Anonymized User Profile Data Matching via Centralized Intermediary
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Solution Overview
Problem
Companies are reluctant to share user profile data due to privacy and competitive concerns, hindering the delivery of customized content such as advertisements, as existing methods require disclosure of sensitive customer information.
Innovation Solution
A system of data appliances and a central server facilitate the anonymization and secure sharing of user profile data by converting it into anonymous identifiers, allowing entities to match and share de-personalized data for improved ad targeting without revealing sensitive information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If user profile data is shared to improve ad customization, then advertising effectiveness is improved, but privacy and security concerns worsen
Solution Approach 1:
The patent introduces a trusted third-party intermediary that performs centralized anonymization and matching of user profile data. This intermediary receives data from multiple entities, applies consistent anonymization algorithms to generate pseudonymous identifiers, and facilitates matching without exposing raw personal information. The intermediary acts as a mediator that enables data sharing benefits while protecting privacy through controlled access and anonymization.
Solution Approach 2:
The patent creates anonymized copies of user profile data that retain useful identifying characteristics for advertising purposes while removing sensitive personal information. Instead of sharing original data, the system generates pseudonymous identifier copies that can be exchanged and matched across entities. These copies serve as substitutes that maintain functionality while eliminating privacy risks associated with sharing raw data.
2Measurement precision
If raw customer data is disclosed to improve targeting precision, then ad delivery quality is improved, but competitive advantage is lost
Solution Approach 1:
The patent extracts and removes sensitive identifying information from user profile data while retaining the anonymized identifiers necessary for matching and targeting. Entities can share and match data using these extracted anonymized keys without exposing their complete customer profiles or proprietary data structures. This extraction process preserves targeting precision while protecting competitive advantages.
Solution Approach 2:
The patent transforms user profile data by changing its parameter representation from identifiable personal information to anonymized pseudonymous identifiers. This parameter transformation maintains the data's utility for matching and targeting purposes while fundamentally altering its form to remove sensitive characteristics. Entities can achieve precise targeting through parameter-matched identifiers without revealing their original data parameters.
3Reliability
If anonymization methods differ between entities, then data security is improved, but data matching capability deteriorates
Solution Approach 1:
The patent establishes a universal anonymization standard and consistent algorithm that all participating entities adopt. This universal approach ensures that the same anonymization method is applied across all entities, enabling reliable matching of anonymized identifiers while maintaining security through the robustness of the standardized algorithm. The universality principle allows the system to function across multiple entities with different data characteristics.
Solution Approach 2:
The patent segments the anonymization process into distinct functional components: data intake, standardized anonymization transformation, identifier generation, and matching. By segmenting the process and applying consistent transformation rules at each stage, the system maintains both security through standardized processing and matching capability through consistent identifier generation across all entities.
Data Source
AI summary
Embodiments facilitate confidential and secure sharing of anonymous user profile data to improve the delivery of customized content. Embodiments of the invention provide a data appliance to an entity such as a business to convert profile data about the business's customers into anonymous identifiers. A similar data appliance is provided to a content provider in one embodiment to generate identifiers for its user profile data. Because the anonymous identifiers are generated with the same anonymization method, identical identifiers are likely generated from profile data of the same users. Therefore, the identifiers can be used to anonymously match the customers of the business to the users of the content provider. Therefore, data can be shared to improve customized content such as advertisements that the business wishes to place with the content provider without requiring the business to disclose customer data in an unencrypted form, and any non-matched data can remain confidential.