Attributes are data points that describe your customers. They’re the building blocks of everything in Trig—defining audiences, setting completion criteria, personalising messages, and tracking progress.
What are attributes?
Think of attributes as facts you know about each customer:
- Who they are (name, email, role)
- What they’ve done (signup date, invoices created, login count)
- Where they are in their journey (stage, job membership)
- What Trig has observed (days in stage, objectives completed)
Every filter, audience, and criteria in Trig is built from attributes.
Attribute types
Ingested attributes
Pulled from external systems into Trig.
Sources:
- CRM: HubSpot, Salesforce
- Data warehouse: Snowflake, BigQuery, Redshift
- Product analytics: Mixpanel, Amplitude, Segment, Pendo
Examples:
company_name (from HubSpot)arr (from Salesforce)signup_date (from product database)plan_type (from billing system)
Trig activity attributes (auto-generated)
Created automatically as customers interact with Trig objects.
For every job, behaviour, stage, and objective:
currently_member_of_[object_name] — Are they currently in?
last_entry_to_[object_name] — When did they enter?
last_exit_from_[object_name] — When did they exit (failed)?
last_completion_of_[object_name] — When did they complete?
currently_member_of_onboarding_stage = true
last_entry_to_poc_1_job = 2024-10-15
last_completion_of_create_first_invoice = 2024-10-18
Rolled-up attributes
Aggregated from child entities (People) to parent entities (Organisations).
| Aggregation | Example |
|---|
| Sum | Total logins across all users |
| Count | Number of users matching criteria |
| Average | Mean value across users |
| Min/Max | Extremes across users |
total_time_entries_created (sum)active_user_count (count)average_session_duration (mean)
Calculated attributes
Derived from other attributes through computation.
Examples:
days_since_signup (today minus signup_date)days_until_renewal (renewal_date minus today)health_score (composite of multiple factors)
Action-created attributes
Set by job actions when customers complete or exit.
Example:
Job completion action: Set completed_onboarding_job = true
Person vs organisation attributes
Person attributes
Describe individual users:
- Identity: email, user_id, name
- Role: job_title, permissions, admin_status
- Behaviour: last_login, feature_usage, session_count
- Trig activity: job membership, behaviour completion
Organisation attributes
Describe accounts/companies:
- Identity: company_name, domain, account_id
- Commercial: arr, contract_value, plan_type
- Relationship: customer_since, renewal_date, csm_owner
- Aggregated: total_users, active_user_count
- Trig activity: stage, job outcomes
Choosing the right level
| Scenario | Level | Why |
|---|
| ”Has this user logged in?” | Person | Individual action |
| ”Is this account healthy?” | Organisation | Account assessment |
| ”Send email to inactive user” | Person | Individual targeting |
| ”Flag accounts for CSM review” | Organisation | Account triage |
Using attributes in filters
Building filters
- Select attribute: Choose from available attributes
- Select operator: equals, not equals, greater than, contains, has value
- Set value: The comparison value
Example:
signup_date is after 30 days ago
AND plan_type equals "Enterprise"
AND currently_member_of_onboarding_stage equals true
Filter groups
| Within a group | AND — All conditions must be true |
| Between groups | OR — Any group can be true |
Common filter patterns
New customers:
signup_date is after 14 days ago
arr is greater than 50000
currently_member_of_onboarding_stage equals true
AND days_in_stage is greater than 30
last_completion_of_job_1 has any value
AND last_entry_to_job_2 has no value
Attributes vs events
Understanding this difference is critical for building effective jobs.
Attributes
- Nature: Static values on a record
- Evaluation: Historical (checked against existing values)
- Persistence: Remain on record until changed
Events
- Nature: Point-in-time occurrences
- Evaluation: Forward-only (only new events trigger)
- Persistence: Stream of discrete actions
Critical distinction
Attributes are evaluated historically: When you create a job with audience signup_date after 30 days ago, Trig checks existing values and immediately includes matching customers.
Events are evaluated forward-only: When you create completion criteria invoice_created at least 1 time, Trig only counts NEW events from when the job goes live—not historical events.
