17457743. ENHANCED ISSUE DETECTION AND RESOLUTION IN A CALL CENTER simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)
Contents
ENHANCED ISSUE DETECTION AND RESOLUTION IN A CALL CENTER
Organization Name
INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor(s)
Clement Decrop of Arlington VA (US)
Tiberiu Suto of Franklin NY (US)
Zachary A. Silverstein of Georgetown TX (US)
ENHANCED ISSUE DETECTION AND RESOLUTION IN A CALL CENTER - A simplified explanation of the abstract
This abstract first appeared for US patent application 17457743 titled 'ENHANCED ISSUE DETECTION AND RESOLUTION IN A CALL CENTER
Simplified Explanation
The patent application describes a method for using machine learning to detect and resolve issues in a call queue with multiple active callers. Here are the key points:
- The processor monitors the call queue and triggers a first threshold when a certain percentage of active callers are in the queue.
- The processor analyzes information in each caller's customer account to identify common factors that may be causing the issue.
- The processor registers the occurrence of the event as a domain event and provides a resolution to the active callers.
- If a second threshold is triggered, the processor executes an Interactive Voice Response workflow.
Potential applications of this technology:
- Call centers: This technology can be used in call centers to proactively detect and resolve issues in the call queue, improving customer satisfaction and reducing wait times.
- Customer service: Companies that provide customer service over the phone can use this technology to identify and resolve issues more efficiently, leading to better customer experiences.
- Telecommunications: Telecommunication companies can implement this technology to manage call queues and address issues in real-time.
Problems solved by this technology:
- Long wait times: By proactively detecting and resolving issues in the call queue, this technology can help reduce wait times for callers, improving their overall experience.
- Inefficient issue resolution: The use of machine learning and analysis of customer account information allows for more accurate identification of common factors causing issues, leading to more effective and efficient resolutions.
- Lack of proactive customer service: This technology enables companies to take a proactive approach to customer service by identifying and addressing issues before they become major problems.
Benefits of this technology:
- Improved customer satisfaction: By resolving issues in a timely manner and reducing wait times, this technology can significantly improve customer satisfaction.
- Increased efficiency: The use of machine learning and automated workflows allows for faster and more efficient issue resolution, saving time and resources.
- Proactive problem-solving: Instead of waiting for customers to report issues, this technology proactively detects and resolves them, leading to a more proactive and customer-centric approach to customer service.
Original Abstract Submitted
In an approach for proactively detecting and resolving an issue of a plurality of active callers placed in a call queue using a machine learning technique, a processor monitors a call queue. A processor determines that a first threshold is triggered when a pre-set percentage of active callers are placed in the call queue. A processor analyzes a set of information in a customer account of each active caller for one or more common factors. A processor identifies a reason for the event occurring from the one or more common factors. A processor registers the event occurring as the domain event. A processor resolves the event occurring by providing the plurality of active callers with a resolution. A processor determines if a second threshold is triggered. Responsive to determining the second threshold is triggered, a processor executes an Interactive Voice Response workflow.
