In-Store Shopper Selection for Remote Order Fulfillment
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Solution Overview
Problem
In-store staff face increased burdens when fulfilling online orders from remote buyers, as they need to locate and deliver items, leading to potential labor cost inefficiencies and difficulties in predicting online transaction volumes, making it costly to maintain sufficient staff.
Innovation Solution
A system that selects either an employee or a willing customer to retrieve and deliver items based on the profit margin of the order, using a computing device to identify eligible shoppers and offer incentives, such as discounts or store credit, to motivate customers to perform order fulfillment tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If employees are used to fulfill online orders, then service quality is maintained, but labor costs increase
Solution Approach 1:
The system enables customers to serve themselves by selecting and retrieving their own ordered items from store shelves. The mobile device interface allows customers to navigate to item locations, and they physically collect their orders without employee assistance, thereby eliminating the need for dedicated fulfillment staff while maintaining service quality.
Solution Approach 2:
The patent introduces an intermediary incentive mechanism (financial rewards, discounts, or store credit) that mediates between the retailer and customer. This intermediary reward system motivates customers to voluntarily perform the fulfillment task, transforming them from passive recipients to active participants in the order fulfillment process.
2Productivity
If more staff are hired to handle online orders, then order fulfillment capacity increases, but operational costs increase
Solution Approach 1:
Customers independently complete the fulfillment process by locating and collecting their items using guidance from the mobile interface. This self-service approach eliminates the need for additional staff to handle order retrieval, thereby maintaining high fulfillment capacity without increasing operational costs.
Solution Approach 2:
The system dynamically adjusts incentives based on various parameters such as item location, customer proximity, and order complexity. By optimizing incentive parameters, the system maximizes customer participation while minimizing the cost per fulfillment, thereby scaling capacity without linearly increasing costs.
3Ease of operation
If employees manually locate and deliver items, then customer service is provided, but time consumption increases
Solution Approach 1:
The mobile interface provides real-time navigation guidance to customers, enabling them to quickly locate their items without employee assistance. This self-directed approach reduces the time employees would otherwise spend guiding customers through the store, while customers receive prompt service directly.
Solution Approach 2:
The system pre-calculates and provides optimal navigation routes to item locations before customers begin their retrieval journey. By preparing the navigation path in advance, customers can efficiently move through the store without delays, reducing overall fulfillment time while maintaining helpful guidance.
Data Source
AI summary
A computing device selects an in-store shopper to fulfill an order placed by a remote buyer. In particular, the computing device receives a message via a communications network. This message comprises a purchase order identifying an item offered for sale at a retail store. The computing device identifies a plurality of people physically located at the retail store and selects, from the plurality of people, a shopper to retrieve the item from the retail store and deliver the item to a delivery location. In particular, selecting the shopper is based on a purchase price and corresponding procurement cost of the item. The computing device transmits an order fulfillment request to a communications device associated with the shopper. The order fulfillment request identifies the item.