Abstract: A buy-online pickup-in-store (BOPIS) order at risk of abandonment is saved by converting the order to same-day delivery. A risk deadline is established using a combination of cognitive prediction, a customer-specific time frame, order constraints, and real-time data. The cognitive prediction uses a customer profile having historical data pertaining to previous BOPIS orders from this customer. If the product is not picked up by the risk deadline, a check is made to see if same-day delivery is feasible. If so, a notification is transmitted to the customer with proposed delivery details. The notification can be sent at an optimal time based on previous notifications sent to the customer and time constraints related to the order, and using an optimal communication channel based on previous engagement rates with the customer over different communication channels. Once confirmation is received from the customer, the product is shipped, saving the sale.

Abstract: A dairy product that is fruit-flavored and reduced in sugar includes a washed fermented dairy material and a washed fruit-based material. Separation technology for the removal of sugars from a fermented dairy material and a fruit-based material to produce the dairy product includes the repetition of a wash cycle involving a dilution step and a separation step. The separation technology achieves at least a 10% reduction in total sugars.

Abstract: In order to detect possible damage to a delivered product, a set of first images of the product is created prior to delivery which are used to generate a first 3D photogrammetry model, and a set of second electronic images are created after delivery which are used to generate a second 3D photogrammetry model. The two models are then compared to determine whether there is a sufficient deviation to conclude the product has been damaged. The comparison is performed by a cognitive system trained with samples of before/after photogrammetry model pairs each associated with either a damaged condition or a not damaged condition. The baseline photogrammetry model is part of a blockchain record and the recipient photogrammetry model is added to the blockchain record. Intermediate photogrammetry models can also be built where there is more than one shipper along the delivery route to assign liability to the proper party.

Abstract: A buy-online pickup-in-store (BOPIS) order at risk of abandonment is saved by converting the order to same-day delivery. A risk deadline is established using a combination of cognitive prediction, a customer-specific time frame, order constraints, and real-time data. The cognitive prediction uses a customer profile having historical data pertaining to previous BOPIS orders from this customer. If the product is not picked up by the risk deadline, a check is made to see if same-day delivery is feasible. If so, a notification is transmitted to the customer with proposed delivery details. The notification can be sent at an optimal time based on previous notifications sent to the customer and time constraints related to the order, and using an optimal communication channel based on previous engagement rates with the customer over different communication channels. Once confirmation is received from the customer, the product is shipped, saving the sale.

Abstract: A computer system monitors network sites to provide expedited delivery services. Operation of a network site is monitored to determine that an item is being obtained from the network site. The network site is scraped to determine that the item is available at a physical location associated with the network site. A courier service is identified to transport the item from the physical location to the delivery location. Delivery of the item is enabled by the courier service to the delivery location. Embodiments of the present invention further include a method and program product for monitoring network sites to provide expedited delivery services in substantially the same manner described above.

Abstract: In order to detect possible damage to a delivered product, a set of first images of the product is created prior to delivery which are used to generate a first 3D photogrammetry model, and a set of second electronic images are created after delivery which are used to generate a second 3D photogrammetry model. The two models are then compared to determine whether there is a sufficient deviation to conclude the product has been damaged. The comparison is performed by a cognitive system trained with samples of before/after photogrammetry model pairs each associated with either a damaged condition or a not damaged condition. The baseline photogrammetry model is part of a blockchain record and the recipient photogrammetry model is added to the blockchain record. Intermediate photogrammetry models can also be built where there is more than one shipper along the delivery route to assign liability to the proper party.

Abstract: A buy-online pickup-in-store (BOPIS) order at risk of abandonment is saved by converting the order to same-day delivery. A risk deadline is established using a combination of cognitive prediction, a customer-specific time frame, order constraints, and real-time data. The cognitive prediction uses a customer profile having historical data pertaining to previous BOPIS orders from this customer. If the product is not picked up by the risk deadline, a check is made to see if same-day delivery is feasible. If so, a notification is transmitted to the customer with proposed delivery details. The notification can be sent at an optimal time based on previous notifications sent to the customer and time constraints related to the order, and using an optimal communication channel based on previous engagement rates with the customer over different communication channels. Once confirmation is received from the customer, the product is shipped, saving the sale.

Abstract: A buy-online pickup-in-store (BOPIS) order at risk of abandonment is saved by converting the order to same-day delivery. A risk deadline is established using a combination of cognitive prediction, a customer-specific time frame, order constraints, and real-time data. The cognitive prediction uses a customer profile having historical data pertaining to previous BOPIS orders from this customer. If the product is not picked up by the risk deadline, a check is made to see if same-day delivery is feasible. If so, a notification is transmitted to the customer with proposed delivery details. The notification can be sent at an optimal time based on previous notifications sent to the customer and time constraints related to the order, and using an optimal communication channel based on previous engagement rates with the customer over different communication channels. Once confirmation is received from the customer, the product is shipped, saving the sale.

Abstract: A method, computer system, and computer program product for in-transit package delivery is provided. The embodiment may determine whether package dimensions satisfy one or more preconfigured conditions. The embodiment may also, in response to determining the package dimensions satisfy the one or more preconfigured conditions, receive real-time location data and travel data for a user recipient and a courier. The embodiment may further determine a target delivery destination and target delivery time window. The embodiment may also transmit a delivery notification to the user recipient and the courier.

Abstract: A computer system monitors network sites to provide expedited delivery services. Operation of a network site is monitored to determine that an item is being obtained from the network site. The network site is scraped to determine that the item is available at a physical location associated with the network site. A courier service is identified to transport the item from the physical location to the delivery location. Delivery of the item is enabled by the courier service to the delivery location. Embodiments of the present invention further include a method and program product for monitoring network sites to provide expedited delivery services in substantially the same manner described above.