Markin + Zendesk
Next best action on the agent's screen, with its reason.
A service contact is the highest-attention moment a customer gives you all year. Deciding what to do with it deserves the same rigour as a campaign, and it is measurable per agent.
Decision APIRead only
What Markin reads
- Ticket volume, reason codes and CSAT
- Contact history per customer
What Markin writes back
- One suggested action per contact, shown in the agent view with its reason
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. |
| Read only | Markin reads signal from this system. Nothing is written back and no schema is changed. |
Zendesk questions
- How does Markin connect to Zendesk?
- Decision API, Read only. 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 Zendesk?
- Ticket volume, reason codes and CSAT; Contact history per customer.
- What does Markin write back into Zendesk?
- One suggested action per contact, shown in the agent view with its reason
- 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.