Service Orchestration Layer for Personalized Action Reminders
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Solution Overview
Problem
Current telecommunications systems lack mechanisms to utilize waiting time productively for users on hold, failing to provide personalized actions or insights based on omnichannel data, and do not proactively notify users of pending actions during waiting periods.
Innovation Solution
A method and system utilizing a service orchestration layer in a 5G telecommunications network, with omnichannel data collector platforms and dedicated logical channels, to proactively suggest personalized actions to users on hold through voice or text messages, leveraging user equipment and virtual network functions for dynamic information collection and notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If users are placed on hold during communication, then the current communication can be maintained, but the user's waiting time is wasted and frustration increases
Solution Approach 1:
The system automatically provides personalized action reminders and information to users during hold periods without requiring manual intervention. The service orchestration layer autonomously collects omnichannel data, determines relevant actions, and delivers notifications through dedicated logical channels, allowing users to passively benefit from the service during waiting periods.
Solution Approach 2:
The system proactively identifies and prepares personalized action reminders before the user completes their hold period. By analyzing omnichannel data in advance and determining relevant pending actions, the system ensures that useful information is ready and delivered at the optimal moment, transforming wasted waiting time into productive engagement.
2Productivity
If personalized action reminders are implemented, then user engagement during waiting time improves, but system complexity increases
Solution Approach 1:
The service orchestration layer acts as an intermediary between existing omnichannel data sources and users. Rather than requiring direct integration with multiple data sources, the orchestration layer collects data from various channels, processes it to identify pending actions, and delivers personalized reminders through dedicated logical channels, simplifying the overall system architecture while enabling sophisticated functionality.
Solution Approach 2:
The system leverages existing omnichannel data infrastructure and communication channels to deliver personalized action reminders. By reusing established data collection mechanisms and communication pathways, the system achieves multi-functional capability without proportionally increasing complexity, as the same infrastructure supports both traditional communications and the new reminder service.
3Loss of information
If omnichannel data collection is implemented, then personalized insights can be provided, but data processing requirements increase
Solution Approach 1:
The service orchestration layer applies local quality by selectively processing only the specific portions of omnichannel data that are relevant to identifying pending user actions. Rather than uniformly processing all collected data, the system tailors its data analysis to the specific context of each user and communication scenario, reducing overall processing requirements while maintaining information completeness where needed.
Data Source
AI summary
Provided are a method, system, and computer program product in which a service orchestration layer is configured in a telecommunications network. Personalized pending user actions are transmitted to a user equipment, in response to a hold being performed over a first communications channel to the user equipment.