Merchant Analysis System Using Sensor Data for Secondary Characteristics
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Solution Overview
Problem
Consumers face difficulty in distinguishing between similar merchants when making purchasing decisions, as existing systems lack the ability to analyze and leverage unique characteristics beyond basic information.
Innovation Solution
A system and method that collect and analyze basic merchant information, transaction data, and sensor data to determine distinguishing characteristics among merchants, such as peripheral services and user preferences, to provide personalized recommendations to consumers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If consumers rely on basic merchant information for decision-making, then the selection process is simple, but the ability to distinguish between similar merchants is insufficient
Solution Approach 1:
The patent segments merchant information into multiple dimensions including primary characteristics (core services), secondary characteristics (peripheral services), and user preference data. This segmentation allows the system to analyze and compare merchants comprehensively without overwhelming complexity, resolving the contradiction by organizing data structurally.
Solution Approach 2:
The patent introduces additional analytical dimensions beyond basic merchant information by incorporating sensor data from user devices, transaction data, and derived user preferences. This multi-dimensional approach enables precise distinction between similar merchants while managing complexity through structured data layers.
2Adaptability or versatility
If the system analyzes multiple merchant characteristics to provide personalized recommendations, then user satisfaction improves, but the data processing complexity increases
Solution Approach 1:
The system performs preliminary actions by collecting and organizing merchant information, sensor data, and transaction data in advance. User preferences are derived and stored beforehand, enabling quick personalized recommendations without complex real-time processing, thus resolving the contradiction between adaptability and processing complexity.
Solution Approach 2:
The patent introduces an intermediary layer that processes raw sensor data and transaction data into structured user preference profiles. This intermediary processing layer simplifies the connection between complex data sources and personalized recommendations, managing data processing complexity while maintaining high adaptability.
3Measurement precision
If the system collects and analyzes sensor data and transaction data, then distinguishing characteristics are accurately identified, but the amount of data to be processed increases
Solution Approach 1:
The patent extracts only the relevant distinguishing characteristics from large volumes of sensor data and transaction data. By focusing on secondary characteristics and user preferences that directly impact merchant selection, the system achieves accurate identification without processing unnecessary data, resolving the contradiction between precision and data volume.
Solution Approach 2:
The system applies local quality analysis by focusing computational resources on specific merchant characteristics that are most relevant to user preferences and decision-making. Rather than uniformly processing all data, the system identifies and analyzes locally important features, achieving high accuracy with reduced data processing requirements.
Data Source
AI summary
A system or method is provided to analyze and determine distinguishing or secondary characteristics among merchants. In particular, the system may collect basic merchant information, such as name, type of business, products/services offered, location, owner, and other basic information regarding merchants. The system may determine merchants that are similar in type, size, location, of other factors, based on the basic information. They system may then determine distinguishing or secondary characteristics among similar merchants. The distinguishing or secondary characteristics may be determined from consumers' transactions with the merchants or other data detected by sensors or devices.