CASE STUDY
Quality Control Overhaul for BPO Partner
Increased CSAT Scores from
33% to 69%
15%
Reduction in Average Handle Time (AHT)
11%
Increase in Productivity
CASE STUDY DETAILS
Project Summary:
The initial analysis revealed several critical insights:
- Quality control scores from manual evaluations did not accurately reflect agent performance or customer satisfaction.
- The AHT analysis indicated inefficiencies in call handling.
- Agent operational metrics were not aligned with quality control processes.
- Client customer satisfaction surveys, conducted through a third-party with a mere 4% response rate, failed to capture actionable insights.
- The manual tracking of agent dispositions and call drivers was inadequate for meaningful analysis.
CASE STUDY DETAILS
The Challenge:
The core challenge revolved around the BPO’s antiquated quality control practices, including heavy reliance on manual call reviews and outdated quality scorecards that emphasized compliance rather than customer experience or operational efficiency.
This approach resulted in a lack of comprehensive call reviewing policies, leading to a non-representative evaluation of call drivers.
PLAN OF ACTION
Project Solution:
The Knowledge Rhino team did a comprehensive overhaul of the quality control framework, integrating cutting-edge technologies and best practices.
THE OUTCOME
New Initiatives:
- Speech Analytics: Equipped with machine learning capabilities to automate call reviews and provide actionable insights; analyzes 100% of call interactions, ensuring a comprehensive understanding of call drivers and agent performance.
- Redesign of Quality Control Scorecards: Focus on metrics directly impacting customer satisfaction, such as agent courtesy, NPS, first call resolution, and overall customer experience.
- After-Call Surveys: Gather immediate feedback, focusing on aspects crucial to understanding the effectiveness of agents.
- Gamification and Avatar-Led Training: enhanced agent engagement and learning; more interactive and effective.
- Predictive Analytics: AI and machine learning algorithms provide near-instant predictions of CX and NPS scores, allowing for timely interventions and improvements.
- Self-Review: Agents received call recordings based on specific business rules, enabling self-assessment and fostering a culture of continuous improvement.
THE OUTCOME
Project Results:
The implementation of these solutions yielded remarkable outcomes within a short span:
- Survey response rates increased from 7% to 68%, indicating a higher level of customer engagement and willingness to provide feedback.
- Customer Satisfaction (CSAT) scores doubled from 33% to 69% within two months, reflecting a significant enhancement in the overall customer experience.
- AHT was reduced by 15%, indicating more efficient call handling and resolution processes.
- Productivity increased 11%, highlighting improved operational efficiencies and agent performance.
What’s more, internal agent satisfaction increased, as the new system provided clear coaching directives, ensuring targeted and effective performance improvement.