Iterable to Braze Migration Guide

Iterable and Braze are the two platforms most often compared at the enterprise lifecycle shortlist stage. They look similar on a feature matrix. They are not similar in how they work.

Both platforms support email, push, in-app messaging, and SMS. Both have workflow builders with conditional branching. Both connect to data warehouses and CDPs. The comparison tends to stall out at the feature level because teams are asking the wrong question. The question isn't which platform has more channels — it's which platform's data model and orchestration logic fits the way your product generates behavioral signals.

If your team is moving from Iterable to Braze, you've typically reached one of two inflection points: either Iterable's workflow builder has become a ceiling on the cross-channel logic you need to execute, or Braze's real-time event processing and Connected Content capabilities represent a meaningful upgrade to your personalization infrastructure. In most migrations we've run, it's both.

At Propel, we've managed Iterable-to-Braze migrations for enterprise consumer brands across healthtech, fintech, and marketplace verticals. What follows is the operator-level guide to doing it without revenue disruption.

Why Teams Move From Iterable to Braze

The decision to migrate to Braze from Iterable is rarely triggered by a single failure. It accumulates.

Workflow complexity ceiling. Iterable's Journey builder is capable. For teams with 5–10 active journeys and standard lifecycle logic, it's often sufficient. For teams building 30, 50, or 80 active Journeys with cross-channel conditional logic, frequency capping across channels, and real-time behavioral branching, the builder's constraints become visible. Braze's Canvas Flow handles omnichannel orchestration at this complexity level without the workarounds Iterable requires.

Personalization at scale. Iterable supports Handlebars templating for personalization. Braze supports Liquid — a more expressive templating language — plus Connected Content, which makes a live API call at send time to pull external data into any message. For teams trying to create personalized campaigns across email, SMS, and push that reflect real-time inventory, pricing, or user state, Connected Content is the capability that closes the gap.

Data warehouse integration. Braze's Currents pipeline streams every engagement event to your warehouse in real time. Combined with cloud data ingestion, teams can close the loop between product analytics and lifecycle marketing in a way that Iterable's data export mechanisms make more complicated. This is the infrastructure behind accurate DTC revenue and LTV attribution.

Predictive capabilities. Braze's Predictive Churn and Predictive Purchases models are native — they run on your Custom Event data without requiring an external ML pipeline. For teams trying to identify users who are about to churn and act on that signal in real time, this is a meaningful operational simplification.

One consumer health brand we migrated had 34 active Iterable Journeys. After the audit, 12 of them were compensating for platform limitations — workarounds that existed because Iterable's conditional logic couldn't support what they needed without branching every Journey into multiple duplicate paths. In Braze's Canvas Flow, those 12 collapsed into 4 Canvases with Audience Path steps. The reduction in operational complexity was as valuable as the capability upgrade.

The Architecture Difference: Iterable vs. Braze

Understanding this before you start determines whether your migration is a rebuild or a re-architecture.

Iterable's model: List-based and field-driven. Users are organized into lists. Custom fields hold profile data. Journeys trigger off list membership changes, custom events, or API calls. Segmentation uses a combination of field values and event history.

Braze's model: Profile-centric and event-driven. Users have profiles with Custom Attributes (static properties) and Custom Event history (behavioral actions with nested properties). Canvases trigger off Custom Events from any source. Segmentation uses Custom Attributes and event filters, with real-time segment membership updates. Braze's behavioral segmentation approach — where every action is an event with properties rather than a field update — produces richer segmentation possibilities with less manual maintenance.

The migration consequence: every Iterable custom field must be mapped to a Braze Custom Attribute. Every Iterable custom event must be mapped to a Braze Custom Event (with attention to property naming and data types). Every list-based Journey trigger must be converted to an event-based Canvas entry condition.

What Transfers and What Doesn't

Transfers With Mapping ✅

User identity data. Email, phone, userId, and standard profile fields transfer via CSV or API import. Braze's user profile schema uses external_id as the primary identifier — map your Iterable userId to this field explicitly.

Custom fields → Custom Attributes. Iterable custom fields (strings, numbers, booleans, dates) map 1:1 to Braze Custom Attributes. Document every field in active use before the migration — unused fields don't need to migrate and create noise in your Braze instance.

Suppression data. Email unsubscribes, SMS opt-outs, and hard bounces transfer, and they move first. Iterable's unsubscribe lists export by subscription channel — map each channel's opt-out list to the corresponding Braze Subscription Group.

Purchase and event history (with planning). Historical behavioral data can be backfilled into Braze via the /users/track API. For teams where historical event data powers Canvas entry conditions or predictive models from day one, this backfill must be scoped and executed as a dedicated migration workstream.

Must Be Rebuilt 🔄

Every Journey becomes a Canvas. Iterable Journeys use a different logic engine than Braze Canvas Flow. There is no migration path. Rebuild in priority order: onboarding → conversion → retention → re-engagement. Use the Braze onboarding Canvas template as the structural starting point for your highest-volume Canvas.

Segmentation logic. Iterable's segment builder conditions don't translate to Braze's filter syntax. Every segment must be rebuilt. This is the opportunity to run the lifecycle stage segmentation playbook against your Braze Custom Attributes and design a cleaner, more durable segment taxonomy than what accumulated in Iterable.

