Dynamic Media Object Customization for Targeted Advertising
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional advertising techniques fail to customize media objects based on individual user preferences within a demographic group, leading to inefficiencies as user behavior changes over time, and do not allow for real-time adjustments to optimize ad performance.
Innovation Solution
A system that generates and delivers custom media objects by creating user and group profiles based on interaction data, using a media object customizer that assembles and updates media elements in real-time based on user behavior, allowing for dynamic adjustments to media object templates and elements to match changing user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional advertising techniques are used to deliver standardized media objects to demographic groups, then implementation is simple and cost-effective, but the advertising effectiveness decreases because user preferences within demographic groups are not customized and user behavior changes over time
Solution Approach 1:
The patent segments demographic groups into more granular user profiles by analyzing individual user interaction data with media objects. Instead of treating all users in a demographic group uniformly, the system divides them into sub-segments based on their specific preferences and behaviors, enabling customized advertising delivery that improves effectiveness without requiring complete system redesign.
Solution Approach 2:
The patent implements dynamic adaptation of media object delivery by continuously monitoring user interaction data and adjusting advertising strategies in real-time. The system evolves from static demographic-based targeting to dynamic user-profile-based targeting that automatically adapts as user preferences change, maintaining advertising effectiveness without manual intervention.
2Reliability
If media object templates are customized for individual user preferences, then advertising effectiveness improves, but the complexity of creating and managing customized media objects increases
Solution Approach 1:
The patent creates a universal media object template system that can serve multiple user profiles simultaneously. A single template design can be dynamically adapted to different user preferences through parameter customization rather than creating entirely separate templates for each user. This multi-functional approach maintains ease of creation while enabling personalized delivery.
Solution Approach 2:
The patent uses template copying and adaptation mechanisms where a base media object template is created once and then copied/modified for different user segments. Rather than manually creating unique media objects for each user preference, the system efficiently replicates and customizes templates based on user profile data, significantly reducing the effort required for customization.
3Adaptability or versatility
If real-time updates to media object templates are implemented based on user interaction data, then the system adapts to changing user preferences, but the processing complexity and data requirements increase
Solution Approach 1:
The patent implements preliminary segmentation of user data and pre-processing of interaction data before it reaches the main processing system. By preparing and organizing user preference data in advance, the system reduces the computational complexity of real-time template updates. Data is pre-categorized and structured so that when user interactions occur, the system can quickly match patterns without complex real-time analysis.
Solution Approach 2:
The patent establishes a feedback loop where user interaction data is continuously collected, analyzed, and used to refine user profiles and media object delivery strategies. This systematic feedback mechanism automates the adaptation process, reducing the need for complex manual processing. The feedback loop efficiently processes data by focusing only on relevant interaction metrics that directly impact template customization decisions.
Data Source
AI summary
Methods and apparatus to deliver targeted advertising are disclosed. An example apparatus includes processor circuitry to: obtain user behavior information corresponding to interaction with a first media object from a user, the first media object including a first customizable media object element and a second customizable media object element independent of the first customizable media object element; analyze a performance of the first media object based on the user behavior information; and update at least one of a user profile of the user or a group profile corresponding to the user using a machine learning model to adjust ratings of the first customizable media object element and the second customizable media object element based on a comparison of the performance of the first media object to a second custom object including at least one of the first customizable media object element or the second customizable media object element.