Weighted Survey Scoring System for Accuracy
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Solution Overview
Problem
Existing survey management systems fail to accurately calculate customer satisfaction scores, as they do not account for the varying importance of questions and the number of answers provided by customers, leading to inconsistent and potentially misleading results.
Innovation Solution
A system that uses survey metadata to assign weights to questions and calculates weighted answers based on customer responses, allowing for the determination of satisfaction scores and categories, stored in a layered data model for efficient reporting and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional independent averaging is used to calculate satisfaction scores, then calculation simplicity is maintained, but measurement precision deteriorates because it does not account for varying question importance and response completeness
Solution Approach 1:
The patent introduces question weights as a new parameter to transform the satisfaction score calculation. Instead of simple averaging, each question's contribution is adjusted by its weight, allowing more important questions to have greater impact on the final score. This parameter change resolves the contradiction by improving measurement precision through weighted calculations while maintaining systematic processing.
Solution Approach 2:
The patent segments the satisfaction score calculation into distinct components: individual question weights, individual satisfaction scores per question, and an overall weighted satisfaction score. This segmentation allows for more precise measurement of each component's contribution while maintaining overall calculation coherence, resolving the contradiction between precision and complexity.
2Loss of information
If all questions are treated equally in survey analysis, then data processing uniformity is maintained, but information quality deteriorates because it does not distinguish between more and less important questions
Solution Approach 1:
The patent applies local quality by assigning different weights to different questions based on their importance. Instead of uniform treatment, each question can have its own weight parameter, allowing the system to preserve more relevant information from high-weight questions while still processing all questions systematically. This resolves the contradiction by reducing information loss through differential weighting.
3Reliability
If simple averaging is used for satisfaction scoring, then calculation speed is maintained, but result reliability deteriorates due to inconsistent treatment of partial and complete surveys
Solution Approach 1:
The patent applies preliminary action by pre-defining question weights and satisfaction categories before survey processing. This allows the system to consistently apply the same weighting scheme and categorization rules to all surveys, ensuring reliability. The pre-established framework enables automated processing that maintains both reliability and efficiency, resolving the contradiction between consistent treatment and processing speed.
Data Source
AI summary
The embodiments may provide a system for managing survey data including a survey metadata handler configured to receive survey metadata for a survey type, and a survey result handler configured to receive one or more completed or partially completed surveys providing one or more answers to questions corresponding to the survey type, a calculating unit configured to calculate one or more weighted answers based on the question weights and the one or more answers, and a satisfaction score for each completed or partially completed survey based on the one or more weighted answers, a category determining unit configured to determine a satisfaction category for the survey type based on the satisfaction scores and satisfaction category information mapping satisfaction categories to satisfaction scores for the survey type, and a database configured to store the survey metadata, the survey results, and the satisfaction category information, as a layered data model.