Cloud Virtual Queue Service with Targeted User Interactions
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Solution Overview
Problem
Current virtual queuing systems fail to efficiently manage multiple queues, address punctuality concerns, and utilize modern data analytics to optimize queue organization and user interactions.
Innovation Solution
A cloud-based queue service that manages multiple queues by receiving user check-in information, identifying user groups, and providing targeted interactions and recommendations based on entity and user data, using a combination of communication methods to facilitate queue management and user engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional physical queues or simple electronic pagers are used, then users can be notified of their position, but users are limited in physical space by the range of the pager and must remain within visual or auditory range of the queue system
Solution Approach 1:
The patent replaces physical queue systems and range-limited electronic pagers with a cloud-based virtual queuing system that uses internet-connected mobile devices. This substitution eliminates physical space constraints by transitioning from mechanical/local notification systems to a network-based information delivery system, allowing users to access queue information from any location with internet connectivity.
Solution Approach 2:
The system transitions from two-dimensional physical queue space to a multi-dimensional virtual space where queue positions are managed and communicated through a cloud platform. Users can join, leave, and be notified of queue positions through digital channels (SMS, email, push notifications) that operate independently of physical proximity to the queue location.
2Productivity
If simple virtual queuing systems are used, then users can join queues remotely, but the systems fail to efficiently manage multiple queues, address punctuality concerns, and utilize modern data analytics
Solution Approach 1:
The system implements comprehensive feedback mechanisms by collecting and analyzing user behavior data, queue performance metrics, and punctuality information. This data feeds into machine learning models that continuously optimize queue management strategies, predict wait times, and improve user experience. The feedback loop enables the system to learn from past performance and adapt to changing conditions.
Solution Approach 2:
The system dynamically adjusts queue management parameters such as wait time thresholds, notification schedules, and group sizing based on real-time data analysis and predictive modeling. By changing these parameters adaptively rather than using fixed rules, the system optimizes efficiency across multiple queues while utilizing the rich data available from user interactions and queue performance.
3Adaptability or versatility
If no group management features are implemented, then individual queue management is simple, but groups of users cannot be efficiently managed across multiple queues
Solution Approach 1:
The cloud-based queue management system provides universal functionality that handles both individual and group queue management through a unified platform. The same system infrastructure manages single users and groups of any size across multiple queues, providing adaptable service without requiring separate systems for different user types.
Solution Approach 2:
The system segments queue management into independent, manageable components that can handle individual users and groups separately. Each user or group is treated as an independent queue entity with its own position tracking, allowing the system to manage complex group scenarios while maintaining simple individual queue operations. This segmentation enables scalable group management without overwhelming system complexity.
Data Source
AI summary
A system and method for managing virtual queues with user-level targeted interactions. A cloud-based queue service manages a plurality of queues hosted by one or more entities. The queue service is in constant communication with the entities providing queue management, queue analysis, and queue recommendations. The queue service is likewise in direct communication with queued persons. Sending periodic updates such as targeted interactions in the form of products, services, and callback opportunities based on analysis of entity data, user-specific data, and data associated with all persons or groups at a given location, both physical or virtual.