Patent ID: 11900430
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method of converting a buy-online pickup-in-store (BOPIS) order for a product by a customer to a delivery order comprising:
establishing a threshold deadline for pickup of the product representing a likelihood that the online order is at risk of abandonment, using a risk perdition stored in memory of a computer system;
monitoring, using a BOPIS system stored in the memory of the computer system, a pickup status of the online order to determine that the product has not been picked up by the threshold deadline, the monitoring using an abandonment detection module;
determining that delivery of the product after the threshold deadline from a location of a store to an address of the customer is still feasible for a known delivery charge, the determining of the feasibility using the abandonment detection module, wherein the abandonment detection module communicates with the store via a network, the store providing information pertaining to the online order to the abandonment detection module;
communicating with a shipper via the network to inquire as to availability of a shipper to pick up the product at the store and deliver it to the address of the customer, as well as the cost for the delivery and time constraints;
transmitting a notification to the customer that the product can be delivered with proposed delivery details including the delivery charge, using a delivery options module and a notification module in the memory of the computer system;
receiving, using a cognitive system having a neural network, a confirmation for delivery from the customer responsive to the notification, the cognitive system being stored in the memory of the computer system;
collecting, using the cognitive system, additional information from the customer for scheduling a delivery;
analyzing a current customer profile and historical data using natural language processing;
analyzing the natural language by generating models for scoring and ranking results for training based on large sets of inputs and outputs as answers to determine a confidence level of an answer of the answers to a query, the query including when the product is picked and packed;
communicating, using the cognitive system, with a store associate for confirming the product has been picked and packed; and
scheduling, using the cognitive system, a delivery for the product.