ETL-Based Communication Channel Selection for Resource Efficiency
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Solution Overview
Problem
Existing communication systems inefficiently utilize computing and network resources by transmitting large volumes of communications without considering optimal communication types, channels, or content relevance, leading to reduced engagement from recipients.
Innovation Solution
An ETL process is employed to analyze raw data for interactions and identity information, determining optimal communication types, channels, and content, transforming the data into communication data suitable for specific channels, and transmitting it efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If large volumes of communications are transmitted without analysis, then communication volume increases, but resource utilization efficiency deteriorates
Solution Approach 1:
The system performs preliminary analysis of recipient data, communication history, and interaction patterns before transmitting communications. The ETL process pre-processes raw data to identify optimal communication types and channels for each recipient, so that when communications are generated, the selection is already optimized based on pre-computed insights from events data and identity data.
Solution Approach 2:
The system extracts only the necessary communication parameters (communication type, channel, content) from the large volume of raw events data and identity data through the ETL process. Instead of processing or transmitting all raw data, only the essential transformed data needed for communication decisions is extracted and used, reducing resource consumption while maintaining communication effectiveness.
2Quantity of substance
If communication data is transmitted without transformation, then data size remains large, but processing efficiency deteriorates
Solution Approach 1:
The ETL transform phase extracts only the essential communication parameters (communication type, channel, content) from the comprehensive raw data, discarding unnecessary information. This extraction reduces data size while retaining only the critical elements needed for communication transmission and processing.
Solution Approach 2:
The system transforms raw data parameters into communication-specific parameters through the ETL process. The transform phase converts general events data and identity data into structured communication data with specific formats and parameters suitable for transmission, changing the data structure from raw unstructured format to optimized communication format.
3Ease of operation
If generic communication methods are used, then implementation simplicity is maintained, but recipient engagement deteriorates
Solution Approach 1:
The system applies different communication types and channels to different recipients based on their specific characteristics found in the events data and identity data. Instead of using a uniform communication approach for all recipients, the ETL process enables customized communication strategies tailored to each recipient's preferences, behavior patterns, and interaction history, thereby improving engagement while maintaining systematic operation.
Data Source
AI summary
In some implementations, a device may obtain raw data including events data indicating a series of events involving interactions between an entity and an individual, and including identity data for the individual. The device may process the raw data to determine, based on the events data and the identity data, a communication type, a communication channel, and a content for a communication to the individual. The device may generate, in accordance with processing the raw data, communication data that includes the content and has a format used for the communication channel. The device may transmit the communication data for an endpoint of the communication channel to cause transmission of the communication, including the content and using the communication type, via the communication channel.