Email templates. Iterable uses Handlebars ({{firstName}}). Braze uses Liquid ({{${first_name}}}). Every template must be rebuilt and every personalization tag rewritten. Test in the pre-send email QA checklist before any Canvas goes live.

Frequency capping logic. Iterable's frequency capping is configured at the Journey and project level. Braze's frequency capping operates at the Canvas level and globally via Rate Limiting. Rebuild your frequency rules in Braze's settings before any Canvas is activated.

Lost or Replaced ❎

Iterable's Catalog feature. Iterable's Catalog allows dynamic content insertion from a data table. Braze's equivalent is Connected Content — more flexible, more powerful, but requiring an API endpoint rather than a static table upload. Teams using Catalog heavily will need to build Connected Content endpoints as part of the migration scope.

Historical campaign analytics. Iterable campaign performance data stays in Iterable. Export it before closing the account. Set up your retention metrics dashboard template in your analytics stack before the first Braze Canvas goes live so you have a clean baseline for measuring Braze performance.

Migration Checklist: Iterable to Braze

Pre-Migration Audit

• Inventory all active Journeys — trigger type, channel mix, entry volume, 30-day performance.
• Map all Iterable custom fields to Braze Custom Attribute data types.
• Identify all Catalog tables in active use — scope Connected Content API endpoints required.
• Document frequency capping rules across all active Journeys.
• Confirm engineering availability for SDK instrumentation if app channels are in scope.

Data Migration

• Export unsubscribes by channel from Iterable — import to Braze Subscription Groups.
• Export hard bounces — set hard_bounced: true in Braze.
• Export active users with all custom fields — map to Braze Custom Attributes.
• Scope historical event backfill via /users/track API if predictive features are needed from day one.
• Segment import into engagement tiers before any Canvas is activated.

Technical Setup

• Verify sending domain in Braze — DKIM, SPF, DMARC. Reference email deliverability channel health standards.
• Configure Braze Subscription Groups per channel.
• Instrument Braze SDK per your event schema — validate every Custom Event and property.
• Build and validate Connected Content endpoints for any Catalog-dependent Journeys.
• Set up Braze Currents if connecting to a data warehouse.

Canvas Rebuild and Go-Live

• Rebuild Canvases in revenue-impact priority order.
• Configure global frequency capping in Braze Rate Limiting settings.
• Run full QA against every Canvas before activation.
• Deactivate Iterable Journeys in parallel as Braze Canvases go live.
• Execute email deliverability warm-up over 4–6 weeks.

Canvas Rebuild Strategy: Iterable Journeys → Braze Canvas Flow

The most important mindset shift: do not rebuild your Iterable Journeys as-is. Rebuild them as they should be, now that your tool can support what your strategy actually requires.

Replace list-based triggers with event-based entry conditions. Iterable Journeys frequently trigger on list membership changes — a user being added to a "Trial Started" list, for example. In Braze, that trigger is a Custom Event: trial_started. The Canvas entry condition is cleaner, faster (real-time, not batch), and more data-rich because the event can carry properties (plan type, trial length, acquisition source) that branch the Canvas immediately on entry.

Use Audience Paths to replace branching Journeys. Many Iterable teams maintain separate Journeys for different user cohorts — one for high-value users, one for standard users — because Iterable's branching requires duplicating Journey logic across paths. Braze's Audience Paths handle this within a single Canvas: one entry point, multiple simultaneous audience tracks, each with its own step sequence. The operational reduction is significant. This is central to how omnichannel orchestration scales without proportionally scaling operational complexity.

Build re-engagement Canvases with win-back logic from the start. Iterable win-back workflows often require manual audience pulls to keep them current. In Braze, re-engagement Canvases trigger automatically on inactivity signals — days since last session, days since last purchase, predicted churn score. Use the win-back campaign blueprint as the structural template and integrate Braze's Predictive Churn audience as the primary entry segment.

Stakeholder Expectations

Lifecycle and CRM team: Plan for 10–14 weeks of elevated workload for a typical enterprise Iterable migration. Iterable programs at scale tend to have high Journey counts and significant template libraries — both require full rebuilds. Campaign output will decrease during the rebuild window. Our campaign analytics and performance insights service maintains visibility through this period.

Engineering team: SDK instrumentation is required for any app channel. Beyond that, Connected Content endpoint development adds engineering scope if you're migrating Iterable Catalog-dependent personalization. Budget accordingly — this is not a one-sprint task for complex programs.

Data and analytics teams: Currents schema design needs to be finalized before any Canvas goes live. Event naming established in Braze flows directly into your warehouse tables. Our events and attributes architecture service covers this as a formal pre-migration deliverable.

Leadership: Revenue from lifecycle channels will fluctuate during warm-up. The customer retention impact calculator is useful for setting the 90-day revenue recovery target before the migration starts, which gives leadership a concrete benchmark rather than a qualitative promise.

Why Propel for Your Iterable to Braze Migration

Propel is a certified Braze partner with enterprise migration experience across consumer brands that have outgrown Iterable's operational model. Our migration framework covers the full program — from Journey audit and schema design through Canvas go-live and Currents integration — with the lifecycle strategy review built into the rebuild phase.

Talk to a Propel operator about your Iterable to Braze migration.