Behavior Change Model Content Delivery System
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Solution Overview
Problem
Publishers face challenges in delivering targeted content due to outdated and inflexible legacy content databases, which hinder their ability to adapt to changing digital environments and provide personalized content based on user behavior, leading to reduced content value and user experience.
Innovation Solution
A system that integrates component content and behavior change models into existing content databases, allowing for the creation of highly targeted and personalized content by segmenting articles into components, using profiling and targeting engines to deliver tailored content across multiple channels based on user behavior and profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If publishers use legacy content databases with established structures, then content organization is maintained, but adaptability to changing digital environments and user behavior modeling is reduced
Solution Approach 1:
The patent segments content databases into modular components that can be independently updated and managed. This allows publishers to adapt specific portions of their content infrastructure to new digital environments without restructuring entire legacy databases, thereby improving adaptability while managing complexity.
Solution Approach 2:
The patent introduces dynamic content structures that can adapt to changing user behaviors and digital environments. By implementing flexible data models and adaptive content delivery mechanisms, the system evolves with digital trends without requiring complete database restructuring.
2Loss of information
If publishers deliver general content without detailed targeting, then content delivery is simple, but content value and user experience are reduced
Solution Approach 1:
The patent implements preliminary user profiling and behavior analysis to pre-segment audiences before content delivery. By preparing user profiles and behavior models in advance, the system can deliver highly targeted content without complex real-time processing, thereby increasing content value while managing system complexity.
Solution Approach 2:
The patent introduces behavior change models as intermediary layers between raw user data and content delivery. These models translate complex user behaviors into actionable targeting parameters, enabling detailed content personalization without requiring the content delivery system to directly process all raw user data.
3Reliability
If publishers update and adapt legacy content databases, then content relevance improves, but cost and effort increase significantly
Solution Approach 1:
The patent divides content databases into updateable segments, allowing publishers to refresh and adapt specific content portions independently. This modular approach reduces the overall effort and cost of content updates by eliminating the need to restructure entire legacy databases.
Solution Approach 2:
The patent implements content templates and reusable content components that can be copied and adapted across multiple platforms and formats. This reduces the effort required to update and adapt content by allowing publishers to create master templates that automatically generate consistent content across different digital channels.
Data Source
AI summary
A system for delivering targeted content based on user behavior stores multiple behavior change models, generates a user record containing information regarding a user, selects a behavior change model from the multiple stored models based on the information in the user record, and delivers to the user targeted content based on the selected behavior change model, the targeted content being adapted to influence the user to change behavior according to the selected behavior change model.