Automated Call Selection for Quality Evaluation
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Solution Overview
Problem
Current quality management systems in call centers face inefficiencies in selecting calls for evaluation, as quality managers must manually search and retrieve calls based on multiple criteria, making it a time-consuming and ineffective process, which limits the benefits of evaluation and adaptation to changing organizational needs.
Innovation Solution
A quality management system that automates the selection of calls for evaluation by defining parameters, quotas, and criteria, allowing for the automatic association of evaluation forms with selected calls, and providing a 'push' mode of operation where relevant recordings are made available to quality managers, enabling efficient evaluation based on various business objectives and KPIs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection of calls for evaluation is performed, then quality managers can evaluate calls based on criteria, but the process becomes time-consuming and ineffective when dealing with thousands of recorded calls
Solution Approach 1:
The system enables automatic selection of calls for evaluation through self-service mechanisms where the quality management system autonomously identifies and selects calls based on predefined criteria, eliminating the need for manual intervention in the selection process while maintaining evaluation accuracy
Solution Approach 2:
The system changes the selection parameters from manual criteria-based selection to automated multi-parameter selection including call type, agent performance metrics, customer satisfaction scores, and business objectives, enabling precise identification of relevant calls without manual time investment
2Ease of operation
If random selection of calls is used, then the selection process is simplified, but the benefits of evaluation are severely limited
Solution Approach 1:
The system implements dynamic call selection that adapts to changing organizational needs and business objectives, automatically adjusting selection criteria and weights based on current priorities, ensuring both operational simplicity and evaluation effectiveness
Solution Approach 2:
The system incorporates feedback mechanisms where evaluation results and performance data continuously inform and refine the automated selection process, improving evaluation effectiveness over time while maintaining ease of operation through the automated system
3Reliability
If multiple criteria are applied for call selection, then evaluation quality improves, but the complexity of the selection process increases
Solution Approach 1:
The system implements a universal automated selection framework that handles multiple selection criteria and business objectives through a single multi-functional platform, managing complex evaluation quality requirements without increasing operational complexity for users
Data Source
AI summary
Embodiments of the invention are directed to a computer-implemented method of performing a quality evaluation. The method may include selecting from a plurality of interaction recordings at least one interaction recording according to at least one KPI. The method may include associating a selected interaction recording with a predefined evaluation form, presenting interactions selected for evaluation to an evaluator and performing a predefined action based on a result of the evaluation.