Agent Communication Support Assistant for Real-Time Coaching

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Traditional human coaching systems for customer service agents are labor-intensive, vary in quality, and are not effective in providing real-time assistance, as they rely on supervisors monitoring communications.

Innovation Solution

A software application that continuously monitors agent communications using natural language processing algorithms and machine-learned models to provide automatic, tailored suggestions for improvement, utilizing a framework with a discriminator model to activate specialized communication support assistants.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If human supervisors monitor agent communications to provide coaching, then coaching is provided, but the system becomes labor-intensive and cannot provide continuous real-time assistance

Engineering Contradiction:

Improvecoaching efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent replaces the mechanical system of human supervisors monitoring communications with an automated natural language processing system. The NLP algorithm continuously analyzes agent-customer interactions, detecting conversational triggers and providing coaching suggestions without human intervention, thereby eliminating labor-intensive monitoring while maintaining or improving coaching effectiveness.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service coaching where the NLP-powered assistant autonomously monitors communications, identifies coaching opportunities, and provides real-time suggestions to agents. The system serves itself by automatically detecting triggers, generating coaching content, and delivering feedback without requiring human supervisor involvement, thus improving productivity while reducing system complexity.

Inventive Principle:

Principle #25Self-service

2Duration of action of moving object

If human supervisors monitor all agent communications, then continuous coaching is provided, but the labor requirement and cost increase significantly

Engineering Contradiction:

Improvecoaching durationVSAvoidhuman resources

Core Design Contradiction:

Duration of action of moving objectVSQuantity of substance

Solution Approach 1:

The patent substitutes human supervisors with an automated NLP system that can continuously monitor agent communications without additional human resources. The natural language processing algorithm analyzes conversations in real-time, providing extended coaching duration while maintaining constant human resource levels, thereby resolving the contradiction between continuous monitoring and resource consumption.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Adaptability or versatility

If a single general coaching model is used for all agents, then the system is simpler, but it cannot provide tailored coaching for individual agent needs

Engineering Contradiction:

Improvecoaching personalizationVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent implements local quality by customizing coaching suggestions based on individual agent characteristics, performance data, and specific needs. The NLP system analyzes each agent's conversation patterns and provides personalized feedback rather than generic coaching, achieving high adaptability while managing system complexity through targeted personalization strategies.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system performs preliminary action by pre-processing and analyzing agent performance data, conversation history, and training requirements before delivering coaching. This preliminary analysis enables the system to tailor coaching content to individual agent needs while maintaining systematic organization, balancing personalization with manageable complexity.

Inventive Principle:

Principle #10Preliminary action

4Reliability

If human coaching is provided, then feedback is given, but the feedback quality varies considerably amongst supervisors

Engineering Contradiction:

Improvecoaching consistencyVSAvoidcoaching quality

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The patent applies parameter changes by standardizing coaching quality through consistent NLP algorithm parameters and evaluation criteria. The system maintains reliable coaching consistency by using fixed algorithmic parameters for analyzing conversations and generating feedback, while improving measurement precision through data-driven insights and objective performance metrics that eliminate human variability.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250039111A1Chat communication support assistants

Publication Date: 2025.01.30 WELLS FARGO BANK NA

AI summary

Disclosed in some examples are methods, systems, and machine-readable mediums which provide for an agent support application with a plurality of plug-in communication support assistants. Each of the plurality of plug-in communication support assistants monitors communications between the agents and customers for different conversational triggers. Conversational triggers may be any conversation, either by the agent or the customer, that the communication support assistant is trained to detect. Upon detecting one of these conversational triggers, the plug-in communication support assistant provides one or more suggestions to the agent.