Virtual Basket Auto-Population for Order Efficiency
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Solution Overview
Problem
Customers face inefficiencies when repeatedly ordering the same items online, as they need to manually add items to their basket each time, which can be time-consuming, especially for regular orders.
Innovation Solution
A system that populates a virtual basket with a preset list of goods based on reference time data and time data associated with the items, allowing customers to efficiently place orders by matching the order time with the item's time data, and facilitates assembly and delivery or pickup at a specified location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If customers manually add items to their basket each time they place an order, then the ordering system maintains simplicity and requires no additional infrastructure, but the time required to place orders increases significantly for repeat customers
Solution Approach 1:
The system performs preliminary actions by automatically populating the virtual basket with preset lists of goods before the customer completes their order. Historical order data is pre-processed and stored as preset lists, which are then automatically retrieved and added to the basket based on matching criteria, eliminating the need for customers to manually add items each time.
Solution Approach 2:
The system creates copies of previous order configurations in the form of preset lists stored in the database. These preset lists are replicated from historical order data and can be automatically instantiated multiple times, allowing customers to quickly reorder the same items without recreating the entire basket each time.
2Productivity
If the system automatically populates the virtual basket with preset lists based on historical data, then ordering efficiency improves for repeat customers, but the complexity of data management and processing increases
Solution Approach 1:
The system segments order data into discrete preset lists that can be independently stored, managed, and retrieved. Each preset list represents a coherent group of items that were ordered together in the past, allowing the system to process and manipulate individual lists rather than entire order histories, thereby reducing processing complexity.
Solution Approach 2:
The system introduces preset lists as an intermediary layer between the customer's ordering action and the detailed historical order data. These preset lists serve as simplified representations that mediate between the complex historical data and the simple act of adding items to the basket, reducing the computational burden on the ordering system.
3Ease of operation
If the system stores and processes preset lists with time data for automatic population, then the convenience for periodic orders is enhanced, but the memory and processing requirements increase
Solution Approach 1:
The system performs preliminary organization of order data by time periods, creating preset lists that are pre-configured with temporal information. This preliminary action allows the system to efficiently match current ordering intentions with historical patterns without storing and processing every individual historical transaction in real-time.
Data Source
AI summary
Techniques for allowing a customer to order goods on-line or remotely and to pick-up the goods at a desired location or store are disclosed. The techniques include receiving a customer order. The customer order includes at least one good. The techniques further include populating a virtual basket with a preset list of goods as a function of reference time data and time data associated with the preset list of goods.