Synchronize contacts (MEP)

Performs a full load on the first run, then processes only new or changed records on subsequent runs using DinMo’s delta detection logic.Overview

In this destination service, DinMo will export and update custom attributes values in the contacts table.

To do so, you will need to go through these three steps:

• Creating a Batch destination. Refer to the corresponding section for more info.

• Creating a user segment composed of all the users and their attributes that will be updated in Batch. Refer to this step-by-step tutorial to learn how to build segments without SQL in DinMo.

• Activating the segment to the Batch destination to start sending data. Refer to the corresponding section for more info.

Each time the activation will be running:

• All attributes values that have changed since the last activation will be updated in Batch

Note that only users of the segment who have an identifier (email address or external ID) linked to a Batch contact will be updated. Batch API does not support contact creation, so DinMo will only update existing contacts without creating new ones.

Destination setup

To start updating attributes, you are first required to create a Batch destination with the corresponding destination service.

Learn how to create such a destination in our step-by-step tutorial

Activation configuration

Once the destination has been setup, and your DinMo segment created, you can create an activation to start sending data to Batch right away.

Learn how to activate a segment in our step-by-step tutorial

Run types and Sync Modes

When configuring your sync, you will be asked to choose the Run Type and the Sync Mode.

For Batch MEP activations, here are the available options:

Run Type	Description	Use Case	Behavior
FULL ONLY	Processes all data from the source and applies the selected sync mode to all records.	Initial load when setting up a new source or destination Full rebuild after major data model changes (schema, business logic, identifiers) Recovery after data corruption or desynchronization	Every run reprocesses the entire dataset No delta detection is applied Can be resource-intensive and time-consuming on large datasets Guarantees full consistency with the source at each run
FULL THEN DELTA	The first sync processes all records. All following syncs applies the selected sync mode only to changed records, based on DinMo’s delta detection logic.	Standard production setup for most pipelines Regular synchronization with large datasets Use cases requiring freshness while optimizing performance and costs	First run performs a full load Subsequent runs process only created, updated, or deleted records Relies on DinMo’s internal delta detection logic Faster execution and reduced compute usage compared to FULL ONLY

Sync modes determine how data is synchronized between your data source and your Batch dashboard. They control whether to insert new records, update existing ones, or both, and how to handle the synchronization process.

For the Batch destination, here are the available options:

Sync Mode	Description	Use Case	Behavior
UPSERT (full only)	Processes all records from the source at every run and applies upsert logic to each record. No change detection is performed.	Initial data loads Small datasets One-off reprocessing or data recovery Connectors or sources without reliable delta keys	Every record is sent to the connector on each run Connector decides whether to insert or update each record No deletions are handled Highest consistency, lowest efficiency
UPSERT (full then delta)	Performs a full load on the first run, then processes only new or changed records on subsequent runs using DinMo’s delta detection logic.	Standard production setup Large datasets with limited changes Frequent syncs requiring good performance	First run processes all records Subsequent runs process only inserted or updated records Connector inserts new records and updates existing ones No deletions are handled Much faster and more cost-efficient than FULL ONLY
MIRROR (full then delta)	Performs a full load on the first run, then keeps the destination fully aligned with the source, including deletions, using delta detection.	Maintaining an exact replica of the source Datasets with frequent updates and deletions Use cases requiring strict data consistency	First run processes all records Subsequent runs insert new records, update changed records, and delete records missing from the source Requires connector support for delete operations More processing than Upsert (delta) but ensures full synchronization

• Upsert mode never deletes records from the destination, even if they are removed from the source.

• Mirror mode ensures full alignment between source and destination, including deletions.

• FULL THEN DELTA is the recommended default for most production pipelines.

• Choosing FULL ONLY should be intentional and limited to specific operational needs.

Fields mapping

In the Fields mapping section, you are asked to specify the field contained in your DinMo segment that Batch will use to link each segment's records to a Batch contact. Depending on your Batch configuration, it may be the email address of the user, or another external ID.

Custom Attributes

In this section, any field you select will be exported as a new custom attribute in Batch. The associated field will have the same name in Batch and DinMo.

These values of the attributes selected here will then be updated at each activation.