Promotional Layout Rules for Real-Time Branded Image Targeting
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Solution Overview
Problem
Existing systems lack efficient methods for dynamically targeting and processing promotional content on client terminals to leverage user-generated images for brand promotion, especially in social media networks, without real-time adaptability and user engagement.
Innovation Solution
A system and method for distributing digital image branding functions based on distribution rules, using client terminals to apply image processing filters and sensors for real-time targeting and creation of branded images, allowing sharing and monetary rewards, integrated with social media platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If promotional content is distributed statically to all users, then coverage is maximized, but targeting precision and user engagement are reduced
Solution Approach 1:
The patent segments the user base into distinct groups based on distribution rules (e.g., geographic location, device type, social media activity). Different promotional content is then targeted to specific segments rather than uniformly distributed to all users, enabling precise targeting while maintaining overall coverage through multi-segment deployment.
Solution Approach 2:
The system dynamically updates user group assignments based on changing distribution rules and user behaviors. Users can be reallocated to different groups as their characteristics change, allowing the system to adapt targeting precision to current user states while maintaining broad coverage across the evolving user population.
2Productivity
If image processing functions are applied in real-time, then user engagement is enhanced, but processing time and computational resources are increased
Solution Approach 1:
Image processing functions are pre-configured and selected based on distribution rules before actual image capture. The system prepares processing pipelines in advance, so when users capture images, the appropriate functions are already ready to be applied, reducing real-time processing delays while maintaining high engagement through personalized processing.
Solution Approach 2:
Users select and apply image processing functions themselves based on their own preferences and the promotional content they engage with. This self-service approach allows users to control the processing time and computational resources used, optimizing engagement without forcing unnecessary processing on all users.
3Measurement precision
If multiple distribution rules are implemented, then targeting accuracy is improved, but system complexity increases
Solution Approach 1:
The system uses a universal distribution rule engine that can handle multiple targeting criteria (geographic, demographic, behavioral) through a single integrated framework. This multi-functional engine processes various rule types using the same underlying mechanisms, improving targeting accuracy across different dimensions while avoiding the complexity of separate systems for each rule type.
Solution Approach 2:
An intermediary layer is introduced between the promotional content and the user population, serving as a rule-based filter that translates complex targeting requirements into executable assignments. This intermediary manages the complexity of multiple distribution rules by providing a structured interface that simplifies rule creation, execution, and updates without exposing the underlying complexity to content creators or users.
Data Source
AI summary
Systems, methods and computer readable products are provided for enabling dynamic loading of one or more digital image branding functions associated with one or more distribution rules. A distribution rule is used to target a group of end users that are selected from a dataset mapping a plurality of end-users according to one or more distribution rules. Instructions are forwarded to present an indication the digital image branding function to each member of the end users group.


