Store Trading Area Mapping With User Data And Generative AI
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Solution Overview
Problem
Existing trading area analysis methods often inaccurately set trading areas for stores, leading to inadequate analysis accuracy.
Innovation Solution
An information processing apparatus that receives store designations, estimates trading areas based on user data, and provides map information with estimated trading area characteristics using generative AI for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a trading area is designated by a client device, then the analysis can be performed, but the accuracy of the trading area analysis is inappropriate
Solution Approach 1:
The system automatically determines the trading area based on store information and user data without requiring manual designation by the client device. The analysis unit autonomously performs estimation processing to identify the trading area and its characteristics, enabling the system to serve itself rather than relying on user input for this critical parameter.
Solution Approach 2:
The patent replaces the mechanical/manual designation method with an automated information processing system. Instead of relying on client device input, the system uses computational algorithms to process store information, user data, and geographical information to automatically determine trading areas, substituting manual operations with automated mechanical processing.
2Measurement precision
If manual trading area designation is used, then the system is simple to operate, but the analysis accuracy is insufficient
Solution Approach 1:
The analysis unit divides the trading area determination process into multiple independent estimation processing steps. The system segments the complex task of accurate trading area identification into distinct processing stages, each handling specific aspects of the estimation, thereby managing complexity through structured decomposition.
Solution Approach 2:
The analysis unit is designed as a multi-functional component that handles various tasks including store information processing, user data analysis, geographical information processing, and trading area estimation. By consolidating these functions into a single universal unit, the system manages complexity through functional integration rather than separate modules.
3Measurement precision
If automated trading area estimation is implemented, then analysis accuracy improves, but the system complexity increases
Solution Approach 1:
The system embeds multiple estimation processing functions within a hierarchical structure. The analysis unit contains nested processing stages where user data analysis, store information processing, and geographical information processing are organized in nested layers, allowing complex processing to be managed through structured containment.
Solution Approach 2:
The analysis unit acts as an intermediary between data input and analysis output. It mediates the complex processing by receiving store information, user data, and geographical information, then producing accurate trading area estimates through coordinated processing of these intermediate data elements.
Data Source
AI summary
An information processing apparatus according to the present application includes a reception unit, an analysis unit, and a provision unit. The reception unit receives designation of a store. The analysis unit performs, based on information concerning a user of the store, first estimation processing of estimating a trading area of the store, the designation of which has been received by the reception unit, and second estimation processing of estimating characteristics of the trading area estimated in the first estimation processing. The provision unit provides map information including information indicating the trading area estimated by the analysis unit and information indicating the characteristics of the trading area.