Location Computing System for Marketplace Expansion
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Solution Overview
Problem
Identifying suitable new geographic locations for offering items across multiple electronic marketplaces is computationally expensive and challenging due to the volume and distribution of data across multiple databases, making it difficult for users to determine which locations to expand into and how to optimize item placement.
Innovation Solution
A method and system utilizing database structures and machine learning to predict the success rate of an item in new locations, providing user interfaces that display predicted successful locations, value-rule parameters, and options to mitigate obstacles, allowing users to efficiently enter new markets by optimizing item positioning and pricing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis of transaction data across multiple databases is performed to identify suitable new geographic locations, then location identification accuracy can be improved, but computational cost and time consumption increase significantly
Solution Approach 1:
The system creates a virtual model of the marketplace by copying and storing transaction data from multiple databases into a standardized format. This virtual representation allows rapid analysis and location identification without repeatedly querying the original complex databases, significantly reducing time consumption while maintaining identification accuracy.
Solution Approach 2:
The patent introduces an intermediary layer (the marketplace system with standardized data structures) between the user and the multiple transaction databases. This intermediary pre-processes and organizes data from various sources, enabling fast location identification without direct complex queries to underlying databases, thus resolving the time-accuracy tradeoff.
2Measurement precision
If comprehensive data from multiple databases is analyzed to determine item demand across locations, then prediction accuracy improves, but system complexity increases
Solution Approach 1:
The system segments the complex multi-database analysis task into distinct components: data extraction from individual databases, standardized transformation, aggregation by geographic location, and demand calculation. This segmentation allows each component to be managed independently, reducing overall system complexity while maintaining comprehensive data analysis for accurate predictions.
Solution Approach 2:
The patent transforms data from multiple different database schemas into a standardized parameter format. By changing the representation parameters of incoming data to a common structure, the system simplifies subsequent analysis operations while preserving all necessary information for accurate demand prediction across locations.
3Measurement precision
If users manually evaluate each potential location for item offering, then decision quality can be improved, but productivity decreases
Solution Approach 1:
The system performs preliminary analysis and evaluation of potential locations automatically before user decision-making. It pre-calculates demand metrics, identifies promising geographic areas, and prepares location recommendations, allowing users to make high-quality decisions faster by reviewing pre-processed information rather than evaluating each location from scratch.
Solution Approach 2:
The system provides feedback to users in the form of data-driven location recommendations and demand predictions. This automated feedback loop delivers actionable insights about which locations are most promising for item offering, enabling users to maintain high decision quality while significantly increasing expansion productivity through informed, rapid choices.
Data Source
AI summary
Systems and methods are provided for using information obtained from a various databases to efficiently identify new or additional geographic locations in which a user, such as a seller, a manufacturer, a distributor, etc. can offer its goods and/or services for acquisition. A user interface is provided that provides information on such locations and value details for a user to utilize in determining where to offer or list an item for acquisition.