Probabilistic Message Routing Using Engagement Metrics
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Solution Overview
Problem
The overwhelming number of messages in communication networks leads to alert fatigue, where recipients ignore or fail to respond to messages due to irrelevant or high-volume communications, including critical messages that may be overlooked, especially when recipients are indisposed.
Innovation Solution
A system that intelligently routes messages based on engagement and contextual information, using a server with notice logic, tracking logic, and score logic to determine the most likely and capable recipients, ensuring relevant messages are prioritized and delivered effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If messages are broadcast to all individuals in the network, then message delivery coverage is improved, but alert fatigue increases and message relevance decreases
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and updating engagement information about network individuals before messages are sent. This includes tracking response patterns, availability status, and interaction history in advance, allowing the routing system to predict who is most likely to respond to incoming messages and route accordingly, preventing alert fatigue before it occurs
Solution Approach 2:
The system implements feedback mechanisms by continuously collecting engagement information from individual responses to messages, calls, and other communications. This feedback loop allows the system to learn from past interactions and improve message routing decisions over time, dynamically adjusting which individuals receive messages based on their demonstrated engagement patterns
2Speed
If messages are sent without considering recipient availability, then message sending speed is improved, but message effectiveness decreases
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and updating engagement information about network individuals before messages are sent. This includes tracking response patterns, availability status, and interaction history in advance, allowing the routing system to predict who is most likely to respond to incoming messages and route accordingly, preventing alert fatigue before it occurs
Solution Approach 2:
The system applies dynamics by making message routing flexible and adaptive rather than static. The routing decisions dynamically adjust based on real-time engagement information and availability status of individuals. The system can change routing behavior on-the-fly as engagement patterns evolve, allowing fast message sending while maintaining effectiveness through adaptive recipient selection
3Measurement precision
If engagement tracking is implemented for all network individuals, then message routing accuracy is improved, but system complexity increases
Solution Approach 1:
The system applies universality by using a single server with integrated notice logic, tracking logic, and score logic that handles multiple functions: receiving messages, monitoring engagement information, calculating response scores, and routing messages. This multi-functional approach consolidates complexity into one system rather than requiring separate components for each function, reducing overall system complexity while maintaining high routing accuracy
Solution Approach 2:
The system applies parameter changes by using a response score parameter that quantifies individual likelihood to respond based on engagement information. This numerical parameter simplifies complex engagement patterns into a single measurable value that can be easily compared and used for routing decisions, transforming complex qualitative engagement data into simple quantitative routing criteria
Data Source
AI summary
Systems, methods, and other embodiments associated with routing messages in a network are described. In one embodiment, a method includes acquiring engagement information about each of a plurality of individuals that are members of a network associated with a user. The engagement information is acquired as a message is received from the user. The method may also include analyzing the network and the engagement information using a set of predefined metrics to determine a probability that each of at least a subset of the plurality of individuals will respond to the message. The method may also include routing the message to at least one individual in the subset as a function of the probability that each of at least a subset of the plurality of individuals will respond.