Tag Suggestion System for E-Commerce Product Discovery
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Solution Overview
Problem
E-commerce websites face challenges in improving tag concordance and coverage, making it difficult for customers to find products, especially for novice users who struggle with navigating vast product offerings.
Innovation Solution
Implementing a system that suggests tags for users to associate with items, using a combination of metadata and relationships between items, with a ranking engine to prioritize suggestions based on source weight and existing associations, presented on item review and detail pages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If customers manually search for products among hundreds or thousands of offerings, then product discovery is possible, but navigation difficulty and time consumption increase significantly
Solution Approach 1:
The system automatically generates tag suggestions and applies them to products without requiring manual intervention from customers or administrators. The tag suggestion engine autonomously analyzes product data, identifies relevant tags from the taxonomy, and presents ranked suggestions, enabling the system to serve itself in the tag assignment process.
Solution Approach 2:
The patent replaces manual mechanical tagging processes with an automated computational system. Instead of customers or administrators manually searching and assigning tags, the system uses automated tag suggestion engines that analyze product data and generate tag recommendations, substituting human effort with algorithmic processing.
2Loss of information
If companies increase manual tagging of products, then tag coverage improves, but workload and operational complexity increase
Solution Approach 1:
The system automatically generates tag suggestions and applies them to products without requiring manual intervention from customers or administrators. The tag suggestion engine autonomously analyzes product data, identifies relevant tags from the taxonomy, and presents ranked suggestions, enabling the system to serve itself in the tag assignment process.
Solution Approach 2:
The system performs preliminary tag suggestion generation before final tag assignment. By pre-computing and ranking tag suggestions based on product data analysis, the system prepares tag recommendations in advance, reducing the complexity of the actual tagging process and improving tag coverage efficiently.
3Loss of information
If companies increase manual tagging efforts, then tag concordance improves, but operational effort and time investment increase
Solution Approach 1:
The system performs preliminary tag suggestion generation before final tag assignment. By pre-computing and ranking tag suggestions based on product data analysis, the system prepares tag recommendations in advance, reducing the complexity of the actual tagging process and improving tag coverage efficiently.
Solution Approach 2:
The patent replaces manual mechanical tagging processes with an automated computational system. Instead of customers or administrators manually searching and assigning tags, the system uses automated tag suggestion engines that analyze product data and generate tag recommendations, substituting human effort with algorithmic processing.
4Adaptability or versatility
If e-commerce websites offer hundreds or thousands of products, then product variety increases, but navigation and product location difficulty worsen
Solution Approach 1:
The system segments the large product catalog into organized categories using a tag taxonomy. By dividing thousands of products into hierarchical tag groups and subgroups, the system makes navigation manageable despite the large variety of products available.
Solution Approach 2:
The system automatically generates tag suggestions and applies them to products without requiring manual intervention from customers or administrators. The tag suggestion engine autonomously analyzes product data, identifies relevant tags from the taxonomy, and presents ranked suggestions, enabling the system to serve itself in the tag assignment process.
Data Source
AI summary
Tag suggestions enable a hosting entity such as a website to determine one or more tags to suggest to a user for association with a particular item within an electronic catalog. After this determination, the hosting entity may suggest the determined tags to the user. To determine these tags, the hosting entity may employ techniques to determine items related to the particular item. The hosting entity then suggests some or all of the tags associated with the related items. Additionally or alternatively, the hosting entity may determine certain metadata associated with the particular item. The entity then may suggest this metadata, or some related phrase or tag, to the user for association with the particular item. However the tag suggestions are determined, the hosting entity may rank the tag suggestions to determine which tags to present to the user or to determine an order in which to present the tags.