Cross-Marketplace Product Data Linking With Unified Identifier Tables
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Solution Overview
Problem
Existing systems fail to provide a timely and unified method for consolidating commercial and advertising data across multiple online marketplaces, which use different product identification protocols, making it difficult for sellers to optimize advertising budgets and make informed decisions.
Innovation Solution
A system and method that uses a proprietary database to link product data from multiple channels, employing a unique identifier (DMC-I) to consolidate data from various marketplaces, transforming it into a unified format, and continuously updating this data to create a comprehensive primary table for easy analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is retrieved from each channel separately using individual identification protocols, then data accuracy for each channel is maintained, but consolidation time increases and decision-making becomes delayed
Solution Approach 1:
The patent introduces a central database as an intermediary component that receives, stores, and harmonizes product data from multiple channels. This database acts as a mediator between the diverse channel-specific data sources and the consolidation process, enabling efficient data integration without sacrificing accuracy. The database stores both channel-specific identifiers and unified identifiers, allowing precise matching and consolidation across channels while maintaining data integrity from each source.
2Reliability
If multiple identification protocols are used across different channels, then channel-specific data integrity is preserved, but product matching complexity increases
Solution Approach 1:
The patent implements a universal identification system that works across all channels. The central database stores multiple types of identifiers (channel-specific identifiers like ASIN, GTIN, and unified identifiers) for each product, allowing the system to universally match products regardless of which channel they originate from. This multi-functional approach enables the same database structure to handle diverse identification protocols while maintaining data integrity from each channel.
Solution Approach 2:
The central database serves as an intermediary layer that translates between different identification protocols. It receives data with various channel-specific identifiers, stores them alongside unified identifiers, and enables matching across channels without requiring complex real-time translation logic in the reporting system. This mediator approach simplifies the matching complexity while preserving channel data integrity.
3Loss of information
If cross-channel consolidation is implemented, then comprehensive product performance visibility is achieved, but system complexity and data harmonization effort increase
Solution Approach 1:
The patent merges data from multiple channels into a single central database that provides comprehensive product performance visibility. By consolidating channel-specific identifiers, unified identifiers, and performance metrics in one database, the system achieves complete product performance visibility across all channels. This merging approach eliminates information loss while managing system complexity through a unified data structure rather than multiple separate systems.
Data Source
AI summary
A method and associated system for linking product data from multiple channels of online marketplaces, the method including a) providing at least one first parameter associated with a product, b) generating a primary table based on the at least one first parameter, c) determining at least one first value associated with the at least one first parameter, d) obtaining data associated with the product from multiple channels of online marketplaces, e) transforming the data into a unified format, where the transformed data includes at least one second value, f) automatically generating an updated primary table based on the primary table, the at least one first value, and the transformed data including the at least one second value in an iterative or recursive manner, and g) continuously replacing the primary table with the updated primary table in an iterative or recursive manner through repeating steps (d)-(f).