Transaction Processing with Purchase-Based Dish Recommendations
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Solution Overview
Problem
Existing systems fail to effectively promote sales through recipe introductions to customers, despite increasing customer service quality.
Innovation Solution
A transaction processing system that includes updating means to register merchandise items, settling means to determine prices, and introducing means to suggest recipes based on purchased items, using a large-scale language model to propose dishes considering the customer's climate and purchase history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If recipe introductions are provided to customers, then customer service quality is improved, but sales promotion effectiveness is insufficient
Solution Approach 1:
The system changes the parameters of recipe introduction by incorporating climate data (temperature, humidity) and purchase history analysis to personalize recommendations. This transforms generic recipe suggestions into targeted, climate-aware promotions that align with customer behavior patterns, thereby improving sales effectiveness while maintaining service quality
Solution Approach 2:
The system implements feedback mechanisms by analyzing customer purchase history and climate conditions to continuously refine recipe recommendations. The feedback loop involves monitoring customer responses to introductions and adjusting future recommendations based on this data, making the sales promotion more effective over time
2Device complexity
If generic recipe introductions are made, then customer service is simplified, but sales promotion is ineffective
Solution Approach 1:
The system enables self-service through automated analysis of purchase history and climate data, where the system independently generates personalized recipe recommendations without requiring manual intervention. This automation maintains simplicity in operation while significantly improving sales promotion effectiveness through data-driven personalization
Solution Approach 2:
The system achieves multi-functionality by integrating multiple data sources (purchase history, climate data) and performing multiple functions (analysis, recommendation generation, personalized introduction) within a unified system. This comprehensive approach improves sales promotion effectiveness while keeping the user interface simple
Data Source
AI summary
According to one embodiment, a transaction processing system includes an update unit, a settlement unit, a judgement unit, and an introduction unit. The update unit updates, at each time when a merchandise item is designated through an operation by a customer, list data representing a list of transacted merchandise items to contain the merchandise item as a transacted merchandise item. The settlement unit settles a price of the transacted merchandise item contained in the list represented by the list data in response to a designation of a settlement. The judgement unit judges, at each time when the list data is updated by the update unit, a dish using a transacted merchandise item contained in a list represented by the updated list data. The introduction unit introduces a dish judged by the judging unit to the customer.