Implication for job design
If you want to exclude customers who have already done something:
- Use an attribute (e.g.,
first_invoice_date has no value)
- Don’t rely on event counts for historical behaviour
Trig activity attributes deep dive
The four core attributes
For every Trig object, you get:
| Attribute | Meaning | Use Case |
|---|
currently_member_of_[X] | Currently in this object | Exclude from other jobs |
last_entry_to_[X] | When they entered | Time-based targeting |
last_exit_from_[X] | When they failed | Target failed customers |
last_completion_of_[X] | When they succeeded | Target successful customers |
Using for job chaining
Job 1: Initial Nudge
- On completion: Customer has
last_completion_of_initial_nudge
Job 2: Follow-Up for Completers
- Audience:
last_completion_of_initial_nudge has any value
Job 3: Rescue for Non-Completers
- Audience:
last_exit_from_initial_nudge has any value
Timing-based targeting
last_entry_to_onboarding_job is after 5 days ago
AND last_entry_to_onboarding_job is before 3 days ago
AND last_completion_of_onboarding_job has no value
Persistence is powerful
These attributes never disappear. Years later, you can still query:
- “Show me everyone who completed Job X in Q3 2024”
- “How many customers who failed Behaviour Y eventually churned?”
Viewing attributes
Settings > Attributes
Navigate to Settings > Audience > Attributes to see all available:
- People Attributes
- Organisation Attributes
- Stage Result Attributes
- Objective Result Attributes
On individual records
Click any person or organisation to see their specific values, grouped by source:
- CRM Attributes
- Product Attributes
- Trig Activity Attributes
Attribute data types
| Type | Operators | Example |
|---|
| String | equals, contains, starts with | company_name contains "Tech" |
| Number | equals, greater than, less than | arr is greater than 50000 |
| Boolean | equals, not equals | is_paying equals true |
| Date | before, after, between | signup_date is after 30 days ago |
| Array | contains, does not contain | tags contains "Enterprise" |
Common attribute patterns
Commercial attributes
arr (Annual Recurring Revenue)
mrr (Monthly Recurring Revenue)
contract_value
plan_type
subscription_status
renewal_date
Engagement attributes
last_login
login_count
session_duration
feature_usage_count
dau (Daily Active Users)
Stage attributes
signup_date
activation_date
first_value_moment
onboarding_complete
days_as_customer
Trig-generated attributes
currently_member_of_[stage/job/behaviour]
last_entry_to_[stage/job/behaviour]
last_completion_of_[stage/job/behaviour]
days_in_[stage]
objectives_completed_count
Best practices
Naming conventions
| Good | Bad |
|---|
first_invoice_created_date | fic_dt |
completed_onboarding_job | flag_1 |
Keep source of truth clear
- Don’t duplicate CRM fields manually
- Use Trig-generated attributes for Trig activity
- Create dedicated fields for write-back
Use Trig attributes liberally
The auto-generated attributes are extremely valuable:
- Use for progressive job targeting
- Build exclusion logic
- Analyse intervention outcomes
Test your filters
Before launching jobs:
- Build the filter in Audience view
- Check the resulting count
- Spot-check individual records
Troubleshooting
”Attribute has no value”
- Is data flowing from the source system?
- Is the attribute mapped in the integration?
- Has the customer record been synced recently?
”Filter returns unexpected results”
- Are you using person vs org attributes correctly?
- Is the operator correct (equals vs contains)?
- Are date comparisons using the right direction?
”Trig activity attributes not appearing”
- Has the job/stage/behaviour been set live?
- Has anyone entered the object yet?
- Attributes only appear after first use
Summary
Attributes are the foundation of everything in Trig:
- Three sources — Ingested (external systems), Trig-generated (platform activity), action-created (job outcomes)
- Two levels — Person (individual users) and Organisation (accounts)
- Attributes = historical, Events = forward — Critical for job design
- Trig activity attributes are powerful — Entry/exit/completion tracking enables progressive jobs
- Roll-ups aggregate up — Person data flows to organisation level
- Persist forever — Historical record enables long-term analysis
Master attributes and you master Trig. 
