Website Visitor Behavior Analysis via Route Clustering
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Solution Overview
Problem
Existing website tracking solutions fail to effectively analyze and differentiate between groups of visitors based on their behavior, as they primarily provide averaged statistics that obscure vital information, making it difficult for website owners to understand trends and optimize user experience.
Innovation Solution
A method and system that analyze website visitor recordings to determine the chronological sequence of user interactions, cluster similar routes based on common path flows, and provide insights into popular and non-popular routes, allowing website owners to make informed decisions on layout and design.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If averaged statistics are used to analyze user behavior, then data processing is simplified, but vital information is obscured
Solution Approach 1:
The patent segments user behavior data into distinct groups or clusters based on similarity in interaction patterns, device characteristics, and engagement metrics. Instead of treating all users as a single averaged group, the system divides the user base into segments that share common behaviors, allowing detailed analysis of each segment while maintaining manageable data processing through systematic classification.
2Measurement precision
If detailed user interaction data is collected, then user behavior understanding is improved, but data processing complexity increases
Solution Approach 1:
The patent merges multiple data collection dimensions (interaction patterns, device information, engagement metrics) into a unified user profile structure. By combining these diverse data types into integrated user records and then clustering similar profiles together, the system achieves comprehensive user behavior understanding while reducing processing complexity through consolidated data organization and pattern recognition.
Data Source
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AI summary
A system and method for analyzing website visitor behavior. The method includes analyzing website visitor recordings associated with a website visit of each of a plurality of website visitors; determining a route taken within the website by each of the plurality of website visitors based on the website visitor recordings, wherein the route includes a chronological sequence of user interactions with website elements; and dividing the plurality of routes into clusters based on common path flows.