Website Configuration Optimization via User Interaction Analysis
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Solution Overview
Problem
Current methods for optimizing website performance through user interaction analysis are complex, time-consuming, and resource-intensive, requiring custom programming for each webpage modification, which limits the speed and efficiency of deployment and increases costs.
Innovation Solution
A system that collects user behavioral data via plugins, analyzes it to determine successful and failed interactions, and automatically modifies website configurations based on this data, using machine learning to optimize user experience and improve conversion rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If custom programming is used to modify and test each web page, then website optimization can be achieved, but human resource requirements and deployment time are significantly inflated
Solution Approach 1:
The patent introduces an intermediary system consisting of a browser extension and a server that mediates between the user and the website. The browser extension captures user interactions and sends them to the server, which then generates and applies modifications. This intermediary architecture eliminates the need for custom programming on each web page while maintaining optimization effectiveness.
Solution Approach 2:
The system enables self-service optimization by automatically capturing user interactions through the browser extension and generating modifications based on analyzed behavior patterns. The website optimizes itself without requiring manual custom programming intervention for each page, reducing human resource requirements while maintaining optimization reliability.
2Manufacturing precision
If custom programming is implemented for each webpage modification, then precise control over webpage changes can be achieved, but deployment speed is significantly reduced
Solution Approach 1:
Instead of implementing custom programming for each webpage, the system creates a copy or template of the desired modification and applies it universally across multiple pages. The server generates modification code based on analyzed user behavior and deploys it across the website, achieving precise control without the need for page-by-page custom programming, thereby significantly increasing deployment speed.
Solution Approach 2:
The patent creates a universal modification system that can be applied across multiple web pages with a single deployment. The server generates versatile modification code that adapts to different pages based on user interaction patterns, eliminating the need for separate custom programming for each page while maintaining precise control over modifications and enabling rapid deployment.
3Reliability
If manual analysis of user behavior is performed to optimize website, then optimization decisions can be made, but time and resource constraints result in high costs and extended deployment timeframes
Solution Approach 1:
The system implements continuous feedback loops where the browser extension captures user interactions in real-time, sends data to the server for analysis, and automatically generates modifications based on the analyzed patterns. This automated feedback mechanism enables rapid optimization decisions without manual analysis, reducing deployment timeframes while maintaining high-quality optimization decisions through data-driven insights.
Solution Approach 2:
The patent replaces the mechanical system of manual user behavior analysis with an automated computational system. The server uses algorithms to automatically analyze interaction data captured by the browser extension, substituting human manual analysis with machine-based processing that is both faster and more scalable, thereby reducing deployment timeframes while maintaining or improving optimization quality.
Data Source
AI summary
Optimized modification of a website based on user interactions with the website may include collecting data associated with the interactions and determining a success or failure of each interaction. A configuration of the website may be modified based on the success or failure of at least one user interaction. The modified website may be presented to a specified number of test users and, for each test user or test user session, a success or failure of each of the test user's interactions with the modified website may be determined. The modified configuration may be deemed successful based on a threshold number of the test user interactions having been determined to be successful. Elements of the website (e.g., a link or a search input box) may then be modified based on the modified configuration having been determined to be successful.