Commerce Architecture GUI for Canonical Data Mapping
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Solution Overview
Problem
Conventional CRM and commerce systems face challenges in integrating customer data from disparate sources, determining data provenance, providing audit logs, and reconciling data with different time scales, which are essential for compliance with privacy laws and efficient data management.
Innovation Solution
The Commerce Architecture GUI enables users to connect various data sources, map consumer data to a canonical data model, define matching and reconciliation rules, and provide data stewardship through point-and-click user interfaces, allowing for efficient data management and query results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional database or CRM systems are used to manage customer data, then data storage and basic access are achieved, but the ability to integrate customer data from disparate, disconnected sources and create a master record is lost
Solution Approach 1:
The patent introduces an intermediary layer (data integration service or ETL process) that sits between disparate data sources and the CRM system. This intermediary handles data transformation, normalization, and integration, allowing the CRM to work with unified customer records without directly managing the complexity of multiple data sources. The intermediary mediates between heterogeneous sources and the standardized CRM data model.
2Productivity
If administrators write specific code to parse through large amounts of data to track events and generate follow-up emails, then cart abandonment tracking functionality is achieved, but the process becomes time consuming, expensive, and error prone
Solution Approach 1:
The system implements self-service capabilities where the CRM automatically tracks cart abandonment events, identifies affected customers, and generates follow-up emails without requiring administrator intervention. The system autonomously parses data, applies business rules, and executes marketing actions, eliminating the need for manual code writing and reducing operational complexity.
Solution Approach 2:
The patent implements preliminary action by pre-configuring data parsing rules, event tracking logic, and email generation templates during system setup. This preliminary configuration allows the system to automatically handle cart abandonment events without requiring administrators to write code when events occur, streamlining the process and reducing errors.
3Adaptability or versatility
If administrators learn the API for each system to program a query to interface with different systems, then data retrieval from multiple sources is achieved, but the learning curve and programming requirements increase
Solution Approach 1:
The patent implements a universal data access layer that provides a single, standardized interface for retrieving data from multiple different systems. Instead of requiring administrators to learn and use different APIs for each system, the universal interface abstracts away the underlying system-specific protocols and provides consistent data access methods, making the system easier to operate while maintaining multi-system capability.
4Reliability
If conventional systems are used for data management, then basic data storage is achieved, but data provenance determination and audit log provision are lost
Solution Approach 1:
The patent implements feedback mechanisms that automatically track and record data provenance information and audit logs as data moves through the system. The system continuously monitors data operations, captures metadata about data sources and transformations, and maintains audit trails. This automated feedback loop ensures compliance with privacy laws by providing complete visibility into data lineage without requiring complex manual tracking infrastructure.
Data Source
AI summary
Disclosed herein are method, system and device embodiments for setting up a graphical user interface (GUI) for a commerce architecture. An embodiment operates by providing a GUI that displays a first button for adding a first data source and a second button for adding a second data source, the second data source being related to the first data source, receiving a first response via the first button to add the first data source and a second response via the second button to add the second data source, providing a view of a first data schema and a second data schema, wherein the first data schema includes at least one object from the first or the second data source, and wherein the second data schema is a canonical data model, mapping the at least one object of the first data schema to at least one object of the second data schema, and providing a single entity view of the at least one object of the second data schema.