Agent Performance Evaluation with Perception-Gap Action Plans
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Solution Overview
Problem
Conventional systems inaccurately rate agents based on customer satisfaction alone, lack flexibility in data collection and analysis, and require multiple software tools for managing customer experience data, making it difficult to develop targeted coaching plans efficiently.
Innovation Solution
An agent evaluation system that utilizes machine learning models to compare user and agent feedback data, generating perception gaps and performance scores, and provides suggested actions and coaching plans through a unified graphical interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional systems base agent ratings solely on customer satisfaction ratings, then the rating process is simple and quick, but the accuracy of agent ratings deteriorates because customer perceptions alone do not account for other aspects of agent performance
Solution Approach 1:
The patent merges multiple data sources including customer satisfaction ratings, agent self-assessments, and objective interaction metrics into a unified evaluation system. This combination allows for more accurate agent ratings by considering multiple perspectives rather than relying solely on customer feedback.
Solution Approach 2:
The system creates a multi-functional evaluation platform that collects and processes various types of data (customer feedback, agent self-assessment, interaction metrics) through a single integrated system, enabling comprehensive agent evaluation while maintaining operational efficiency.
2Adaptability or versatility
If conventional systems require multiple software tools to collect and report customer experience data, then the system can gather diverse data types, but the ease of operation deteriorates as managers must navigate multiple tools and steps
Solution Approach 1:
The patent consolidates multiple data collection and reporting functions into a single integrated platform. Managers can access and analyze diverse customer experience data including surveys, interaction metrics, and agent performance data through one unified interface, eliminating the need to navigate multiple separate tools.
Solution Approach 2:
The system provides a universal platform that handles multiple data types and evaluation functions within a single tool, allowing managers to collect, analyze, and report on various aspects of customer experience without switching between different software applications.
3Loss of information
If conventional systems use multiple steps to collect information for developing action plans, then comprehensive data can be gathered, but the productivity deteriorates due to the time required to navigate multiple steps
Solution Approach 1:
The system performs preliminary data aggregation and analysis, automatically compiling relevant customer experience data and generating initial insights before managers begin developing action plans. This preliminary processing reduces the manual steps required and accelerates the overall plan development process while maintaining information completeness.
Solution Approach 2:
The system provides automated feedback mechanisms that deliver relevant performance data and insights directly to managers, enabling faster decision-making and action plan development. The feedback loop includes real-time or near-real-time data delivery that reduces the iterative steps traditionally required to gather sufficient information.
4Reliability
If conventional systems rely on customer satisfaction ratings only, then the system is simple to implement, but the reliability of agent performance assessment deteriorates due to lack of multiple perspectives
Solution Approach 1:
The patent combines multiple assessment perspectives including customer satisfaction ratings, agent self-assessments, and objective interaction metrics into a unified evaluation framework. This multi-perspective approach enhances the reliability of agent performance assessment by cross-validating results across different data sources.
Solution Approach 2:
The system implements a multi-source feedback mechanism that collects performance data from customers, agents, and system metrics simultaneously. This triangulated feedback approach improves assessment reliability by comparing and correlating data from multiple independent sources rather than relying on a single perspective.
Data Source
AI summary
The present disclosure relates to systems, non-transitory computer-readable media, and methods for determining an existence of a perception gap for an interaction event. In particular, in one or more embodiments, the disclosed systems generate a suggested action and provide the suggested action for display via a graphical user interface of an agent device. In some embodiments, the disclosed systems utilize a machine learning model to generate the suggested action for the agent. Furthermore, in one or more embodiments, the disclosed systems generate an agent performance score reflecting an overall performance of an agent. In some embodiments, the disclosed systems utilize a machine learning model to generate the agent performance score.