Information Provision Through Visual Customer-Factor Analysis
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Solution Overview
Problem
Conventional methods fail to accurately determine the factors contributing to customers' intentions such as subscription, revisit, repurchase, or recommendation, and lack a display mechanism to easily grasp the extent of these contributions.
Innovation Solution
An information providing device and method that conducts multivariate analysis on customer evaluation data to calculate and visually display the contribution degrees of evaluation factors for contract, revisit, and recommendation intentions, using a network-capable terminal to output analysis results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional questionnaire aggregation methods are used, then data collection is simple, but the ability to determine contribution degrees of evaluation factors to customer intentions is insufficient
Solution Approach 1:
The patent introduces multivariate analysis as an intermediary computational method between raw questionnaire data and contribution degree results. The analysis system uses regression analysis and factor analysis as mediators to transform evaluation data into quantified contribution degrees, resolving the contradiction by adding analytical complexity only where needed for precise measurement.
Solution Approach 2:
The system changes parameters by transforming qualitative evaluation data into quantitative contribution degree parameters through statistical analysis. By converting evaluation scores into weighted contribution values, the system achieves precise measurement of factor contributions while managing complexity through parameter transformation rather than structural complexity.
2Measurement precision
If detailed multivariate analysis is conducted, then contribution degrees are calculated accurately, but ease of grasping results deteriorates
Solution Approach 1:
The patent applies color coding to visualize contribution degrees, where different colors represent different levels of contribution. This allows accurate multivariate analysis results to be displayed in an easily graspable visual format, resolving the contradiction by translating complex numerical data into intuitive color-based visual representations.
Solution Approach 2:
The system transforms one-dimensional numerical contribution degrees into two-dimensional visual displays with spatial positioning and sizing. By mapping contribution degrees to visual dimensions (position, size, color intensity), the system maintains calculation accuracy while dramatically improving ease of grasping results through visual perception.
3Ease of operation
If simple display methods are used, then ease of grasping results is high, but the ability to display contribution degrees with high accuracy deteriorates
Solution Approach 1:
The patent displays contribution degrees using visual dimensions (position, size, color) that directly encode quantitative information. This allows simple visual display methods to maintain high accuracy by mapping numerical contribution degrees to visual properties, where position indicates factor identity, size indicates contribution magnitude, and color indicates contribution level.
4Reliability
If hierarchical multivariate analysis is conducted, then factor analysis comprehensiveness is improved, but analysis processing time increases
Solution Approach 1:
The patent segments the analysis into hierarchical levels (first-level factors, second-level sub-factors, third-level detailed factors). This segmentation allows comprehensive factor analysis to be conducted systematically, where each level builds on the previous one, improving comprehensiveness while managing processing time through structured progressive analysis rather than simultaneous comprehensive analysis.
Data Source
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AI summary
Provided is an information providing device, a method, and a program capable of visually grasping a contribution degree of an evaluation factor with respect to a contract intention or a recommendation intention for others of a customer. An information providing device includes: a survey data acquisition means configured to acquire evaluation data including evaluation values for evaluation items for a target product or service, the evaluation data including evaluation values for a plurality of evaluation items related to a contract intention or a recommendation intention for others; a multivariate analysis means configured to calculate contribution degrees of a plurality of explanatory variables with respect to an objective variable by conducting a multivariate analysis based on the evaluation data using an evaluation value for the contract intention or the recommendation intention for others as the objective variable, and evaluation values for a plurality of evaluation items in the evaluation data as the explanatory variables; and an analysis result output means configured to display an analysis result from the multivariate analysis means on an information terminal capable of communicating via a network.