Portable Micro-segment Object for Precise Consumer Targeting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods struggle to accurately classify and segment large user populations into micro-segments for targeted content delivery, as consumers increasingly filter content and marketing messages, leading to underutilization of collected data due to lack of industry expertise and technological limitations.
Innovation Solution
A computer program product and system that generates a portable micro-segment object based on expression trees, allowing for precise definition and targeting of micro-segments using demographic and behavioral attributes, enabling marketers to create highly targeted content and personalized marketing campaigns across various devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional segmentation methods are used to classify large user populations, then the system can process data with current technology, but the segmentation precision and accuracy are insufficient for micro-segmentation
Solution Approach 1:
The patent segments the user classification process into distinct components: expression graph generation from campaign attributes, portable micro-segment object creation, and pattern matching against user data. This segmentation allows each component to be optimized independently, achieving high segmentation precision without overwhelming system complexity.
Solution Approach 2:
The portable micro-segment object serves as an intermediary between the campaign definition and the user database. It encapsulates the segment criteria in a self-contained format that can be efficiently processed and matched against user populations, bridging the gap between complex segmentation requirements and practical processing capabilities.
2Measurement precision
If more consumer data is collected to improve segmentation accuracy, then the potential for better micro-segmentation increases, but the data becomes under-utilized due to lack of expertise and technology
Solution Approach 1:
The system performs preliminary actions by pre-defining portable micro-segment objects that encapsulate segmentation logic before actual campaign execution. This allows consumer data to be pre-processed and organized into meaningful segments, ensuring that when data is collected, it can be immediately and effectively utilized without requiring complex real-time analysis.
Solution Approach 2:
The portable micro-segment objects are self-contained and self-descriptive, containing all necessary information about segment criteria and attributes. This self-service capability allows the system to automatically process and utilize consumer data without requiring external expertise for interpretation, eliminating data under-utilization.
3Adaptability or versatility
If marketers create highly specific micro-segments for targeted content delivery, then content relevance improves, but the complexity of defining and managing segments increases
Solution Approach 1:
The portable micro-segment object format is universal and can be used across multiple campaigns and platforms. A single micro-segment definition can be reused and adapted for different content delivery scenarios, providing high adaptability and versatility while reducing the complexity of defining segments from scratch for each campaign.
4Measurement precision
If recommendation systems use complex algorithms like collaborative filtering to improve recommendations, then recommendation quality may improve, but accurate segmentation of very large user populations remains challenging
Solution Approach 1:
The system segments the large user population into pre-defined portable micro-segments before applying recommendation algorithms. This segmentation reduces the complexity of processing very large populations by organizing users into manageable, well-defined groups, thereby improving both recommendation accuracy and processing efficiency.
Data Source
AI summary
A selection of one or more segment attributes from an offer provider campaign is received at a graphical user interface. The one or more segment attributes define one or more segments that correspond to one or more offers in the offer provider campaign. Further, an expression graph based on the one or more segment attributes is generated. In addition, a portable micro-segment object is generated based on the expression tree such that the portable micro-segment object lacks dependence on the offer provider campaign.