Dynamic Web Page Personalization via User Group Segmentation
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Solution Overview
Problem
Static web pages with pre-defined links fail to provide personalized content based on user behavior and profile analysis, resulting in a generic browsing experience that does not cater to individual user interests.
Innovation Solution
A method and system that utilize behavioral and profile analysis to identify user groups and create customized content, dynamically modifying web pages by adding or removing links to provide a tailored browsing experience, leveraging a Social Browsing Enhancement engine to organize and display content relevant to each user group.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static web pages with pre-defined links are used, then the system is simple and easy to implement, but the content is not personalized and does not cater to individual user interests
Solution Approach 1:
The patent segments users into different groups based on behavioral and profile analysis, creating personalized content experiences for each segment. The system divides the user base into distinct categories (e.g., first group, second group) and provides tailored content navigation and links for each segment, thereby achieving content personalization without requiring complete system redesign.
Solution Approach 2:
The patent implements dynamic content delivery by modifying web page content based on real-time user group identification. Instead of static pre-defined links, the system dynamically generates and displays customized content, links, and navigation elements according to the user's identified group, enabling adaptability while maintaining system manageability through automated processes.
2Ease of operation
If customized content is created for each user group, then user engagement is improved, but the complexity of content creation and management increases
Solution Approach 1:
The patent enables the system to automatically perform content customization without manual intervention for each user. The system self-services by automatically identifying user groups, selecting appropriate content, and generating personalized web page versions. This automation reduces the operational burden on content managers while maintaining high user engagement through personalized experiences.
Solution Approach 2:
The patent utilizes behavioral analysis and profile data as feedback mechanisms to continuously improve content personalization. By analyzing user behavior patterns and profile information, the system receives feedback about user preferences and automatically adjusts content delivery accordingly, reducing the need for manual content management while enhancing user engagement through data-driven personalization.
3Loss of information
If behavioral and profile analysis is performed to identify user groups, then content relevance is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary user grouping and analysis before content delivery. By pre-segmenting users into groups based on their profiles and behavioral patterns, the system prepares personalized content structures in advance. This preliminary action reduces real-time processing requirements when a user accesses the system, as the heavy analytical work has already been completed during user onboarding or idle periods.
Solution Approach 2:
The patent changes the parameters of content delivery based on user group identification. Instead of performing full behavioral analysis for every content request, the system uses pre-established user group parameters to quickly determine content relevance. This parameter-based approach maintains high content relevance while significantly reducing processing time by leveraging pre-computed user attributes and group classifications.
Data Source
AI summary
Provided are techniques for providing customized content for social browsing flow. In response to accessing existing content, a group is identified from a plurality of groups created from behavioral and profile analysis. Additional content is created for the existing content to provide a customized browsing experience based on the identified group. The additional content is displayed with the existing content.