Customer-Provider Matching via Categorical Profile Segmentation
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Solution Overview
Problem
Current methods for selecting a hair stylist or service provider fail to ensure compatibility between the customer's preferences and the provider's expertise, leading to potential mismatch in service quality and personality compatibility, resulting in unsatisfactory experiences for both parties.
Innovation Solution
A computer-implemented method that creates profiles for customers and service providers using categorical and discrete values, allowing for AI-driven matching based on preferences, location, and expertise, providing ranked recommendations that consider the importance of skills and personality traits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional methods are used to select a hair stylist, then the selection process is simple and quick, but the compatibility between customer preferences and provider expertise cannot be ensured
Solution Approach 1:
The patent transforms the service provider selection process by changing parameters from simple geographic proximity to a multi-dimensional compatibility score based on categorical values (personality traits, expertise, preferences) and discrete values (importance weights, distance). This parameter transformation enables reliable compatibility matching while managing system complexity through structured data organization.
Solution Approach 2:
The patent segments the compatibility assessment into distinct categorical values (personality traits, expertise areas, preferences) and discrete values (importance weights, distance metrics). This segmentation allows the complex matching problem to be broken down into manageable components that can be processed independently and combined to produce an overall compatibility score.
2Measurement precision
If comprehensive profiles with multiple categorical values are created for matching, then matching accuracy improves, but data collection time and processing complexity increase
Solution Approach 1:
The patent implements a flexible data collection approach where customers can provide partial profile information (excessive action) without being required to complete all categorical value assessments. The system processes available data to generate compatibility scores, allowing accurate matching even with incomplete profiles, thus reducing data collection time while maintaining matching precision.
Solution Approach 2:
The system performs preliminary processing of categorical values and importance weights during profile creation, organizing data in advance for efficient matching operations. This preliminary action reduces processing time during actual matching queries while maintaining high accuracy through pre-structured compatibility calculations.
3Ease of operation
If location-based filtering is applied to find nearby service providers, then service accessibility improves, but the pool of potential matches is reduced
Solution Approach 1:
The patent adds a distance dimension to the matching process by incorporating discrete values for maximum travel distance and calculating geographic proximity. This dimensional extension allows the system to filter providers by location (improving accessibility) while maintaining adaptability through configurable distance thresholds and weighted distance factors in the compatibility calculation.
Solution Approach 2:
The system dynamically adjusts the balance between location proximity and compatibility scoring through configurable importance weights. Customers can adjust the weight of distance factor versus other compatibility criteria, allowing the match pool size to adapt dynamically based on individual preferences for accessibility versus comprehensive matching.
Data Source
AI summary
A computer-implemented method of matching a customer with a service provider, the method comprising: creating, by a computing device, a profile of a customer having a plurality of categorical values descriptive of or liked by the customer; creating, by the computing device, a profile of a service provider having a plurality of categorical values descriptive of or liked by the service provider; creating, by the computing device, a request by the customer to recommend a service provider, wherein the request includes one or more requested categorical and discrete values; and providing, by the computing device, ranked recommendations of service providers to the customer based on a comparison of the categorical values in the profiles of the customer and the service provider and the requested categorical and discrete values by the customer. A service provider can be a hair stylist.