Anonymized Online Data Aggregation for Merchant Strategy
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Solution Overview
Problem
Merchants face challenges in acquiring reliable demographic and transaction data beyond their own business while protecting customer privacy, as existing methods rely on unreliable survey data and lack correlation between demographic and transaction data, and customers are hesitant to share data due to privacy concerns.
Innovation Solution
A system and method that processes online data by separating personally identifiable information (PII) from non-personally identifiable information (non-PII), associating non-PII data with unique user identifiers, and sending it to a reporting server for analysis, ensuring customer privacy is maintained by not linking online data to PII, allowing for demographic and transaction data reporting without revealing individual identities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If merchants use survey data to gather demographic information, then they can obtain some customer insights, but the data becomes unreliable due to self-selection bias
Solution Approach 1:
The patent introduces a third-party data aggregation service as an intermediary that collects anonymous demographic and transaction data from multiple sources. This mediator processes and aggregates data without direct merchant-customer interaction, eliminating self-selection bias while providing reliable aggregated insights.
Solution Approach 2:
The system creates anonymized copies of customer data that strip personally identifiable information while preserving demographic and behavioral patterns. These copies can be analyzed for research purposes without affecting the original data sources or introducing selection bias.
2Loss of information
If merchants collect detailed customer data to improve targeting, then they can develop better online strategies, but customer privacy is compromised
Solution Approach 1:
The patent extracts and removes personally identifiable information from customer data before aggregation and analysis. Only anonymized demographic and behavioral data are retained and shared with merchants, enabling targeted strategies while protecting individual privacy through systematic extraction of identifying elements.
Solution Approach 2:
The system transforms customer data by changing its parameters - converting identifiable personal data into anonymized aggregate statistics. This parameter transformation maintains the utility of data for marketing analysis while eliminating privacy risks associated with individual identification.
3Loss of information
If merchants track customer behavior across multiple sites, then they can correlate demographic and transaction data, but specialized software is required increasing complexity
Solution Approach 1:
The patent creates a universal data aggregation platform that serves multiple merchants and data sources through a single system. This multi-functional platform handles data collection, anonymization, aggregation, and distribution, eliminating the need for each merchant to implement specialized tracking software while enabling cross-site behavioral correlation.
4Loss of information
If surveys are used to gather customer feedback, then merchants can understand customer preferences, but participation is low due to privacy concerns
Solution Approach 1:
The system uses anonymized copies of customer data for analysis instead of requiring direct customer participation in surveys. Researchers and merchants can access aggregated behavioral patterns and demographic information without customers needing to complete surveys, dramatically increasing data availability while maintaining privacy.
Data Source
AI summary
Customer online data is collected via script on customer computers and is communicated to a server hosted by an organization, such as a card issuer. The customer online data communicated to the server is non-personally identifiable information (non-PII). In turn, the server aggregates the non-PII customer online data from the set of participating merchants. The server associates the received non-PII customer online data with non-PII demographic data. Other non-PII transaction data, such as previous transactions processed at a card issuer, also can be associated with the non-PII customer online data and non-PII demographic data. These associations are, in turn, used to create reports and to provide services to help merchants or other requesting organizations develop online strategies to drive click thru and conversion rates.