Iterable + Amplitude
Connect Iterable and Amplitude for Marketing That Actually Knows Your Users
Pull behavioral analytics from Amplitude directly into Iterable to personalize campaigns with real product data — not guesswork.
Why integrate Iterable and Amplitude?
Iterable and Amplitude are two of the strongest tools in a modern growth stack, but they work in isolation by default. Amplitude captures detailed behavioral data about how users interact with your product. Iterable turns that kind of intelligence into personalized, multi-channel campaigns. When you connect them, lifecycle marketing stops being a gut-feel exercise — every message your team sends is backed by real, current user behavior.
Automate & integrate Iterable & Amplitude
Use case
Sync Amplitude Behavioral Cohorts to Iterable for Targeted Campaigns
Amplitude cohorts built on product usage — users who finished onboarding, churned from a feature, or crossed a usage threshold — can sync automatically to Iterable as dynamic lists. No more manual CSV exports. Your campaigns reflect current behavioral data, and your team can launch targeted outreach the moment a user qualifies.
Use case
Trigger Iterable Campaigns Based on Amplitude Events
When a user fires a behavioral event in Amplitude — completing a trial, abandoning a checkout step, hitting a usage milestone — tray.ai can immediately trigger a corresponding Iterable campaign or workflow. That real-time connection turns Amplitude's analytics layer into a campaign trigger, cutting the time between a user action and your marketing response.
Use case
Enrich Iterable User Profiles with Amplitude Behavioral Attributes
Amplitude tracks granular user behavior — session frequency, feature adoption scores, NPS responses. Syncing those attributes into Iterable user profiles lets you personalize email, push, and SMS campaigns based on what users actually do. Use them as personalization tokens or as conditions inside Iterable's journey builder.
Use case
Feed Iterable Campaign Engagement Data Back into Amplitude
Close the measurement loop by pushing Iterable engagement events — opens, clicks, conversions, unsubscribes — back into Amplitude as tracked events. Product and data teams can then analyze how marketing touchpoints influence behavior, retention, and revenue inside Amplitude, without needing a separate BI tool.
Use case
Suppress Active Iterable Campaigns for Users Flagged in Amplitude
Amplitude can identify users who are already highly engaged, currently in a sales conversation, or showing churn-risk signals that call for a different approach. Automatically suppress or adjust active Iterable campaigns for those users based on their Amplitude cohort membership — so you're not sending irrelevant content at the worst possible moment.
Use case
Automate Re-Engagement Campaigns for Amplitude-Identified Churned Users
When Amplitude detects a user has gone dormant — based on inactivity thresholds, declining session frequency, or feature abandonment — tray.ai can enroll them in a targeted re-engagement workflow in Iterable. Campaigns can reference the specific features the user last touched, which makes the outreach feel timely rather than generic.
Use case
Align A/B Test Results from Amplitude with Iterable Campaign Variants
Teams running product experiments in Amplitude can use tray.ai to map experiment cohorts and variant assignments into Iterable, so marketing communications match the product experience each user is actually seeing. This prevents users in a control group from receiving campaign messaging built around a feature they've never encountered.
Get started with Iterable & Amplitude integration today
Iterable & Amplitude Challenges
What challenges are there when working with Iterable & Amplitude and how will using Tray.ai help?
Challenge
Identity Resolution Across Two Separate User Schemas
Amplitude and Iterable each have their own user identity models. Amplitude typically uses a device or user ID; Iterable centers on email address or a custom userId. Mapping users accurately between the two without duplicates or mismatches is technically tricky, and error-prone when done by hand.
How Tray.ai Can Help:
tray.ai's workflow logic lets teams define custom identity mapping rules that translate Amplitude user identifiers into Iterable's required fields. Lookup steps, conditional branching, and enrichment calls make sure every record is matched correctly before anything gets written to either platform.
Challenge
Handling High-Volume Event Streams Without Data Loss
Amplitude can generate enormous volumes of behavioral events, especially for consumer products with millions of active users. Pushing all of them into Iterable in real time risks hitting API rate limits, creating message queues, or losing data during traffic spikes.
How Tray.ai Can Help:
tray.ai handles high-throughput data flows with built-in retry logic, error handling, and batch processing. Workflows can filter, deduplicate, and throttle event payloads before they reach Iterable's API, so delivery stays reliable without pushing either platform past its limits.
Challenge
Keeping Cohort Definitions and Iterable Segments in Sync Over Time
Amplitude cohorts are dynamic — users enter and exit constantly based on their behavior. Without automation, marketing teams have to repeatedly export and re-import cohort membership, which introduces lag, human error, and stale audience data into campaign targeting.
