Product Webpage Segmentation for Scalable eCommerce Monitoring
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Solution Overview
Problem
There is a need for product manufacturers, distributors, and resellers to understand how their products and competitors' products are presented and sold on eCommerce platforms, as traditional methods of spot checks and inspections are not scalable for online sales.
Innovation Solution
A computing device generates a structural model of a product webpage, determines if it matches a stored model, extracts product information using machine learning, and updates the webpage based on the extracted information, sending it to a display device for analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional spot checks and random inspections are used to monitor product presentation on eCommerce platforms, then manual verification of pricing and placement can be performed, but the method is not scalable for online sales and requires significant human resources
Solution Approach 1:
The system enables automated self-monitoring of product webpages by having the computing device automatically retrieve, analyze, and extract information from eCommerce websites without requiring human inspectors to visit each page manually
Solution Approach 2:
The patent replaces manual mechanical inspection methods with automated computational processes, using processors to retrieve webpages, generate structural models, and extract product information algorithmically rather than through human spot checks
2Loss of information
If comprehensive product information is extracted from all product webpages, then complete competitive analysis can be achieved, but the processing time and computational resources increase significantly
Solution Approach 1:
The system extracts only the specific product information that is relevant to competitive analysis (such as pricing, placement, and promotion data) from the webpages, rather than processing and analyzing all content on each page, thereby reducing processing time while maintaining information completeness
Solution Approach 2:
The patent segments the webpage analysis process into distinct phases: retrieving the webpage, generating a structural model, identifying product information sections, and extracting specific data points. This segmentation allows for efficient processing by focusing computational resources on relevant sections only
3Extent of automation
If automated systems are implemented to analyze product webpages, then scalability is improved, but the initial system setup and implementation complexity increases
Solution Approach 1:
The system is designed as a universal platform that can monitor and analyze product webpages across multiple eCommerce websites and for various product types, reducing the need for separate automated systems for different monitoring needs and thereby managing implementation complexity
Data Source
AI summary
Methods, devices, and system for updating product webpages on an eCommerce website. A computing device may receive an address of a product webpage, retrieve the product webpage from the received address, and generate a structural model of the retrieved product webpage. The computing device may determine whether a similar product webpage from the received address has previously been segmented, use the generated structural model to segment the retrieved product webpage and generate a segmenting result in response to determining that a similar product webpage from the same address has not been segmented. The computing device may extract product information from the generated structural model based on the generated segmenting result and perform an update operation based on the extracted product information.