Market Identification System De-identifies Customer Data
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Solution Overview
Problem
Businesses face challenges in accurately identifying and sizing untapped markets in a timely manner, as existing methods lack precision and often fail to account for privacy and security concerns when analyzing customer data.
Innovation Solution
A market identification system (MIS) that allows users to create queries based on customer attributes, de-identifies and aggregates data, and displays market information, ensuring privacy and security compliance by removing personal information and providing weighted values for data robustness, accessible through a secure computer environment via the internet or network platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If customer data is analyzed to identify market opportunities, then market identification accuracy is improved, but customer privacy and security are compromised
Solution Approach 1:
The system extracts and removes personally identifiable information (PII) from customer data before analysis. This extraction process separates useful market intelligence from sensitive personal information, allowing accurate market identification while protecting customer privacy through systematic removal of harmful data elements.
Solution Approach 2:
The system introduces an intermediary processing layer that de-identifies data before market analysis. This intermediary process acts as a mediator between raw customer data and market intelligence generation, transforming identifiable data into anonymized aggregates that preserve analytical value while eliminating privacy risks.
2Measurement precision
If comprehensive customer attributes are collected for market analysis, then market sizing accuracy is improved, but data complexity and processing requirements increase
Solution Approach 1:
The system segments comprehensive customer attributes into distinct categorical groups (geographic, demographic, financial, behavioral). This segmentation organizes complex multi-dimensional data into manageable segments that can be independently processed and analyzed, reducing overall system complexity while maintaining complete market analysis capability.
Solution Approach 2:
The system transforms raw customer attribute data into standardized parameter formats with defined weightings and aggregation rules. By changing the parameter representation from raw heterogeneous data to structured weighted parameters, the system simplifies processing complexity while preserving the comprehensive nature of market analysis.
3Object-affected harmful factors
If de-identified and aggregated data is provided, then customer privacy is protected, but data utility for market analysis is reduced
Solution Approach 1:
The system applies different levels of identification removal to different data elements based on their sensitivity and analytical value. Rather than uniformly de-identifying all data, the system selectively anonymizes only the portions necessary for privacy protection while preserving local qualities of data that maintain analytical utility for market analysis.
Solution Approach 2:
The system creates composite market intelligence products that combine multiple de-identified data sources and attributes into aggregated market profiles. These composite representations maintain analytical utility by synthesizing information across multiple dimensions while the aggregation process inherently protects individual privacy through loss of granular identifiability.
Data Source
AI summary
Embodiments of the present invention provide a method and system for providing a marketing identification system by enabling creating an entry for customer data in a way that allows searching of customer attributes, querying the customer data, retrieving data in response to the query, de-identifying and aggregating the retrieved data, and displaying the de-identified and aggregated data in a way that identifies the available market as defined by the query. The invention can be implemented via a stand-alone computing system or such a system interconnected with other platforms or data stores by a network, such as a corporate intranet, a local area network, or the internet.