Dynamic Contact List Adaptation via Speech Pattern Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current contact list systems in call centers often fail to provide agents with access to the best available expertise to handle customer issues, especially when queries span multiple areas or exceed an agent's normal experience, as the default or personalized lists may not accurately reflect the expertise of potential contacts.
Innovation Solution
A method that monitors live communications interactions to detect patterns and update contact lists in real-time, allowing for the selection and presentation of the most suitable experts to agents during customer interactions, using speech recognition and subject codes to generate dynamic lists of contacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static contact list is used, then the system is simple to implement, but the contact list cannot adapt to changing communication needs and patterns
Solution Approach 1:
The contact list is transformed from a static structure to a dynamic one that automatically updates based on monitored communication patterns. The system continuously analyzes interactions and reorders contacts based on detected patterns, making the list adaptive to changing needs without manual intervention.
Solution Approach 2:
The system monitors live communications interactions and uses this feedback to detect patterns and update the contact list accordingly. The feedback loop ensures the contact list reflects actual communication behavior and adjusts automatically based on observed patterns.
2Ease of operation
If a personalized contact list is maintained, then the user has control over their contacts, but the system cannot proactively suggest relevant contacts based on current interaction patterns
Solution Approach 1:
The system performs self-service by automatically analyzing communication patterns and updating the contact list without requiring user input. It independently detects patterns and reorders contacts based on monitored interactions, reducing the need for manual maintenance while preserving user control.
Solution Approach 2:
The system continuously monitors communications and uses this feedback to detect patterns that indicate expertise relevance. This feedback mechanism ensures the contact list is updated with current expertise information without losing user control over the list structure.
3Productivity
If the contact list is updated manually, then the user can control the list content, but the system cannot respond in real-time to changing communication needs
Solution Approach 1:
The system operates continuously by monitoring communications and updating the contact list in real-time without interruption. This continuous action ensures the contact list always reflects current communication patterns and expertise availability, eliminating manual update delays.
Solution Approach 2:
The system performs automatic self-service updates by independently analyzing communication patterns and reordering contacts without requiring user intervention. This automation significantly increases update speed while the complexity is managed through algorithmic processing rather than manual operations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables agents in call centers to consult the most appropriate experts in real-time, improving the handling of complex customer issues by continually suggesting contacts suited to the current situation, enhancing the effectiveness of customer support.
Implementation Method 1
the step of monitoring a live communications interaction comprises conducting speech recognition on a stream of voice data passing through the interface
Data Source
AI summary
During communications sessions between an agent in a call center and a customer, it is often desirable that a secondary agent is consulted, the secondary agent perhaps more suited to the particular needs of the customer. It is preferred that the original agent is presented with a list of the best-suited agents with which to consult, if needs be. Accordingly, a system and method for managing a list of contacts for presentation to a user of a computer system (e.g. a call center agent) is disclosed. The system provides for the monitoring of live communications between an agent and a customer, and further provides for the detecting of a pattern of data in the monitored live communications interaction (e.g. utilising speech recognition to recognise use of a particular keyword). The system is then operable to present a list of suggested contacts to the agent, the suggested contacts chosen based on a match between selection criteria for that contact and on the particular data pattern detected.