Dynamic Scoring for Personalized Media Promotions
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Solution Overview
Problem
Traditional digital media merchandising promotions are inefficient in targeting users' interests, leading to ineffective sales generation, as they are broadly advertised regardless of user interest.
Innovation Solution
A method and system for managing media library merchandising promotions that determine personalized promotions by assigning universal and personal scores based on user interactions and media library content correlations, allowing for dynamic updating and grouping to present relevant content to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional algorithmic presentation of promotions is used, then promotions are broadly advertised to all users, but the effectiveness in generating sales decreases due to lack of user interest alignment
Solution Approach 1:
The patent segments the generic promotion audience into personalized user groups based on their media library content and interaction history. By dividing the broad user base into segments with similar preferences (determined through correlation analysis of media items), the system can target promotions more effectively to each segment's interests rather than using a one-size-fits-all approach.
Solution Approach 2:
The patent applies local quality by customizing promotion content and selection for each individual user based on their specific media library composition. Instead of uniform promotion quality for all users, the system adjusts promotion relevance locally for each user by analyzing their unique media collection and interaction patterns, thereby improving sales effectiveness for each user segment.
2Adaptability or versatility
If personalized promotions are implemented based on user interactions and media library correlations, then user interest targeting improves, but system complexity increases due to scoring and matching mechanisms
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing correlation data between media items in users' libraries and promotional content before actual promotion delivery. The system pre-establishes scoring mechanisms and matching criteria based on historical interaction data, so that when promotions are needed, the personalized selection can be quickly generated without complex real-time computations.
Solution Approach 2:
The patent introduces an intermediary layer of correlation scoring and matching algorithms that bridge the gap between raw user data and promotion delivery. This intermediary system processes and structures user interaction history and media library information into standardized correlation scores, simplifying the overall system architecture by creating a dedicated processing layer that handles the complexity of personalization.
3Productivity
If dynamic updating of universal and personal scores is performed, then promotion relevance to user interests increases, but computational resources and processing time increase
Solution Approach 1:
The patent implements periodic action by updating user scores and promotion recommendations at scheduled intervals or triggered by specific events (such as completing a certain number of interactions or reaching a time threshold). Instead of continuously recalculating scores in real-time, the system performs periodic updates based on accumulated interaction data, reducing computational overhead while maintaining relevant promotion personalization.
Data Source
AI summary
A method and/or system for managing media library merchandising promotions may include determining one or more current promotions from a plurality of promotions. A universal score may be assigned to each of the one or more current promotions, wherein the universal score is updated dynamically based on interactions with the one or more current promotions by one or more users. A personal score for each of the one or more current promotions may be assigned for a particular user, wherein the personal score is updated dynamically based on interactions with the one or more current promotions by the particular user. Personalized digital content promotions may be determined for the particular user from the current promotions based on the personal score and/or the universal score. The personalized promotions may be presented to the particular user.