ASRS On-Site Purchase System with Personalized Impulse Stocking
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Solution Overview
Problem
Existing automated storage and retrieval systems (ASRS) lack the ability to effectively pre-stock items based on customer preferences and history, leading to missed impulse purchase opportunities and reduced customer satisfaction.
Innovation Solution
A system and method that analyzes customer profiles for preferences, purchase, and search history to pre-stock a variety of general and seasonal items at ASRS, using a processor to generate a subset of likely impulse purchases, which are then displayed on an interactive touchscreen terminal for customers to select and update their orders upon arrival, facilitating seamless on-site purchases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If ASRS stocks a wide variety of general and seasonal items, then customer satisfaction and impulse purchase opportunities increase, but inventory management complexity and space requirements increase
Solution Approach 1:
The system performs preliminary analysis of customer profiles, purchase history, and search history to pre-identify likely impulse purchases before customers arrive at the ASRS. Items are pre-stocked based on this analysis, allowing customers to quickly browse and purchase without real-time inventory management complexity during the purchase moment.
Solution Approach 2:
Instead of stocking all possible items uniformly, the system curates a targeted selection of items based on local customer preferences and historical data. Each ASRS location customizes its inventory based on the specific customer base and seasonal trends of that area, optimizing variety while managing complexity.
2Productivity
If ASRS uses customer profile analysis to pre-stock items, then impulse purchase opportunities increase, but data processing complexity and system requirements increase
Solution Approach 1:
The system performs data analysis and item selection in advance, before customers arrive at the ASRS. Customer profiles, purchase history, and search history are analyzed beforehand to pre-identify likely impulse purchases, reducing the complexity of real-time decision-making during the actual purchase process.
Solution Approach 2:
The system automatically analyzes customer data and generates personalized item recommendations without requiring manual intervention. The automated analysis of purchase history and search patterns enables the system to self-optimize its inventory suggestions, reducing the operational complexity burden on staff.
3Loss of time
If ASRS displays personalized item subsets on touchscreen terminals, then customer purchase speed increases, but terminal interaction complexity and technology requirements increase
Solution Approach 1:
The system pre-generates personalized subsets of likely impulse purchase items based on customer profiles before the customer arrives at the terminal. This preliminary curation presents customers with a pre-sorted, relevant item list rather than requiring them to search through entire inventories, significantly reducing search time while keeping the terminal interface simple.
Solution Approach 2:
The touchscreen terminal displays a customized, location-specific item subset tailored to each customer's preferences and history. This localized personalization ensures that each customer sees only the most relevant items, reducing the complexity of navigation and selection while maximizing purchase efficiency.
Data Source
AI summary
A method for an on-site purchase at an automated storage and retrieval system (ASRS) can include: analyzing likely impulse purchases for customers during a given season, the likely impulse purchases being associated with each customer's profile which comprises preferences, purchase history and search history; stocking items for customers to purchase and pick up at the ASRS, the stocked items comprising general and seasonal items, and supplementary items selected based on an analysis of the likely impulse purchases; receiving a customer's order for purchasing an item; detecting a customer's arrival within a predetermined area around the ASRS; offering a subset of the stocked items for the customer to add to the order, updating the order based on customer's purchase selections or declines; completing a payment transaction of the updated order; automatically updating the items for inclusion in the ASRS based on the customer purchase selections or declines.