Abstract: A device may obtain historical order data comprising orders submitted by users to an online system, each order indicating a retailer location and a timestamp. A device may generate a first set of training examples, each training example indicating order demand at a retailer location during one period of time from a first set of periods of time. A device may train the demand forecast prediction model with the first set of training examples. A device may apply the demand forecast prediction model to a second set of periods of time to predict order demand for each period of time in the second set of periods of time. A device may track order demand across each period of time in the second set of periods of time. A device may generate a second set of training examples, each training example indicating a difference between the predicted order demand and the tracked order demand at the retailer location during each period of time from the second set of periods of time.

Abstract: The present disclosure is directed to determining shopper-location pairs. In particular, the methods and systems of the present disclosure may identify a set of available shoppers associated with an online shopping concierge platform and located in a geographic area; identify a set of available warehouse locations associated with the online shopping concierge platform and located in the geographic area; and determine, based at least in part on the set of available shoppers, the set of available warehouse locations, and one or more machine learning (ML) models, a set of shopper-location pairs optimized based at least in part on time required by the set of available shoppers to travel from their respective current locations to one or more of the set of available warehouse locations.

Abstract: The present disclosure is directed to determining shopper-location pairs. In particular, the methods and systems of the present disclosure may identify a set of available shoppers associated with an online shopping concierge platform and located in a geographic area; identify a set of available warehouse locations associated with the online shopping concierge platform and located in the geographic area; and determine, based at least in part on the set of available shoppers, the set of available warehouse locations, and one or more machine learning (ML) models, a set of shopper-location pairs optimized based at least in part on time required by the set of available shoppers to travel from their respective current locations to one or more of the set of available warehouse locations.