Website Clickstream Diagnosis for Automated User Experience Monitoring
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Solution Overview
Problem
Current systems for identifying and remedying website problems are inefficient, requiring significant human labor and time, and often fail to accurately capture user experience issues due to incomplete surveys and slow data analysis.
Innovation Solution
A computer-implemented method and system that automatically extracts click data from websites, processes it into behavioral features, and uses an analytics engine trained on this data to diagnose potential user experience problems, reducing human intervention and accelerating the identification of issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual survey methods are used to identify website problems, then user feedback can be collected, but the process requires significant human labor and time investment
Solution Approach 1:
The patent replaces manual survey collection and analysis with an automated system that uses machine learning algorithms to process clickstream data. The system automatically extracts behavioral patterns from user interactions with the website, eliminating the need for manual survey administration and analysis while providing continuous, real-time problem detection.
Solution Approach 2:
The system enables self-service problem detection by automatically monitoring user behavior patterns and generating diagnostic reports without human intervention. The machine learning model continuously learns from user interactions and autonomously identifies usability problems, allowing the system to serve itself rather than requiring manual analysis.
2Measurement precision
If survey data collection is used, then user problems can be identified, but the data analysis process is very slow
Solution Approach 1:
The patent replaces slow manual survey analysis with automated machine learning processing of clickstream data. The system processes large volumes of user interaction data in real-time using computational algorithms, dramatically increasing the speed of problem detection while maintaining diagnostic accuracy through pattern recognition and anomaly detection capabilities.
Solution Approach 2:
The system performs preliminary processing of clickstream data continuously as users interact with the website, pre-processing and analyzing behavioral patterns before problems manifest. This proactive approach allows the system to detect issues as they occur rather than relying on retrospective survey data, significantly improving detection speed.
3Productivity
If automated clickstream monitoring is implemented, then problem detection speed increases, but system complexity increases
Solution Approach 1:
The patent extracts and isolates specific behavioral patterns and metrics from the complex clickstream data using feature extraction techniques. By focusing on key indicators of user experience problems rather than processing all raw data, the system reduces computational complexity while maintaining high detection speed and accuracy.
Solution Approach 2:
The system transforms raw clickstream data into meaningful diagnostic parameters through data processing and feature engineering. By converting complex user interaction patterns into simplified metrics and categories, the system reduces the complexity of analysis while maintaining the ability to detect subtle usability issues efficiently.
Data Source
AI summary
The following relates generally to diagnosing problems with websites. In some embodiments, a webpage interaction processor receives a list of potential user experience problems. The webpage interaction processor then extracts click data from the website, and processes the extracted click data into grams. Subsequently, an analytics engine is trained based on the processed click data. The trained analytics engine may then diagnose the problem of the website with a potential user experience problem from the received list of potential user experience problems. In some embodiments, the process is entirely automated.