Anonymous Customer Data Exchange via Third-Party Linking
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Solution Overview
Problem
Current methods for exchanging customer information between business entities require the transfer of large volumes of data, including personally identifiable information (PII), which can be inefficient and violate customer privacy, making it challenging to share insights while maintaining privacy constraints.
Innovation Solution
A method and system that process customer information by identifying common customers between entities without exchanging PII, using a third entity to link customer attributes while eliminating PII, allowing for anonymous record creation and sharing, thus enabling efficient and privacy-compliant information exchange.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If customer information including PII is transferred between business entities, then information exchange completeness is improved, but customer privacy protection deteriorates
Solution Approach 1:
The patent extracts and removes personally identifiable information (PII) from customer records before exchange, retaining only anonymized attributes. This allows complete customer behavior and preference data to be shared while eliminating privacy-violating identifiers, directly resolving the contradiction between information completeness and privacy protection.
Solution Approach 2:
The patent introduces a third-party intermediary service that receives customer data from participating entities, performs anonymization processing, and distributes processed data back to entities. This intermediary architecture enables full information exchange while the intermediary controls and enforces privacy protection by removing PII before data leaves any entity's control.
2Measurement precision
If large volumes of customer data are transferred, then analysis accuracy is improved, but data transfer efficiency deteriorates
Solution Approach 1:
The patent segments customer data into essential anonymized attributes needed for analysis and separates out unnecessary PII and redundant information. This segmentation transfers only the critical data elements required for accurate customer profiling and behavior analysis, maintaining analysis accuracy while dramatically reducing transfer volume and improving efficiency.
3Measurement precision
If PII is shared between entities, then customer identification accuracy is improved, but privacy compliance deteriorates
Solution Approach 1:
The patent creates anonymized copies of customer records that preserve all behavioral, preference, and transactional attributes necessary for identification and analysis, while replacing actual PII with anonymized identifiers. These copies enable accurate customer matching and profiling without containing any regulatable personally identifiable information, thus maintaining identification accuracy while ensuring privacy compliance.
Data Source
AI summary
A third party facilitates exchange of customer data between first and second entities while maintaining customer privacy. Personally identifiable information (PII) and first entity customer attributes of a first set of customers are received from a first entity. PII for a second set of customers is received from a second entity. First and second set common customers are identified using the PII of the first and the second set of customers. Subsequently, a list of third set of customers is sent to the second entity. The list of third set of customers includes the common customers and a plurality of other customers from the second set of customers. Second entity customer attributes are received for each customer in the list of third set of customers. Further, the first entity customer attributes of the common customers and the second entity customer attributes of the common customers are linked.