Profile ingestion brings customer context from business systems into Data activation, so audiences and journeys can reflect the real customer state rather than just website behavior. Targeting becomes more precise when it uses attributes like relationship status, value, eligibility, and preferences.
What does profile data mean
Profile data refers to attributes that describe a customer over time. Unlike events, these attributes remain true until they're changed.
Common examples:
Customer ID and account status
Loyalty tier and points balance
Subscription package, renewal date, contract end date
Customer value band or predicted value
Consent state and channel preferences
Home market, language, and product ownership
The most useful profile attributes are the ones you already use to make targeting decisions.
Sources of profile data
Profile data usually lives in a small set of business systems. You will need to determine which system you want to use as the source for each attribute based on your use case.
CRM ingestion works well when the CRM is the system of record for customer identity and status, and you want a simple first integration.
CRM systems
Often contain customer identifiers, lifecycle status, sales context, and marketing permissions.Billing and subscription systems
Often contain contract details, subscription state, renewals, churn signals, and payment status.Ecommerce platforms
Often contain purchase history, product ownership, and customer status flags.Customer support systems
Often contain service status, open tickets, satisfaction signals, and escalation flags.
Data warehouses and lakes often contain joined and enriched attributes across many sources, including value models and derived segments. Warehouse ingestion works well when you need enriched attributes (LTV bands, churn risk) or when you want a single integration that aggregates data from multiple upstream sources.
Example: churn prevention using contract end date
A subscription business wants to target customers whose contract end date is approaching:
The billing system provides contract end date and renewal status as profile attributes.
A daily sync keeps these attributes up to date.
An audience is defined as "contract ends in 30 days and renewal not confirmed".
A journey triggers reminders and offers across available channels.
When renewal status changes, the profile updates, and the customer exits the journey.
This use case depends more on profile ingestion than on website tracking.
Before you begin
Make sure that you have the following details ready before setting up profile ingestion:
You have identified which system is the source of truth for each attribute. Use a source that has the most reliable data for the attributes you want to ingest.
You have a stable customer identifier that matches across systems.
You have defined the necessary attributes for your first activation use cases. Most implementations achieve better results by starting small, as in the following examples. This minimal set is enough to support several high-value activation patterns without creating a large mapping effort:
Customer identifier: Customer ID, account ID
Relationship status: Prospect, active, churned
Value signal: Tier, value band, LTV segment
Time-based attribute: Renewal date, contract end date
Consent and preferences: Email opt-in, channel preferences
You understand the update cadence required for each attribute. The right cadence depends on the use case. The goal is predictable freshness for the decisions being made, not maximum frequency:
Daily is often enough for value bands, tier, and lifecycle status.
More frequent may be needed for renewal windows, eligibility flags, or consent updates.
Real-time is typically reserved for attributes with immediate activation impact.
Instructions
Step 1: Set up the profile sync
To ingest the profile data, connect to the source system and define what data to ingest, and when:
Connect the source system using the provided integration method in our Data Activation setup guides.
Map the source fields to platform profile attributes.
Specify the customer identifier field for matching.
Set the sync schedule based on your freshness requirements.
Run an initial sync to populate profiles.
Step 2: Validate attribute values
After the sync completes:
Go to Data → Profiles, where you can search with the identifier to check sample profiles to confirm attributes appear correctly.
Verify that values match what you expect from the source system.
Go to Orchestration and then Create Audience to test that audiences using these attributes populate as expected.
Verify the setup works
After setting up profile ingestion:
Confirm that profiles have the expected attributes populated.
Go to Data → Profiles and search for the profiles with the identifier. If the attributes don't appear for the profile, check that the sync is running.
Check that attribute values update when the source changes (after the next sync).
If the values are stale, the sync cadence may be too low. To fix this, increase the sync frequency.
Validate that audiences based on these attributes include the right profiles.
If the attributes connect to the wrong profiles, there is likely an identifier mismatch. Check the customer ID mapping.
If you see duplicate profiles, check that you use consistent identifiers across the sources.
Test a journey that uses a profile attribute as an entry or exit condition.
Under Orchestration → Create Orchestration, set up an entry condition and count profiles on a step or two to confirm that profiles go through each stage as expected.