Anonymized Customer Data Analysis for Privacy Preservation
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Solution Overview
Problem
Customers are uncomfortable providing personally identifiable information for personalized experiences, leading to reduced interaction with websites, as they feel their privacy is compromised, resulting in websites becoming less effective and valuable.
Innovation Solution
A method that stores customer data in a protected database, restricting access to approved privacy-preserving queries, which generate aggregated data without personally identifiable information, and creates anonymous personas by injecting noise into customer data, ensuring individual privacy is preserved.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If personalized customer data is collected and analyzed, then website relevance and effectiveness are improved, but customer privacy is compromised
Solution Approach 1:
The patent extracts personally identifiable information (PII) from customer data through a filtering mechanism. The system separates PII from behavioral and preference data, retaining only anonymized information for analysis. This extraction principle resolves the contradiction by removing the harmful element (PII) while preserving the useful elements (behavioral patterns) needed for website personalization.
Solution Approach 2:
The patent introduces an intermediary component - a privacy filter or anonymization layer - that sits between raw customer data and analysis systems. This intermediary processes data to remove PII while maintaining the utility of aggregated behavioral information. The mediator enables both privacy protection and effective data utilization simultaneously.
2Productivity
If aggregated customer data is analyzed, then marketing effectiveness is improved, but individual customer privacy may be compromised
Solution Approach 1:
The patent segments customer information into distinct categories: personally identifiable information (PII) and anonymized behavioral data. By segmenting the data types and applying different handling rules to each segment, the system enables aggregated analysis for marketing while protecting individual privacy. The segmentation principle allows simultaneous achievement of marketing effectiveness and privacy preservation.
3Reliability
If customer data is stored for analysis, then data integrity is maintained, but security risks increase
Solution Approach 1:
The patent extracts and removes PII from stored customer data, retaining only anonymized information. By taking out the most sensitive elements (identifiable information) while preserving essential analytical data, the system maintains data integrity for analysis purposes while significantly reducing security risks associated with storing comprehensive personal information.
Data Source
AI summary
A method of preserving individual information privacy for each of a plurality of customers while providing aggregated information about the plurality of customers includes storing static customer data and dynamic customer data of the plurality of customers in a protected database. The method includes restricting shared access to the static customer data and the dynamic customer data to a set of approved privacy-preserving queries. The privacy preserving queries include a privacy-preserving aggregation query that uses one or more parameters to indicate a characteristic of interest for which aggregation of the static customer data and the dynamic customer data is requested. The privacy-preserving aggregation query may be configured to retrieve aggregated customer data related to the characteristic of interest. The aggregated customer data may be returned in response to the privacy-preserving aggregation query not including any personally identifiable information of any particular one of the plurality of customers.