available attributes
3

Name clearly

Use a descriptive name that documents the criteria
4

Verify membership

Check that the right customers are included

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Available filter attributes

Ingested attributes:
  • Company size, ARR, contract value
  • Industry, region, segment
  • Product tier, subscription status
Trig-generated attributes:
  • Last entered/exited/completed stage
  • Last entered/exited/completed behaviour
  • Last entered/exited/completed job
  • Current membership in stages, behaviours, jobs
Calculated attributes:
  • Team size (count of people)
  • Activity metrics (aggregated from individuals)

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Using cohorts

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In job targeting

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In stage entry

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As exclusions

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In completion criteria

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Common cohort patterns

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ICP segmentation

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Stage-based cohorts

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Risk-based cohorts

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Job outcome cohorts

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Cohorts and Trig metadata

One of the most powerful aspects is using Trig-generated metadata as filter criteria.

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Stage membership attributes

For every stage:

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Behaviour membership attributes

For every behaviour:

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Job membership attributes

For every job:
This metadata enables powerful cohort definitions that connect different parts of the customer journey.

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Best practices

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Name cohorts clearly

Include key criteria in the name when practical.

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Start with business-critical segments

Don’t create cohorts for everything. Focus on:
  • Your ICPs (customer types you treat differently)
  • Risk segments (who needs attention)
  • Outcome segments (who succeeded, who didn’t)

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Use for recurring audiences

If you find yourself building the same filter repeatedly, that’s a signal to create a cohort. Rule of thumb: if you’ll use this audience more than twice, make it a cohort.

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Review periodically

Business definitions change. Review cohorts periodically to ensure definitions still match reality.

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Consider exclusion cohorts

Sometimes it’s cleaner to define who should be excluded:
  • “Never Email” cohort
  • “Sales-Owned” cohort
  • “Churned” cohort

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AI-assisted cohort definition

Trig includes natural language capabilities for defining cohorts:
The system interprets this and constructs appropriate filters. Useful for exploration before formalising as permanent cohorts.

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Common questions

Dynamically when queried. As attributes change, membership automatically adjusts.
Yes. Viewing a cohort shows current members with their attributes.
Not directly. Use the underlying attributes or combine filter groups.
Jobs lose that targeting criteria. Check dependencies before deleting.
No. A cohort is either organisation or people. Create separate cohorts for each type.

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Summary

Cohorts are persistent, reusable audience segments:
  1. Define once, use everywhere — Eliminate redundant filter configuration
  2. Dynamic membership — Customers automatically join and leave based on criteria
  3. Leverage Trig metadata — Stage, behaviour, and job history become filterable
  4. Build for business segments — Focus on audiences that drive different treatment
  5. Name clearly — Good names make cohorts self-documenting
Well-designed cohorts become the backbone of your customer segmentation.