Markin + Optimizely
Product-side hypotheses executed as flags, read as revenue.
Experimentation platforms answer the question you brought them. Markin's job is to produce a continuous supply of questions worth asking, and to keep the ones that pay.
Decision APITriggered event
What Markin reads
- Experiment definitions and assignment logs
- Feature flag exposure
What Markin writes back
- Proposed variants with expected value
- Targeting decisions per user
How the connection works
| Pattern | What it means here |
|---|---|
| Decision API | The surface asks Markin for a decision at render time and receives one action plus its reason, with a defined fallback. |
| Triggered event | Markin emits an event that starts or advances a journey. Near-immediate, and the channel keeps its own governance. |
Optimizely questions
- How does Markin connect to Optimizely?
- Decision API, Triggered event. The surface asks Markin for a decision at render time and receives one action plus its reason, with a defined fallback.
- What does Markin read from Optimizely?
- Experiment definitions and assignment logs; Feature flag exposure.
- What does Markin write back into Optimizely?
- Proposed variants with expected value Targeting decisions per user
- 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.