Message Scoring Based on Sender Influence and Engagement
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Solution Overview
Problem
Users of online platforms face challenges in processing and responding to a large number of incoming messages from various senders, particularly those who are influential or highly engaged, as they lack the resources to adequately address all communications, which can impact goodwill, relationship nurturing, and marketing efforts.
Innovation Solution
A system that scores and ranks messages based on the influence and engagement levels of the message sender, allowing for prioritization and filtering of messages, using components such as a message component to identify message data, an influence component to determine influence data, an engagement component to determine engagement data, and a scoring component to combine these metrics into a total score for message sorting and filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users process and respond to all incoming messages, then relationship management and marketing efforts are improved, but resource consumption and time requirements increase beyond available capacity
Solution Approach 1:
The system changes the parameter of message prioritization by calculating and applying composite scores based on sender attributes (influence, engagement, recency) to transform the message processing system from treating all messages equally to ranking messages by importance, enabling resource allocation based on priority
Solution Approach 2:
The system segments the incoming message stream into priority tiers based on calculated scores, separating high-priority messages from low-priority ones, allowing users to focus resources on the most important communications while automatically handling or deprioritizing less critical messages
2Productivity
If users prioritize responses to influential senders, then marketing effectiveness and relationship nurturing are improved, but time for processing other messages is reduced
Solution Approach 1:
The system performs preliminary action by pre-calculating sender scores and priorities before the user needs to process messages. Influence, engagement, and recency metrics are computed in advance, and messages are pre-ranked, so when the user reviews messages, the prioritization is already established, saving decision time
3Measurement precision
If the system calculates comprehensive sender scores using multiple attributes, then message prioritization accuracy is improved, but system complexity and computational requirements increase
Solution Approach 1:
The system manages complexity by standardizing multiple sender attributes (influence, engagement, recency) into a unified scoring framework. Each attribute is normalized and weighted to contribute to a single composite score, transforming complex multi-dimensional evaluation into a manageable single-metric prioritization system
Solution Approach 2:
The scoring system serves multiple functions simultaneously: it evaluates sender influence, measures engagement history, tracks recency of interaction, and generates prioritization rankings all through a single integrated scoring mechanism, reducing the need for separate evaluation systems for each metric
Data Source
AI summary
A message sent by a message sender to a message receiver can be, e.g., upon arrival at a message system server, ranked or scored based on attributes of the message sender such as influence and engagement. Influence can relate to a determination of how influential the message sender is. Engagement can relate to a determination of how interested the message sender is in content published or syndicated by the message receiver. The message score can reflect a combination of an influence score and an engagement score. Scored messages can be sorted or filtered according to a desired element and a presentation of messages stored by the message system can be updated (e.g., ordered and scored) according to the desired element.