Database Sub-User Segmentation for Targeted Electronic Actions
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Solution Overview
Problem
Current systems lack efficient methods for categorizing sub-users of a database to optimize electronic message delivery, leading to sub-optimal response rates and increased user effort in creating distribution lists.
Innovation Solution
A computer-implemented method and apparatus that utilize a segmentation server to translate user input into a standardized segmentation system vernacular, parse user data, and logically combine criteria to identify and perform electronic actions on segmented sub-users, incorporating user feedback and behavior tracking for improved categorization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual categorization of sub-users is used, then user control over segmentation is maintained, but user effort and time consumption increase significantly
Solution Approach 1:
The system enables self-service automatic categorization by allowing the system to automatically segment sub-users based on their own data and behavior patterns without requiring manual user intervention. The segmentation server autonomously processes user data, applies segmentation criteria, and generates categorized distribution lists, eliminating the need for users to manually create and maintain these lists while preserving user control through configurable segmentation parameters.
2Productivity
If generic electronic messages are sent to all sub-users, then message distribution is simplified, but response rates decrease due to lack of personalization
Solution Approach 1:
The system applies local quality by tailoring electronic messages to specific sub-user segments based on their characteristics, behaviors, and preferences. Instead of sending identical generic messages to all sub-users, the segmentation server creates distinct message variations for different segmented groups, allowing each segment to receive personalized content that resonates with their specific needs and interests, thereby improving response rates while maintaining distribution efficiency.
3Measurement precision
If detailed user data is collected for precise segmentation, then categorization accuracy improves, but system complexity and data processing requirements increase
Solution Approach 1:
The system applies segmentation by dividing the complex task of user categorization into manageable components handled by specialized servers. The segmentation server specifically handles data processing and categorization logic, while other servers handle different functions. This modular segmentation allows the system to process detailed user data for precise categorization without overwhelming the entire system, as the complexity is distributed across dedicated components rather than concentrated in a single monolithic structure.
Data Source
AI summary
Apparatuses, methods, and systems for electronic categorization of sub-users of a database for receiving an electronic action are disclosed. One method includes receiving a segmentation description from a user of a user server, retrieving user data from the database, translating the segmentation description to a standardized segmentation system vernacular based on the segmentation description and the retrieved user data, identifying a set of individual criteria contained within the standardized segmentation description vernacular mapped to variable names, expressing the standardized segmentation system vernacular as a logical statement in terms of the variable names, parsing each individual criteria of the set of individual criteria against sub-user data of the database in parallel yielding a representation of each criteria, identifying sub-users of a segment by logically combine the representation of each criteria according to the logical statement, and performing an electronic action directed to the sub-users identified by the segment.