Win Share Content Prioritization for User Engagement
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Solution Overview
Problem
Content providers face challenges in identifying and optimizing content presentation to engage users, as conventional methods fail to effectively determine which content to display and where, leading to user disengagement if relevant content is not presented.
Innovation Solution
A system and method using a win share approach to assign values to content items based on user interactions, prioritizing and optimizing content presentation by tracking user interactions and distributing win shares to identify engaging content for display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional keyword and link structure management is used to ensure good traffic from search engines, then search engine traffic is improved, but user engagement with relevant content deteriorates
Solution Approach 1:
The patent implements feedback mechanisms by tracking user interactions with content items and using this data to dynamically adjust content presentation. The system monitors user behavior patterns and feeds this information back into the content selection algorithm, allowing continuous optimization of both search engine traffic and user engagement based on actual user responses.
Solution Approach 2:
The system changes parameters by dynamically adjusting content presentation based on user interaction data. Instead of static keyword optimization, the system modifies content selection, placement, and frequency based on real-time user behavior metrics, enabling adaptation to both search engine requirements and user engagement needs.
2Ease of operation
If content is presented without optimization based on user interactions, then content presentation simplicity is maintained, but user engagement deteriorates
Solution Approach 1:
The content optimization system operates autonomously by automatically tracking user interactions, analyzing behavior patterns, and adjusting content presentation without manual intervention. The system serves itself by using its own collected data to optimize its performance, maintaining simplicity while improving engagement through automated adaptive algorithms.
3Reliability
If win share tracking and content optimization is implemented, then user engagement is improved, but system complexity increases
Solution Approach 1:
The patent segments the content optimization process into distinct functional modules: user interaction tracking, win share calculation, content selection, and presentation optimization. Each module handles a specific aspect of the optimization process, making the overall complex system manageable through functional decomposition and independent development of each component.
4Measurement precision
If frequent presentation of high win share content is implemented, then content relevance is improved, but content diversity deteriorates
Solution Approach 1:
The system applies local quality by presenting different content frequencies to different user segments based on their specific interaction patterns and preferences. Instead of uniform content presentation, the system tailors content frequency and selection to individual user characteristics, maintaining relevance for each user while preserving overall system diversity through personalized content delivery.
Data Source
AI summary
Disclosed herein is a statistical approach, a win share approach, used to assign a win share value to content items. User interaction with content items is tracked, and a win share value is assigned to content items in response to a “winning” action performed by a user. Win shares associated with content items are used to identify content items that are to be presented, and can further be used to identify an optimal presentation, e.g., layout, presentation frequency, etc., of content items that is to be presented.