Selecting a location for order fulfillment based on machine learning model prediction of incomplete fulfillment of the order for different locations
US12131358B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 11, 2020 |
| Grant date | Oct 29, 2024 |
| Priority date | — |
| Expiry date | Mar 27, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldIT methods for management
- WIPO sectorElectrical engineering
Abstract
In an online concierge system, a shopper retrieves items specified in an order by a customer from a retail location. The online concierge system optimizes order fulfillment by selecting a retail location for an order that is most time-efficient and that is most likely to have each of the item in the order available. Hence, the online concierge system may select a less convenient retail location that is more likely to have each item being ordered available. To predict whether a retail location incompletely fulfill the order if selected to fulfill the order, the online concierge system trains a machine learning model based on prior orders fulfilled by the retail location, a shopper retrieving items in the order, items in the order, and other features.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.