Markin + Adobe Journey Optimizer integration
Profile attributes and events into the Adobe estate.
What is a Adobe Journey Optimizer AI agent?
A Markin and Adobe Journey Optimizer setup writes committed decisions into Experience Platform profiles and triggers journeys with the reason attached. Adobe ranks offers you configured; Markin decides whether an offer should exist and proves it against a holdout.
Adobe's own decisioning ranks offers you have configured. Markin decides whether an offer should exist at all, and proves the answer against a holdout before it scales.
What Markin reads
- Experience Platform profile attributes
- Journey step events
What Markin writes back
- Profile attributes with the committed action
- Journey trigger events
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 Adobe Journey Optimizer?
- How does Adobe Journey Optimizer decisioning compare to a decision layer?
- Can I write a next best action into Adobe Experience Platform profiles?
- How do I prove incremental revenue from AJO journeys?
- How do I generate new offer ideas rather than ranking existing ones?
What Markin does in Adobe Journey Optimizer
- 01Read Experience Platform profile attributes.
- 02Read journey step and delivery events.
- 03Propose new candidate actions, not only rankings of configured offers.
- 04Write the committed action onto the profile with its reason.
- 05Emit journey trigger events.
- 06Maintain randomised holdouts inside the profile store.
- 07Read outcomes back keyed to the decision ID.
- 08Report incremental revenue per journey and per offer.
Scope of work
The growth work behind Adobe Journey Optimizer
The list above is what Markin touches in Adobe Journey Optimizer. 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.
- Reconcile the same customer across billing, CRM, product and support identities.
- Read consent, subscription and channel eligibility state before anything else.
Find where revenue is leaking
Normally a quarterly analyst deep dive.
- Detect involuntary churn from failed payments, card expiry and retry behaviour.
- Spot onboarding steps where activation falls off and revenue never starts.
Explain why
Normally a two-week investigation pulled off the roadmap.
- Keep the query trail so an analyst can reproduce every number.
- Run the investigation automatically and return the drivers with their evidence.
Write hypotheses worth funding
Normally a workshop, limited to the ideas in the room.
- Write hypotheses continuously across marketing, product, pricing and technical health.
- Attach the expected revenue effect and the population it applies to.
Decide per customer
Normally segment rules refreshed when someone has time.
- Suppress an action rather than send a weak one, and log why.
- Choose the next best action for each customer, for each moment.
Execute in the tools you already run
Normally a ticket, then a slot in next month's calendar.
- Roll a decision batch back cleanly when something looks wrong.
- Leave the estate exactly as it was if Markin stops writing.
Prove it caused the revenue
Normally argued about, rarely measured.
- Stop an experiment early when the evidence is conclusive either way.
- Refuse to call a result that has not cleared the evidence standard.
Retire, govern and hand over
Normally nobody's job, so nothing is ever switched off.
- Show the whole decision trail when legal, finance or an auditor asks.
- Hand the team a portfolio they can read, question and overrule.
Teams use Adobe Journey Optimizer together with
Where this shows up
Adobe Journey Optimizer questions
- How does Markin connect to Adobe Journey Optimizer?
- 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 Adobe Journey Optimizer?
- Experience Platform profile attributes; Journey step events.
- What does Markin write back into Adobe Journey Optimizer?
- Profile attributes with the committed action Journey trigger events
- 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.