Ledgers
The Ledgers section provides a transaction-level audit trail for every points movement in the loyalty program. Each entry records a single debit or credit to a customer's wallet with full traceability: the transaction that triggered it, the loyalty rule that generated it, the store where it occurred, and the resulting balance.
This is the authoritative source for financial reconciliation, external audits, and dispute resolution — any discrepancy between reported points and actual balances can be traced to the exact event.
When to use Ledgers vs. Campaign Performance
Use Campaign Performance to measure campaign effectiveness (redemption rates, ROI, audience reach). Use Ledgers for financial-grade traceability: reconciling balances, auditing specific customers, or investigating a disputed points movement.
Use Cases
| Use Case |
|---|
| → Reconcile the total points issued in a period against the expected value from your loyalty rules configuration. |
| → Audit the full points history of a specific customer to resolve a support dispute. |
| → Verify that expiration events ran correctly and no points were incorrectly expired. |
| → Export raw ledger data to feed into a finance system or external reporting tool. |
| → Confirm that a points correction or manual adjustment was applied correctly. |
| → Investigate an anomalous balance by tracing each debit and credit in chronological order. |
| → Produce a regulatory compliance report showing all points transactions in a jurisdiction during a period. |
Filters
| Filter | Description |
|---|---|
| Date From / To | Analysis window — filters by the timestamp of each ledger entry |
| Country | Filter by country of the transaction location |
| Store | Filter by specific store or store group |
| Movement Type | Select one or more: Issuance, Activation, Redemption, Expiration, Correction, Cancellation |
| Rule | Filter by the loyalty rule that triggered the movement |
| Customer | Search by customer ID or email to view a single customer's history |
| Segment | Filter by a saved customer audience |
Ledger Entry Structure
Each ledger entry represents a single points movement event and contains:
| Field | Description |
|---|---|
| Timestamp | Exact date and time of the movement |
| Customer ID | The enrolled customer whose wallet was affected |
| Movement Type | Issuance, Activation, Redemption, Expiration, Correction, or Cancellation |
| Points Delta | Points credited (positive) or debited (negative) in this event |
| Running Balance | Customer's total available balance after this movement |
| Monetary Value | Currency equivalent of the points delta |
| Rule Name | The loyalty rule that generated this movement |
| Transaction ID | The cart/checkout transaction that triggered the event (where applicable) |
| Store | Location where the underlying transaction occurred |
| Expiry Date | For issuance entries: the date on which these points will expire if not redeemed |
Movement Types
| Type | Description |
|---|---|
| Issuance | Points credited to a customer's wallet as a result of a purchase or qualifying event. Points may be issued in a pending state if the program uses an activation delay. |
| Activation | Pending points that become available for redemption after the activation window has elapsed (e.g. 15-day returns period). |
| Redemption | Points burned by a customer in exchange for a reward or cashback. |
| Expiration | Points that reached their expiry date without being redeemed. Expiration is processed automatically by the scheduled jobs. |
| Correction | Manual adjustment applied by a loyalty administrator (credit or debit). Includes a reason field for audit trail. |
| Cancellation | Points reversal triggered by a cancelled or returned transaction. |
Export
The Ledgers section supports raw data export. Use the Download option to export the filtered ledger as a CSV or XLSX file containing all entry fields. For large date ranges or high-volume programs, exports are generated asynchronously and delivered to the requesting user's email.
How It Works
Ledger entries are written in real time as the Streaming API processes cart and event data. Each points rule execution creates one or more ledger rows. The BigQuery dataset retains the full history with no aggregation — every individual entry is preserved.
Because ledger data is at line level (not aggregated), Loyalty Insights loads only the filtered subset. Use narrow date ranges and specific filters (store, customer, rule) for best performance when exploring through the interface. For bulk analysis across the full dataset, connect directly to BigQuery using the integration credentials available in the platform settings.