Wine Label Affinity System Visual Preference Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current wine recommendation systems rely heavily on expert ratings and consumer taste profiles, which are subjective and do not account for the significant influence of visual attributes of wine packaging on purchasing decisions, leading to inefficiencies in consumer selection and sales.
Innovation Solution
A system and method that rank and recommend wines based on visual attributes of the packaging, correlating descriptor intensity values with consumer preference profiles to enhance sales by optimizing label presentation and consumer preference matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wine recommendation systems rely on expert ratings and consumer taste profiles, then subjective wine selection guidance is provided, but visual attributes of wine packaging are not accounted for leading to inefficiencies in consumer selection
Solution Approach 1:
The patent changes the parameters used for wine recommendation from subjective expert ratings and taste profiles to objective visual attributes of wine packaging. The system analyzes visual characteristics such as label colors, imagery, and design elements to generate recommendations, thereby improving selection accuracy while maintaining ease of operation for consumers.
2Adaptability or versatility
If a large number of wine labels are displayed to consumers, then more product variety is available, but consumers lack the bandwidth to effectively search and index wines
Solution Approach 1:
The system performs preliminary action by pre-analyzing and indexing wine visual attributes before consumer interaction. The automated system processes and categorizes wine packaging visual characteristics in advance, creating a structured database that enables rapid retrieval and recommendation, thus providing wide variety while minimizing consumer search time.
Solution Approach 2:
The patent replaces the mechanical manual search and indexing process with an automated computer-based visual analysis system. The system uses image processing and pattern recognition algorithms to automatically extract and analyze visual attributes from wine labels, substituting human cognitive effort with automated computational processes.
3Ease of operation
If wine clubs and third parties make selection decisions for consumers, then purchasing process is simplified, but consumers lose the ability to discover and select wines independently
Solution Approach 1:
The system enables self-service by allowing consumers to independently explore and select wines based on their own visual preferences. The automated visual attribute analysis provides recommendation capabilities that empower consumers to make their own selections without relying on third-party curators, while still maintaining ease of operation through automated filtering and ranking.
Data Source
AI summary
The present invention relates generally to a system and method for sorting, ranking, and presenting and/or recommending multiple products for purchase having different labels in a coherent and structured way, and more specifically a system and method to generate marketing communications which display labels and/or wine labels based on an affinity system and ranking to help consumer and buyer select and purchase wine using either a digital interface or even in the course of normal retail buying process to select appropriate product.