Dynamic User Segmentation for Content Delivery Accuracy
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Solution Overview
Problem
Current content delivery systems face inefficiencies in targeting users due to overly simplistic or broad segmentation techniques based on limited user characteristics, leading to suboptimal message delivery and resource allocation.
Innovation Solution
The system compiles user characteristics through device information, interaction data, and public databases, infers additional characteristics using algorithms, and assigns users to targeted segments based on demographics, behaviors, and interests, allowing for prioritization and customization of content delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If content providers use broad segmentation techniques based on limited user characteristics, then the content delivery system is simpler to operate, but the accuracy and relevance of content delivery deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the user population into multiple segments based on multiple user characteristics (e.g., age, location, device type, behavior patterns). This allows the system to maintain operational simplicity while improving delivery accuracy by targeting specific segments with relevant content rather than treating all users uniformly.
Solution Approach 2:
The patent transitions from one-dimensional segmentation (e.g., only by age) to multi-dimensional segmentation by incorporating numerous user characteristics simultaneously. This dimensional expansion enables the system to achieve both ease of operation through automated multi-factor analysis and high delivery accuracy through comprehensive user profiling.
2Device complexity
If content providers target all residents of a city, then the content delivery process is simpler, but resource allocation efficiency deteriorates
Solution Approach 1:
The patent extracts and identifies specific user characteristics that are most relevant to the content being delivered. By extracting only the necessary characteristics (e.g., home ownership status for real estate content) rather than analyzing all possible user attributes, the system maintains process simplicity while improving resource allocation efficiency through targeted delivery to relevant segments.
Solution Approach 2:
The patent applies local quality by customizing content delivery strategies for different user segments based on their specific characteristics. Instead of using a uniform approach for all city residents, the system delivers tailored content to specific segments (e.g., homeowners receive housing content, renters receive rental content), thereby improving resource allocation efficiency without significantly increasing overall process complexity.
3Device complexity
If the system uses a limited number of user characteristics for segmentation, then the system complexity is reduced, but the relevance of targeted content to users deteriorates
Solution Approach 1:
The patent performs preliminary action by pre-processing and organizing user characteristics into structured categories (demographic, behavioral, contextual) before the content delivery process. This preliminary organization allows the system to handle multiple characteristics efficiently without increasing operational complexity, while simultaneously improving content relevance through comprehensive user profiling.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting which user characteristics are considered most important based on the content type and target audience. The system can weigh different characteristics differently (e.g., prioritizing location for local services, prioritizing age for product recommendations), allowing high relevance through multi-characteristic analysis while maintaining manageable system complexity through flexible parameter configuration.
Data Source
AI summary
Segments used to select content to be targeted to a user are recursively refined based on continuously derived user characteristics. Based on information gathered from new requests for targeted content and/or user interaction with previously delivered content the user is assigned to one or additional targeted segments. The targeted segments can be used to select content to be delivered to the user based on the user's assignment to the targeted segments. Accordingly, each user is grouped into one or more targeted segments and based on the user's inclusion in those segments, requests for targeted content can be served to the user.