Markin + Iterable integration
Decisions as user fields and custom events.
What is a Iterable AI agent?
A Markin and Iterable setup writes the decided action into user profile fields or emits a custom event, so existing Iterable journeys stay in place and simply act on a better input. Channel governance stays with Iterable.
Frequency caps, quiet hours and consent stay enforced by Iterable. Markin only supplies intent, which is what makes the connection safe to switch on incrementally.
What Markin reads
- User fields and channel preferences
- Send and engagement events
What Markin writes back
- User fields with the committed action
- Custom events for journey entry
How the connection works
| Pattern | What it means here |
|---|---|
| Attribute write-back | Markin writes the decision onto the customer profile; your existing journeys read it as an entry condition. Latency is the platform's sync interval. |
| Triggered event | Markin emits an event that starts or advances a journey. Near-immediate, and the channel keeps its own governance. |
What can you ask Markin to do in Iterable?
- How do I add AI decisioning to Iterable?
- Can Iterable journeys be triggered by a churn model?
- What are the best Iterable alternatives for decisioning?
- How do I prove Iterable campaigns cause revenue?
What Markin does in Iterable
- 01Read user profile fields and list membership.
- 02Read send, engagement and purchase events.
- 03Write the chosen action and reason into profile fields.
- 04Emit custom events that trigger the right journey.
- 05Arbitrate so only one journey fires per customer per window.
- 06Maintain a randomised holdout list.
- 07Read outcomes back keyed to the decision ID.
- 08Report incremental revenue per journey.
Scope of work
The growth work behind Iterable
The list above is what Markin touches in Iterable. A connector is only the surface. Below is the work itself: what an analyst, a lifecycle manager, a data scientist and an experimentation lead would do between them, running continuously against your own data.
Read the estate
Normally a data engineer, once, then never refreshed.
- Read contact history so past sends count as pressure on the customer.
- Track catalogue, pricing and plan changes as they happen.
Find where revenue is leaking
Normally a quarterly analyst deep dive.
- Spot pricing and packaging mismatch between what people buy and what they use.
- Spot product friction that correlates with downgrade and cancellation.
Explain why
Normally a two-week investigation pulled off the roadmap.
- Separate mix effects from real behaviour change.
- Rank drivers by how much of the movement each one accounts for.
Write hypotheses worth funding
Normally a workshop, limited to the ideas in the room.
- Attach the evidence and the assumption each one depends on.
- Rank the portfolio by expected value, not by seniority.
Decide per customer
Normally segment rules refreshed when someone has time.
- Arbitrate between every action competing for that same customer.
- Apply frequency caps, fatigue and quiet hours before anything is committed.
Execute in the tools you already run
Normally a ticket, then a slot in next month's calendar.
- Write decisions into the CRM, engagement and warehouse systems already in production.
- Trigger journeys and campaigns that your lifecycle team owns and can edit.
Prove it caused the revenue
Normally argued about, rarely measured.
- Refuse to call a result that has not cleared the evidence standard.
- Publish the readout in the same place for every experiment.
Retire, govern and hand over
Normally nobody's job, so nothing is ever switched off.
- Retire programmes automatically when they stop beating control.
- Re-test assumptions that decay, such as price sensitivity and seasonality.
Iterable questions
- How does Markin connect to Iterable?
- Attribute write-back, Triggered event. Markin writes the decision onto the customer profile; your existing journeys read it as an entry condition. Latency is the platform's sync interval.
- What does Markin read from Iterable?
- User fields and channel preferences; Send and engagement events.
- What does Markin write back into Iterable?
- User fields with the committed action Custom events for journey entry
- Do we have to move our data to Markin?
- No. Markin reads from your warehouse, product events and operational systems in place, on your compute, under the access rules your data team already set. Nothing is copied into a separate customer base and there is no vendor-side profile store to migrate off later.
- Does Markin replace our engagement platform or CDP?
- No, and it should not. Your engagement platform keeps the channel, the templates, the deliverability and the governance. Your CDP keeps identity and consent. Markin adds the layer neither has: deciding which action deserves to exist for each customer, and proving it against a holdout.
- What if the system we use is not listed?
- The four activation patterns cover almost everything: attribute write-back, triggered event, decision API and direct surface rendering. Any system that exposes an API, accepts a table, or can read a warehouse column can receive decisions. New connectors are built during deployment, typically in days.