How Tray.ai Can Help:
tray.ai runs scheduled or event-driven sync workflows that continuously compare Amplitude cohort membership against Iterable lists, adding new members and removing disqualified ones automatically. Campaign targeting always reflects the latest behavioral snapshot, with no manual intervention.
Challenge
Preventing Feedback Loops When Syncing Data Bidirectionally
When you're pushing engagement data from Iterable back to Amplitude while also reading behavioral data from Amplitude to update Iterable, circular data flows become a real risk — where an update in one system triggers an unnecessary or conflicting update in the other.
How Tray.ai Can Help:
tray.ai workflows can be built with source-of-truth tagging, conditional logic, and update timestamps to catch and break potential feedback loops before they cause data inconsistencies. Each sync direction can be independently scoped and gated to prevent circular trigger chains.
Challenge
Managing API Versioning and Schema Changes Across Both Platforms
Iterable and Amplitude both ship regular updates to their APIs, event schemas, and data models. A breaking change on either side can silently cause integration failures, miscategorized events, or dropped user attributes if no one's watching.
How Tray.ai Can Help:
tray.ai abstracts API complexity through managed connectors that are updated alongside platform changes. Workflow-level error alerting and logging give operations teams immediate visibility when a schema mismatch or API error occurs, so teams can fix problems before they do real damage to data quality.
Start using our pre-built Iterable & Amplitude templates today
Start from scratch or use one of our pre-built Iterable & Amplitude templates to quickly solve your most common use cases.
Iterable & Amplitude Templates
Find pre-built Iterable & Amplitude solutions for common use cases
Template
Amplitude Cohort to Iterable List Sync
Automatically syncs users from a defined Amplitude behavioral cohort into a corresponding Iterable subscriber list on a scheduled or real-time basis, keeping campaign targeting aligned with current product analytics.
Steps:
- Fetch current cohort membership from Amplitude via API on a defined schedule or webhook trigger
- Compare cohort members against existing Iterable list subscribers to identify additions and removals
- Add new cohort members to the Iterable list and remove users who no longer qualify
Connectors Used: Amplitude, Iterable
Template
Amplitude Event to Iterable Campaign Trigger
Listens for specific behavioral events fired in Amplitude and instantly triggers a targeted Iterable campaign or journey enrollment for the qualifying user, enabling real-time lifecycle marketing at the moments that matter.
Steps:
- Receive an event payload from Amplitude via webhook when a user fires a defined behavioral event
- Validate the event properties and look up or create the corresponding user record in Iterable
- Trigger the specified Iterable campaign or enroll the user in a multi-step journey workflow
Connectors Used: Amplitude, Iterable
Template
Iterable Engagement Events to Amplitude User Properties
Pushes Iterable campaign engagement data — email opens, clicks, and conversions — into Amplitude as user events and properties, so product teams can analyze the influence of marketing on product behavior inside a single analytics view.
Steps:
- Capture Iterable engagement webhook events such as email open, click, or conversion
- Transform the event payload into Amplitude's event schema with the appropriate event type and user identifiers
- Send the formatted event to Amplitude's HTTP API to record it against the user's behavioral timeline
Connectors Used: Iterable, Amplitude
Template
Amplitude Churn Cohort to Iterable Re-Engagement Workflow
Automatically identifies users flagged as churned or at-risk in Amplitude and enrolls them in a personalized Iterable re-engagement journey, with messaging tailored to the features they last used.
Steps:
- Poll Amplitude for updates to a defined churn-risk cohort on a daily or hourly schedule
- For each newly added user, retrieve their last active feature and session data from Amplitude
- Enroll the user in the appropriate Iterable re-engagement journey with personalized data fields populated
Connectors Used: Amplitude, Iterable
Template
Bidirectional Iterable and Amplitude User Profile Sync
Maintains a continuous, bidirectional sync of user profile attributes between Amplitude and Iterable, so behavioral properties from Amplitude enrich Iterable profiles and marketing subscription statuses from Iterable stay current in Amplitude.
Steps:
- On a scheduled interval, fetch updated user properties from both Amplitude and Iterable
- Apply conflict resolution logic to determine the authoritative value for each user attribute
- Update user profiles in both platforms with the reconciled attribute values using their respective APIs
Connectors Used: Iterable, Amplitude
Template
Amplitude Experiment Cohort to Iterable Suppression List
Maps Amplitude A/B experiment variant assignments to Iterable suppression lists, so users in control groups are excluded from campaign variants built around features they haven't seen.
Steps:
- Retrieve experiment cohort definitions and variant assignments from Amplitude
- Identify control group users who should be excluded from specific Iterable campaign sends
- Add those users to the appropriate Iterable suppression list for the duration of the experiment
Connectors Used: Amplitude, Iterable