Recipient Selection via Pre-Analyzed User Behavior
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Solution Overview
Problem
Current information sharing methods are inefficient and time-consuming, requiring users to manually select recipients and tools, often leading to delayed or misplaced information due to the complexity of identifying interested parties and choosing appropriate communication channels.
Innovation Solution
A system that analyzes pre-analyzed user behavior to automatically determine the most relevant recipients and preferred communication tools, allowing users to quickly and accurately share information by selecting the content to be shared, which is then dispatched through the identified tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual recipient selection and tool choice is used, then users can precisely control information distribution, but the process becomes time-consuming and complex
Solution Approach 1:
The system pre-analyzes user behavior patterns from historical messaging data before information sharing is needed. This creates ready-to-use recipient recommendations and tool suggestions that can be instantly deployed when a user wants to share information, eliminating the time-consuming manual selection process while maintaining precision through behavior-based accuracy
Solution Approach 2:
The system automatically performs recipient identification and tool selection based on analyzed user behavior patterns, making the system self-serve the information sharing task. The user simply initiates the share action, and the system autonomously determines optimal recipients and communication channels based on pre-analyzed data, reducing manual effort to minimal interaction
2Reliability
If comprehensive contact repositories are searched for dispatch addresses, then complete recipient coverage is achieved, but the complexity of information retrieval increases
Solution Approach 1:
The system segments the contact repository into behavior-based groups rather than searching through all contacts uniformly. By dividing contacts into segments based on pre-analyzed user interaction patterns, the system achieves complete recipient coverage within relevant segments without the complexity of searching entire contact databases
Solution Approach 2:
The system introduces behavior analysis data as an intermediary layer between the user and contact repositories. This intermediary layer pre-processes and filters contact information based on user behavior patterns, serving as a mediator that simplifies the retrieval process while ensuring reliable recipient identification through behavior-based filtering
3Adaptability or versatility
If multiple communication tools are available for information dispatch, then communication versatility is improved, but the difficulty of tool selection increases
Solution Approach 1:
The system changes the selection parameter from user subjective preference to objective behavior-based recommendations. By analyzing historical messaging patterns, the system determines which communication tools the user actually prefers for different recipients, transforming tool selection from a complex subjective decision into an automated objective process based on usage data
Data Source
AI summary
Targeted information to be shared according to a “pre-analyzed user behavior” of a set of potential candidates is analyzed. The pre-analyzed user behavior is determined from a set of previously conveyed messages from a sender to one of the potential candidates. A list representing a determined subset of the potential candidates and related preference tools/applications is presented to the sender via a user interface. Tools/applications are determined for sending said targeted information content. An action message is sent to the tools/applications of selected candidates, which results in each of the subset of potential candidates receiving the targeted information.