20240037588. LOCATION-BASED ASSIGNMENT OF SHOPPER-LOCATION PAIRS simplified abstract (Maplebear Inc. (dba Instacart))

LOCATION-BASED ASSIGNMENT OF SHOPPER-LOCATION PAIRS

Organization Name

Maplebear Inc. (dba Instacart)

Inventor(s)

Rockson Chang of Somerville MA (US)

Licheng Yin of Burlingame CA (US)

Chen Zhang of San Jose CA (US)

Michael Chen of San Francisco CA (US)

Aaron Dou of Santa Clara CA (US)

Radhika Anand of Sunnyvale CA (US)

Nicholas Sturm of Denver CO (US)

Ajay Sampat of San Francisco CA (US)

LOCATION-BASED ASSIGNMENT OF SHOPPER-LOCATION PAIRS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240037588 titled 'LOCATION-BASED ASSIGNMENT OF SHOPPER-LOCATION PAIRS

Simplified Explanation

The present disclosure is about a method and system for determining shopper-location pairs in an online shopping concierge platform. It involves identifying available shoppers and warehouse locations in a geographic area, and using machine learning models to optimize shopper-location pairs based on travel time.

• The method and system identify available shoppers and warehouse locations associated with an online shopping concierge platform in a specific geographic area.
• Machine learning models are used to determine the best shopper-location pairs based on the available shoppers, warehouse locations, and travel time.
• The optimization is done to minimize the time required for shoppers to travel from their current locations to the warehouse locations.

Potential applications of this technology:

• Online shopping concierge platforms can use this method to efficiently match shoppers with nearby warehouse locations, improving the overall shopping experience.
• Retailers can utilize this system to offer faster delivery options by strategically locating warehouses based on shopper demand and travel time.
• Logistics companies can optimize their operations by identifying the most efficient shopper-location pairs, reducing travel time and costs.

Problems solved by this technology:

• The method solves the problem of efficiently matching shoppers with warehouse locations in an online shopping concierge platform.
• It addresses the challenge of minimizing travel time for shoppers, improving the overall efficiency of the system.
• The system helps overcome the logistical challenge of managing shopper-location pairs in a geographic area.

Benefits of this technology:

• Shoppers can enjoy faster and more convenient online shopping experiences with reduced travel time for order fulfillment.
• Retailers can improve customer satisfaction by offering faster delivery options and optimizing their operations.
• Logistics companies can streamline their processes and reduce costs by optimizing shopper-location pairs based on travel time.

Original Abstract Submitted

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.