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Marketing ⇄ Data warehouse

Iterable to Yellowbrick integration — real-time, two-way sync

Keep Iterable and Yellowbrick in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Why teams connect Iterable and Yellowbrick

Put modeled data to work and measure what it drives: Yellowbrick and Iterable keep contacts, audiences, and campaign results in step in real time, in both directions.

Yellowbrick is where your team models customers, product usage, and revenue into trusted tables; Iterable runs the campaigns, audiences, and messages that reach those people. The two overlap wherever the same person, account, or segment matters to both, and when the bridge between them is a nightly export or a hand-built list, marketing targets stale data while analytics never sees what the campaign returned.

Stacksync syncs Tables, Views, Users and Roles, Databases in Yellowbrick with Users, Events, Campaigns, Templates in Iterable field by field, in real time, and in both directions. You decide which system owns which fields — a computed score or segment can flow out to Iterable while sends, opens, and conversions flow back to Yellowbrick — and Stacksync keeps every copy consistent and resolves conflicts by rules you set.

Common use cases

  • 01 Sync CRM and marketing data into Yellowbrick tables so it can be joined with large fact tables for enterprise BI.
  • 02 Land ERP transactional extracts in Yellowbrick for finance and supply-chain analytics.
  • 03 Two-way sync User profiles and their custom data fields between Iterable and a Postgres database or CRM so attributes and subscription state stay aligned in both systems.
  • 04 Push warehouse or CRM audience segments into Iterable as Users via bulkUpdate (up to 1000 per call) and subscribe them to static Lists to drive campaigns.

Common sync patterns

Activate a modeled audience

A segment or score built in Yellowbrick — high-intent accounts, churn risk, a lifetime-value tier — lands as an audience or contact field in Iterable, so campaigns target the people your data actually points to instead of a static export.

Keep the contact and audience list current

New and updated contacts, leads, or audience members flow between Yellowbrick and Iterable, so the marketing audience reflects the people in your warehouse and corrections propagate instead of the two sides drifting apart.

Suppression and consent stay aligned

Unsubscribes, bounces, and consent or opt-out flags held in either system propagate to the other, so no one is messaged after opting out and Yellowbrick holds the current state for auditing.

What you can sync between Iterable and Yellowbrick

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Iterable objects Yellowbrick objects How this pairing syncs
Users User profiles keyed by email or userId with custom data fields; upserted via POST /api/users/update, read via GET /api/users/{email} or getByUserId, bulk-written via /api/users/bulkUpdate (up to 1000 users per call), and deleted or GDPR-forgotten. Users and Roles Access-control objects that govern what a sync service account can read and write. Users is specific to Iterable and Users and Roles to Yellowbrick — each maps to any object or custom field on the other side.
Events Custom and system events tracked via /api/events/track and /api/events/trackBulk (up to 1000 events per call); a single user's event history is read via GET /api/events/{email}. Databases Top-level containers for schemas and tables. Events is specific to Iterable and Databases to Yellowbrick — each maps to any object or custom field on the other side.
Campaigns Email, SMS, push, and in-app sends; metadata and metrics read via GET /api/campaigns and /api/campaigns/metrics, created and sent via /api/campaigns/create and /api/campaigns/trigger. Schemas Namespaces used to organize synced datasets by source or domain. Campaigns is specific to Iterable and Schemas to Yellowbrick — each maps to any object or custom field on the other side.
Templates Reusable email/SMS/push/in-app message templates with handlebars fields; read via /api/templates and per-channel get endpoints, written via /api/templates/email/upsert and the other channel upserts. Tables Columnar MPP tables; the primary targets for warehouse syncs. Templates is specific to Iterable and Tables to Yellowbrick — each maps to any object or custom field on the other side.
Lists Static subscriber lists; read via GET /api/lists and /api/lists/getUsers, with users added or removed via /api/lists/subscribe and /api/lists/unsubscribe to control who receives a send. Views Logical views used to shape reads for BI and downstream syncs. Lists is specific to Iterable and Views to Yellowbrick — each maps to any object or custom field on the other side.

How changes propagate between Iterable and Yellowbrick

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Iterable Yellowbrick Sub-second propagation

DetectionIterable notifies Stacksync of record changes through webhook events. System Webhooks push email/SMS/push/in-app and custom events (send, open, click, bounce, complaint, unsubscribe) as JSON POSTs in near real time.

DeliveryEach detected change is applied to Yellowbrick as a row-level write, with types converted between the two schemas.

Yellowbrick Iterable Interval-based propagation

DetectionStacksync polls Yellowbrick for changes on an incremental schedule, reading only records changed since the previous pass. Polling on timestamp columns.

DeliveryEach detected change is written to Iterable through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Iterable: Limits are per endpoint and per project/key; exceeding one returns HTTP 429, so exponential backoff is advised. Event tracking allows far higher volume than metadata endpoints like campaigns/templates, and the Export API is throttled more tightly. Since Nov 10, 2025, passing the key in the query string or body is rate-limited more strictly than the Api-Key header.
  • Yellowbrick: No API rate limits; throughput depends on cluster sizing, and bulk loads should use ybload rather than row-by-row inserts.
What ships with Iterable ⇄ Yellowbrick

Connect Iterable and Yellowbrick for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Iterable–Yellowbrick connection.

Real-time

Two-way sync

Changes in Iterable or Yellowbrick instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Iterable or Yellowbrick data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Iterable or Yellowbrick record.

Observability

Monitoring

Track your Iterable ⇄ Yellowbrick sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Iterable and Yellowbrick.

How the Iterable and Yellowbrick connectors work

Iterable

Integration surface
Iterable REST API (JSON over HTTPS): Users, Events, Campaigns, Templates, Lists, Catalogs, and Commerce endpoints, plus a bulk Export API for historical data
Authentication
API key sent in the Api-Key HTTP header (also accepted as Api_Key; the name is case-insensitive). Keys are scoped by type - Server-side, JavaScript (Web SDK), or Mobile - with optional JWT-enabled keys. US projects use api.iterable.com; EU projects use api.eu.iterable.com.
Change detection
System Webhooks push email/SMS/push/in-app and custom events (send, open, click, bounce, complaint, unsubscribe) as JSON POSTs in near real time; historical backfill and incremental catch-up run through the Export API over a date range.
Capabilities
read · write · webhooks
Rate limits
Limits are per endpoint and per project/key; exceeding one returns HTTP 429, so exponential backoff is advised. Event tracking allows far higher volume than metadata endpoints like campaigns/templates, and the Export API is throttled more tightly. Since Nov 10, 2025, passing the key in the query string or body is rate-limited more strictly than the Api-Key header.

Yellowbrick

Integration surface
SQL wire protocol (PostgreSQL-compatible) with JDBC/ODBC drivers; bulk loading via the ybload utility
Authentication
Database credentials, with LDAP and Kerberos options in enterprise deployments
Change detection
Polling on timestamp columns; no exposed transaction-log CDC
Capabilities
read · write
Rate limits
No API rate limits; throughput depends on cluster sizing, and bulk loads should use ybload rather than row-by-row inserts.
How it works

How to connect Iterable to Yellowbrick — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Iterable and Yellowbrick with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Iterable connected
    Yellowbrick connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Iterable and Yellowbrick objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Iterable ⇄ Yellowbrick
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Iterable Yellowbrick
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Iterable and Yellowbrick integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

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DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 391 integrations available for Iterable and Yellowbrick.

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