Online Concierge System Prepopulating Shopping Cart
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Solution Overview
Problem
The existing online concierge systems face inefficiencies in reducing the time between creating a shopping list and successfully obtaining desired items, which affects the overall customer experience, as customers spend more time searching for items rather than browsing.
Innovation Solution
The online concierge system employs machine learning models to intelligently select and prepopulate items in a shopping cart for customers, optimizing item selection based on cost and benefit metrics, allowing third-party pickers to fill the cart before the customer arrives, while the customer completes the procurement of remaining items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the customer picks all items themselves from the shopping list, then the customer has control over item selection, but the time required to obtain all desired items increases significantly
Solution Approach 1:
The patent segments the item selection process into two parts: pre-selected items that will be automatically added to the cart, and remaining items that the customer must still select. This segmentation allows the system to handle time-consuming tasks (picking pre-selected items) while preserving customer control over final selections.
Solution Approach 2:
The system performs preliminary action by pre-selecting items and adding them to the customer's cart before the customer arrives at the store. This eliminates the time-consuming task of manually selecting and adding items during the shopping trip, while the customer still has control over the final cart contents.
2Loss of time
If the system prepopulates all items in the shopping cart automatically, then the time to obtain items is reduced, but the system complexity and decision-making requirements increase
Solution Approach 1:
The patent applies local quality by making different parts of the shopping list have different statuses: some items are marked as pre-selected and will be automatically added to the cart, while other items remain as regular selections requiring customer input. This allows the system to automate only the appropriate portions without overwhelming complexity.
Solution Approach 2:
The system performs partial action by pre-selecting only a subset of items from the shopping list rather than all items. This partial automation reduces the complexity burden on the system while still providing significant time savings for the customer.
3Duration of action of moving object
If third-party pickers are used to prepopulate the shopping cart, then the customer's time for browsing is increased, but the cost and coordination requirements increase
Solution Approach 1:
The patent implements self-service by allowing customers to select items for prepopulation through the online interface, with the system automatically handling the physical picking and cart population. This transfers the time-consuming task from the customer to the system, increasing customer browsing time while managing coordination complexity through automation.
Data Source
AI summary
An online concierge system facilitates creation of shopping lists of items for ordering from a physical retail store and at least partial self-service fulfillment of orders by the customer. To support fulfillment by the customer, the online concierge system may intelligently select one or more items of the order to be picked by a third-party picker and prepopulated to a shopping cart reserved for the customer in advance of the customer arriving at the retail location. The items for prepopulating may be selected based on various factors that optimize prepopulation decisions on an item-by-item basis in accordance with various machine learning models. The online concierge system may furthermore facilitate procurement of the remaining items by the customer through a customer client device that may track item procurement and/or provide guidance for locating items.