Get Store Orders
Orders
Get Store Orders
Retrieve all orders for a specific store with flexible filtering options including date ranges, status, and pagination.
GET
Get Store Orders
This endpoint provides comprehensive access to all orders for a specific store with powerful filtering capabilities. Perfect for store management, reporting, and operational oversight.Documentation Index
Fetch the complete documentation index at: https://developer.lulacommerce.com/llms.txt
Use this file to discover all available pages before exploring further.
This endpoint supports advanced filtering and pagination to efficiently handle large volumes of order data while providing flexible search capabilities.
Query Parameters
The unique identifier of the store whose orders you want to retrieve
Filter orders by status (e.g., “pending”, “accepted”, “in_progress”, “completed”, “canceled”)
Filter by delivery platform (e.g., “DoorDash”, “UberEats”, “GrubHub”, “LulaDirect”)
Start date for filtering orders (ISO 8601 format: YYYY-MM-DDTHH:mm:ssZ)
End date for filtering orders (ISO 8601 format: YYYY-MM-DDTHH:mm:ssZ)
Page number for pagination
Number of orders per page (max 100)
Field to sort by (“createdAt”, “price”, “status”, “partner”)
Sort direction (“asc” or “desc”)
Response
Array of order objects matching the filter criteria
Pagination information for the response
Summary statistics for the filtered orders
Response Example
Filter Examples
Filter Examples
Get Today’s OrdersGet Pending Orders from UberEatsGet Last Week’s Completed Orders
Time Zones: All timestamps are returned in UTC. Convert to your local timezone as needed for display purposes.
Use Cases
Common Use Cases
Common Use Cases
Daily Operations Dashboard
- Get today’s orders with status filtering
- Monitor pending orders requiring attention
- Track fulfillment performance
- Calculate daily/weekly/monthly revenue
- Analyze order value trends
- Track performance by delivery platform
- Monitor order completion rates
- Analyze peak order times
- Track customer satisfaction metrics
- Review historical order patterns
- Identify popular items and trends
- Plan inventory based on demand

