Dynamic Consumer Product Attribute Generation
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Solution Overview
Problem
Online shopping experiences are hindered by consumer expectations not being fully captured in product descriptions, leading to inaccurate and inefficient product identification in e-commerce platforms.
Innovation Solution
A method that receives a search query, extracts user expectations, identifies synonyms, and generates product attributes based on consumer-generated content, adding metadata and updating the product catalog to improve search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If product descriptions are generated by manufacturers or retailers, then product information is available in the product catalog, but consumer expectations are not fully captured leading to inaccurate search results
Solution Approach 1:
The patent introduces consumer-generated content (reviews, ratings, forum posts) as an intermediary source of information between consumers and the product catalog. This intermediary captures consumer expectations and translates them into searchable attributes, bridging the gap between manufacturer-provided product descriptions and consumer search needs.
Solution Approach 2:
The system implements feedback loops where consumer search queries and generated content are analyzed to extract new attributes, which are then added back to the product catalog. This continuous feedback process ensures the catalog evolves to better capture consumer expectations and improves search accuracy over time.
2Productivity
If traditional product description fields are used, then the product catalog structure is simple, but consumer expectations are not captured leading to inefficient product identification
Solution Approach 1:
The patent implements dynamic attribute generation where the product catalog structure adapts based on consumer behavior and generated content. Attributes are dynamically created and added to the catalog based on analyzed consumer queries and feedback, making the catalog structure flexible and responsive rather than static.
Solution Approach 2:
The system segments consumer-generated content into distinct attributes and metadata categories (opinion data, occurrence frequency, sentiment analysis). This segmentation allows complex consumer feedback to be organized into manageable, searchable components that can be efficiently integrated into the product catalog structure.
3Reliability
If manufacturer-generated product descriptions are used, then information consistency is maintained, but consumer-defined attributes are missing reducing search relevance
Solution Approach 1:
The patent merges manufacturer-generated product descriptions with consumer-generated content and attributes. Both sources are integrated into a unified product catalog structure, combining the consistency and reliability of manufacturer information with the adaptability and consumer-relevance of user-generated attributes.
Solution Approach 2:
The system creates a multi-functional product catalog that serves both manufacturer information dissemination and consumer search needs. The catalog structure is designed to accommodate both traditional product specifications and consumer-defined attributes, making it universally applicable to diverse search scenarios.
Data Source
AI summary
Methods and systems of defining product attributes may involve receiving a search query and extracting a user expectation from the search query. In addition, an attribute may be defined for a product based on the user expectation. In one example, consumer generated content such as forum content, review content, blog content and social networking content, is used to define the attribute.