Market Analysis System for Feature Opportunity Scoring
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Solution Overview
Problem
Existing market analysis methods fail to accurately determine the importance of features to customers and the opportunity for new solutions, leading manufacturers to guess which features will achieve market success, as they do not consider customer satisfaction with current products and the desirability of potential features.
Innovation Solution
A method and system that collect survey data on desired outcomes and potential features, processing it to calculate opportunity scores and rank features based on importance, satisfaction, and desirability, correlating potential features with desired outcomes to identify the most valuable solutions for product development.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing market analysis methods are used to determine feature importance, then the analysis process is simple, but the accuracy of determining customer needs and unmet opportunities is poor
Solution Approach 1:
The market analysis system segments customer feedback into distinct categories: desired outcomes, current satisfaction levels, and potential feature desirability. This segmentation allows precise measurement of customer needs while maintaining manageable system complexity through structured data collection and analysis modules.
Solution Approach 2:
The system adds multiple dimensions to traditional market analysis by incorporating not only what customers want (desired outcomes) but also how satisfied they are with current solutions and which specific features they prefer. This multi-dimensional approach enhances measurement precision without overwhelming complexity.
2Productivity
If manufacturers rely on guessing which features will achieve market success, then the development process is flexible, but productivity and market success are reduced
Solution Approach 1:
The system performs preliminary market analysis by collecting and analyzing customer feedback on desired outcomes, current satisfaction levels, and potential feature desirability before product development begins. This preliminary action identifies unmet opportunities and prioritizes features, significantly improving productivity while preventing information loss.
Solution Approach 2:
The system establishes continuous feedback loops where customer insights are systematically collected, analyzed, and used to guide product development decisions. This feedback mechanism ensures that customer information is captured and utilized effectively, transforming guessing into informed decision-making and boosting productivity.
3Measurement precision
If only customer feedback on desired outcomes is collected, then the survey process is simple, but the ability to identify specific feature opportunities is limited
Solution Approach 1:
The survey system is designed with multi-functionality, simultaneously collecting data on desired outcomes, current satisfaction levels, and potential feature desirability from a single customer feedback source. This universal approach enables precise feature opportunity identification without proportionally increasing time requirements, as one survey serves multiple analytical purposes.
Data Source
AI summary
A method for performing a market analysis may include collecting survey data, which may include evaluation data for desired outcomes, the desired outcomes consisting of attributes of one or more products or services. The desired outcome evaluation data may include importance and satisfaction data. Further, the survey data may include evaluation data for potential features. The potential features evaluation data may include desirability data indicative of the affinity survey participants have for potential features. The method may further include processing the collected survey data using a computer processor. The processing may include calculating, based on the importance and satisfaction data, opportunity scores for the individual desired outcomes. The processing may also include correlating potential features with desired outcomes. In addition, the processing may include ranking the potential features based on the collected desirability data and the calculated opportunity score.