Group loyalty data surfaces in Insights+ through the standard Points and Points Redemption Summary export templates. Group activity doesn't create a separate data model. Instead, it's identifiable through specific fields within the existing fact tables.

Finding group transactions in reports

Standard fact tables use dim_event_user_id to identify the individual member who triggered an event, not the group entity. To analyze performance at the group level, you need to join on group membership data to associate individual member IDs with their respective groups.

There are two fields for identifying group-specific activity:

• In the Points Redemption Summary fact table, dim_redemption_type_id takes the value group_redemption for points redeemed from a group wallet. For these rows, point_category_id is set to -1.
• In the Reward Fact tables, the group_loyalty_redemption field identifies redemptions made against a group wallet.

In the event log data, group transactions are recorded under the GroupTransactionAdd event, separate from the individual TransactionAdd event. Filter on this event name to isolate transactions made on behalf of a group.

Once you have identified the relevant fields and events, use the following export templates to pull the data.

Exporting group loyalty data

Use the following Insights+ export templates to pull group loyalty performance data.

To schedule exports, go to Insights+ > Data Connectors > Export Schedules and create a new schedule using the relevant template.

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Note:

Standard export templates don't include a native group-level aggregation. Aggregating data to the group level requires post-processing the exported data using the group membership list, which you can download from the Member Care group view or retrieve via GET /v2/userGroup2 (see Get user group details).