Customer Intent Analysis Interface for Visual Factor Contribution
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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 means for high-accuracy contribution degree grasping.
Innovation Solution
An information providing device and program 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.
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 coefficients and standardized beta values as mediators to quantify the relationship between evaluation factors and customer intentions, transforming qualitative survey responses into precise contribution degree measurements.
Solution Approach 2:
The patent replaces manual data analysis methods with automated computational algorithms. The system automatically calculates correlation coefficients, performs multivariate regression analysis, and generates contribution degree rankings without manual intervention, substituting mechanical computational processes for human analysis while maintaining measurement precision.
2Measurement precision
If detailed multivariate analysis is conducted to achieve high accuracy, then contribution degree measurement precision improves, but ease of operation deteriorates
Solution Approach 1:
The analysis system performs self-service by automatically executing multivariate analysis algorithms without requiring user expertise in statistical methods. The system autonomously processes questionnaire data, calculates contribution degrees, and presents results in an easily interpretable format, enabling users to obtain precise measurements without needing to understand the underlying complex analysis procedures.
Solution Approach 2:
The patent segments the analysis process into distinct functional modules: data collection, multivariate analysis execution, contribution degree calculation, and result presentation. This segmentation allows each module to be optimized independently, maintaining high measurement precision in the analysis phase while ensuring ease of operation in the user interface phase.
3Adaptability or versatility
If multiple levels of evaluation items are analyzed, then comprehensiveness of analysis improves, but device complexity increases
Solution Approach 1:
The patent adds a hierarchical dimension to the evaluation framework by organizing evaluation items into multiple levels (e.g., first-level items, second-level items, and third-level items). This dimensional organization allows the system to analyze relationships at different granularities simultaneously, improving comprehensiveness while managing complexity through structured hierarchy rather than flat complexity.
Data Source
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.