Abstract: Disclosed are systems and methods for mufti-point destination arrival time analysis. In one aspect, the system may include a memory storing instructions and at least one processor configured to execute the instructions to. The processor performs operations including receiving a request for an order, receiving an acceptance of an order associated with the first external system, determining, upon receiving the acceptance, a first arrival estimate, determining, upon assigning a delivery worker to fulfill the order, a second arrival estimate, and determining, upon receiving confirmation that the delivery worker has retrieved the order from the merchant, a third arrival estimate. Additionally, the operations may include and forwarding, upon their determination, the first, second, and third arrival estimates to the customer.

Abstract: The present disclosure provides systems and methods for redelivering packages to customers, comprising a memory storing instructions and a processor configured to execute the instructions to receive, from a first user device, a notification of a delivery failure of a package, modify a database to assign the notification of the delivery failure and a cause for the delivery failure to the package identifier, modify the database to assign the package identifier to a group, among a plurality of groups, based on a delivery address associated with the package identifier, generate a map of the plurality of groups, and send the map for display on the user device. The map may comprise an activatable icon, and a location of the activatable icon on the map may be associated with the delivery address associated with the package identifier.

Abstract: The embodiments of the present disclosure provide systems and methods for managing inventory placement, comprising a memory storing instructions and at least one processor configured to execute the instructions. The processor may be configured to receive an identifier of a product for inventory placement, and determine, based on historical shipment data stored in a database, a region with the highest customer demand for the product. The processor may predict, using a machine learning algorithm, a product tag associated with the product based on at least a temperature associated with the region with the highest customer demand for the product. The processor may further modify the database to assign the product tag to the product identifier, and assign the product for placement in a fulfillment center. The fulfillment center may be associated with a fulfillment center tag corresponding to the product tag assigned to the product.