AI Transcript-Based Control Presets for Operator Evaluations
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing call center evaluation systems rely on manual and time-consuming processes prone to human error, bias, and fatigue, failing to accurately assess agent performance due to inconsistent application of performance standards.
Innovation Solution
An AI-based system that analyzes voice session recordings and transcripts to identify common words or phrases associated with specific evaluation answers, allowing for automated scoring and reducing manual interaction by generating auto-answer parameters for evaluation interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual evaluation processes are used by evaluators, then evaluation can be performed with human judgment and contextual understanding, but the process is time-consuming and prone to human error and bias
Solution Approach 1:
The system enables self-service evaluation by allowing the evaluation system to automatically generate draft evaluations using AI analysis of call transcripts, eliminating the need for manual evaluator input for routine assessments while maintaining the ability for human review when needed
Solution Approach 2:
The patent replaces the mechanical manual evaluation process with an automated AI-based system that analyzes call transcripts, identifies performance indicators, and generates evaluation scores, substituting human manual labor with automated computational processes
2Stability of the object's composition
If manual evaluation processes are used, then evaluators can apply performance standards with contextual understanding, but consistency is compromised due to fatigue and human error
Solution Approach 1:
The system incorporates feedback mechanisms where AI analysis of call transcripts provides objective performance measurements that can be reviewed and adjusted by evaluators, creating a continuous improvement loop that enhances both consistency and accuracy over time
Solution Approach 2:
The evaluation process is segmented into distinct components: AI-generated draft evaluations based on transcript analysis, evaluator review and adjustment, and final scoring. This segmentation allows each component to specialize, with AI handling consistent objective measurement and humans providing contextual judgment
3Productivity
If automated AI-based evaluation is implemented, then evaluation speed and consistency are improved, but the system requires sophisticated analysis of transcripts and voice recordings
Solution Approach 1:
The AI evaluation system is designed as a universal platform that can handle multiple evaluation criteria and call types through a single integrated system, using the same core transcript analysis technology across different evaluation scenarios to manage complexity
Data Source
AI summary
A data processing system for artificial intelligence-based setting of controls in an evaluation interface comprising a data store storing: a plurality of transactions; a plurality of completed evaluations, each completed evaluation including an indication of a transcript portion associated with an evaluation answer. The system determines a word or phrase common to a first set of transcript portions associated with the evaluation answer; creates a first set of auto answer parameters that includes the word or phrase; auto answers the question for a set of test transactions to generate an auto answer for each test transaction; and based on a determination that the first set of auto answer parameters auto answered the question with a threshold level of accuracy, configures an evaluation system to use the first set of auto answer parameters to preset an answer control in an evaluation operator interface.