Call quality monitoring is the process of evaluating call quality to meet customer needs and requirements. It is important for analyzing customer preferences, experiences, and behaviors. Quality monitoring objectives include integrating AI analytics and improving the listening process. Call centers should use advanced software rather than excel to analyze performance data and make strategic decisions. Methods to improve include aligning calls with technologies like CTI and speech analytics, and using speech analytics to understand customer sentiment. Performance management is also key and involves monitoring quality, providing feedback, and addressing issues through innovative training. The presentation emphasizes the importance of quality assurance, illustrates insights from performance management tools, and frames speech analytics as effective for improving performance.
2. What is call center quality assurance?
• The process of quality assurance within call center is evaluating the
quality of call made by an agent that advocates the requirement and
the needs of a customer.
• Customer calls is now based upon live chats. AI, email and social
media interaction.
• Quality assurance accounts acceleration in implementing of effective
business performances ,efficient agent operations and strategic
decision making.
3. Process of upgrading quality monitoring of
call
• Monitoring of call quality is required for analyzing consumer
preference and buying behavior.
• Consumer experience, integration with AI analytics, strategically
organizing of reports and upgrading the listening process to consumer
are the objectives of quality monitoring.
4. Methods to upgrade quality assurance of call
• Call centers shall eliminate excel and use advanced software for
analyzing performance analytics.
• Analyzing performance analytics and then inducing strategic decisions
for enhancing performance.
5. Methods to upgrade quality assurance of call
• Call centers shall align the process of calling with software such as
language management, CTI and speech analytics.
• Depicting consumer behavior and consumer sentiment through using
of speech analytics application.
• Further improvisation for depicting podiums to connect with
consumers is required for call centers.
6. Combine performance management and
monitoring.
• Performance monitoring encompasses quality scores, training and
encountering challenges.
• Performance management accounts feedbacks, opportunities and
consumer interaction.
• Recognizing performance issues shall raise the standards of
performance management in call centers.
• Innovative training shall be addressed for raising performance
management.
• Information should be provided to stakeholders during training to
make it innovative.
7. Effectiveness of speech analytics application
• Speech analytics examines human speech to depict emotion,
preference and buying behavior.
• Speech analytics in call center can raise revenue and help in
developing effective performance.
8. The dependence of AI on human intelligence
• Human intelligence evaluates consumer needs and performance
weaknesses while AI only helps in gaining data insights.
• Remarkable performance in call centers can be achieved through
combining AI with human intelligence.
• AI should be used for technological developments while human
intelligence shall adhere contemplating upon these developments.
9. Concise
• The importance of quality assurance into the process of calls from call
centers is highlighted through the presentation.
• Insights of performance management through applications, training
and feedbacks is illustrated into the presentation.
• Framing of speech analytics as highly effective for raising performance
is emphasized into this presentation.
10. Reference
Kachhawa. A, 2021. What, Why And How Of Call Center Quality Monitoring?.
https://www.qevalpro.com/blog/call-center-quality-monitoring/#