Automated Merchant Authority Data Aggregation
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Solution Overview
Problem
Service providers face inefficiencies in aggregating and consolidating merchant information from multiple sources, leading to limited availability and consumer dissatisfaction, as well as reduced reach for merchants due to time-consuming manual filtering and consolidation processes.
Innovation Solution
Automated systems that scrape information from various sources, utilize APIs and web services to structure data, and prioritize information based on source reliability, allowing for efficient identification and storage of merchant data elements, thereby increasing the breadth of information available to consumers and enhancing merchant visibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual filtering and consolidation of merchant information from multiple sources is used, then information accuracy can be maintained, but time consumption and processing efficiency deteriorate
Solution Approach 1:
The patent replaces manual mechanical filtering and consolidation processes with automated computer-based systems that use algorithms, APIs, and web services to scrape, structure, and prioritize merchant information from multiple sources, eliminating time-consuming manual labor while maintaining information accuracy through systematic validation
Solution Approach 2:
The system enables automated self-service information aggregation where computers automatically scrape data from multiple sources, structure it using predefined schemas, prioritize it based on source reliability, and consolidate it without human intervention, allowing the system to serve itself in gathering and organizing merchant information
2Device complexity
If information is obtained from a limited number of sources, then consolidation complexity is reduced, but information availability deteriorates
Solution Approach 1:
The patent creates a universal automated information aggregation system that can handle data from multiple diverse sources (websites, APIs, web services) using a unified approach with standardized data structures and prioritization algorithms, enabling the system to process information from any source type without increasing operational complexity
Solution Approach 2:
The system changes the parameter of information source capacity from limited to extensive by implementing automated scraping and API integration capabilities that can systematically access and process data from numerous sources simultaneously, with computer-based prioritization algorithms managing the increased volume without proportionally increasing complexity
3Loss of information
If automated information aggregation from multiple sources is implemented, then information availability increases, but system complexity increases
Solution Approach 1:
The patent segments the complex information aggregation system into distinct modular components: data scraping modules for different source types, API integration modules, data structuring modules with standardized schemas, prioritization algorithms based on source reliability, and consolidation modules, allowing each component to be developed and maintained independently
Solution Approach 2:
The system introduces intermediary standardized data structures and prioritization algorithms that act as mediators between diverse information sources and the final consolidated output, translating various source formats into a unified structure and filtering information based on predetermined reliability criteria, thereby managing complexity through standardized interfaces
Data Source
AI summary
Architectures and techniques are described related to identifying merchants associated with information obtained from a number of sources and storing portions of the information in data elements related to the merchants. The information may be provided in a structured format that enables the service provider to associate certain information with a particular merchant or in an unstructured format. The service provider may analyze the information received from the sources to determine whether the information includes any merchant identifying information. When the service provider identifies a merchant based on the merchant identifying information, the service provider may extract additional portions of the information received (e.g. merchant reviews, merchant attributes, etc.) and store those additional portions of information in the data element of the merchant. The service provider may utilize the information obtained about merchants for one or more applications, such as directory services, identifying affinities between merchants, and the like.