Market Segment Grouping via Bias-Mitigated Matrix Compression
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Solution Overview
Problem
Strategic decision-making is hindered by unorganized information, where large amounts of data do not necessarily lead to well-informed decisions due to lack of recognized relationships between information segments in market analysis.
Innovation Solution
A system and method utilizing a computing device with a bias mitigation module, matrix compression module, and matrix consistency score module to form and analyze a bias-mitigated and compressed square matrix, determining the best matrix consistency score for segment grouping within a market.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a large amount of information is collected for market analysis, then the quantity of data increases, but the ability to recognize relationships between information segments deteriorates due to lack of organization
Solution Approach 1:
The patent segments the market information into distinct segments and uses a square matrix structure where each row and column represents a segment. This segmentation allows relationships between segments to be systematically captured and analyzed, preventing loss of relationships while maintaining large quantities of information.
Solution Approach 2:
The patent transforms market information into a two-dimensional matrix structure, adding spatial organization to the data. This dimensional transformation enables visual and systematic recognition of relationships between information segments, solving the problem of unorganized large-scale data.
2Productivity
If second choice data is used directly in matrix analysis, then the data is utilized, but bias in the data deteriorates the accuracy of segment grouping
Solution Approach 1:
The patent applies preliminary bias mitigation processing to the second choice data before incorporating it into the matrix analysis. This preliminary action removes biases from the data, ensuring that subsequent segment grouping is based on accurate, unbiased information while still utilizing the full dataset.
3Quantity of substance
If the square matrix is not compressed, then all data is retained, but the complexity of analyzing the matrix increases
Solution Approach 1:
The patent extracts and removes redundant or less important information from the square matrix through compression, while retaining the essential data needed for accurate segment grouping. This extraction process reduces matrix complexity and makes analysis more manageable without sacrificing critical information.
Data Source
AI summary
A method for determining a grouping of segments within a market. The method includes forming a bias mitigated square matrix from a square matrix populated with second choice data, and forming a compressed matrix from the bias mitigated square matrix. Each different segment is initially associated with a row of the square matrix and a column of the square matrix. The method also includes determining a matrix consistency score for the compressed matrix, forming at least one additional compressed matrix from the bias mitigated square matrix, and determining matrix consistency scores for each additional compressed matrix. The method further includes determining which matrix consistency score is best.