Today’s leading business process outsourcers (BPOs) are getting more from their call center quality monitoring data. And they’re doing it with conversational AI and automation.
What is call center monitoring and why does it matter?
Call center quality monitoring is a critical tool for measuring BPO health and effectiveness. It’s also a wellspring of valuable insights for improving both customer experience (CX) and agent performance. With today’s advanced conversational automation software, BPOs are unlocking richer call center monitoring data than ever before and leveraging it to optimize their end-to-end CX operations. Those that utilize AI-enabled “intelligent” call center monitoring have a considerable advantage over their peers—particularly in today’s digital-first BPO environment.
Perhaps the most obvious benefit of intelligent call center monitoring is improved customer experience. Monitoring software that uses conversational AI can capture, record and analyze spoken and written customer input faster and more accurately than live agents (who are only human, after all). This not only eliminates manual recording errors; it can also unearth subtle insights—such as sentiment and emotional feedback—that agents might overlook. These insights can then be used to fine tune the overall call center quality monitoring process and, consequently, improve customer experience.
Call center quality monitoring doesn’t exist in a vacuum. In fact, the whole purpose of quality assurance is to ensure the entire customer service experience meets organizational quality standards. That includes training agents on best practices, call etiquette, process efficiency and other factors that impact call quality. For many contact centers, quality assurance training translates to call recording playback (with or without some form of supporting coaching). However, this reactive approach to call center monitoring yields limited results which can only be applied to future interactions.
To be truly effective, call center quality monitoring should be proactive, offering agents actionable guidance and training during the call itself. By analyzing interactions in real-time, conversational AI can identify friction points and automate next-best actions based on established call quality standards. It also enables real-time agent coaching, allowing coaches to provide valuable on-call training and to even intervene on behalf of agents during particularly complex or challenging calls.
What are the common challenges when implementing call center monitoring?
Call center quality monitoring isn’t without its challenges, some of which are more acutely felt or specific to the BPO industry. Because BPOs handle large volumes of calls on the behalf of others, they must balance often-limited staffing and technological resources with lofty client expectations, service requirements and quality assurance standards. Common challenges when implementing call center monitoring within the BPO space include:
Monitoring All Calls
BPOs handle higher customer call volumes than most industries, often for multiple clients. That volume can quickly overwhelm legacy call center monitoring programs and manual processes. To make matters worse, many BPOs rely on live quality assurance staff who can only monitor a small percentage of calls. Fortunately, conversational AI can solve these volume-related challenges and more. By assigning AI to call center quality monitoring, BPOs can effectively monitor 100% of their contact center calls—regardless of volume. And because machines do the monitoring (not people), they are less prone to errors and oversights.
Effective call center quality monitoring requires agent buy-in and participation. However, when QA programs and processes are excessively tedious, frustrating or burdensome, agents are less likely to participate fully (if at all). By eliminating manual friction points and streamlining the call center monitoring process, conversational AI can calm agent frustrations and secure stronger participation across the entire operatio
Transparency and Tracking
Another big challenge to effective call center quality monitoring is tracking calls—and their QA outcomes—effectively and transparently. Again, manual efforts and agent-driven programs make it difficult, if not impossible, to consistently monitor even a small percentage of calls. Not so for conversational AI. In call center monitoring, AI serves as a “single source of truth”, ensuring that all calls are tracked consistently with complete data transparency for optimal quality assurance.
What are the best practices for effective call center monitoring?
While call center quality monitoring protocols differ from call center to call center, there are a few fundamental best practices all BPOs should follow for optimal efficiency and effectiveness. One thing they all have in common: their value increases exponentially with automation and conversational AI. Here are the top four best practices for effective call center monitoring:
When setting call center monitoring standards, be sure to define quality parameters fully and clearly. Remember: consistency is everything. Quality standards should be embedded throughout the agent experience—from onboarding and training to knowledge base reference materials. Conversational AI and automation can track call center quality monitoring, ensure standards are met and even help refine standards using conversational data and other customer feedback.
To be effective, call center monitoring needs definitive benchmarks for measuring quality standards. Key performance indicators (KPIs) and metrics help contact centers gauge their QA health and identify areas for improvement. Common call center quality metrics include call quality, first call resolution (FCR), average handle time (AHT) and customer satisfaction. (To learn more, read our article, “5 Important Metrics for Call Center Success“.)
The best call center monitoring operations are the most transparent and easiest for agents to grasp. To maintain quality and consistency, the entire organization must be on the same page. Automation can ensure quality standards are communicated and updated enterprise-wide when needed. It can also help train and educate agents during calls by surfacing relevant knowledge articles and guiding agents via next-best action prompts.
Compliance can mean a few things to call center quality monitoring. There’s compliance with company quality standards, and there’s compliance with industry and/or government guidelines and regulations. By listening for compliance-related conversational cues and identifying “hot spots” for potential non-compliance, conversational AI can help BPOs achieve both. And because it can monitor 100% of calls, the technology can drive significantly higher compliance rates than human auditors ever could.
Case Study: BPO improves call center monitoring with conversational AI and automation.
A global business process outsourcer wanted to deliver business insights to one of its Fortune 500 customers, who used the company’s services for its Global IT helpdesk. However, the client did not have enough QA bandwidth to monitor high volumes of calls and was able to monitor only 5% to 10% of calls manually. Consequently, it was difficult to evaluate agent performance, understand the customer’s ‘real voice’ and measure customer satisfaction scores.
The company approached Uniphore for a solution to address the business need. After careful consideration, U-Analyze—Uniphore’s advanced interaction analytics platform—was recommended and ultimately implemented. This solution provided the company with actionable insights to evaluate agent performance and calls.
A global leader in business process outsourcing and information technology services across multiple locations with over 80,000 professionals. The company helps their clients to create a competitive edge by utilizing business process outsourcing and IT services.
- Inability to monitor huge call volumes owing to lack of QA bandwidth
- Lack of actionable insights to improve customer satisfaction
- Lack of understanding of the 'real voice' of customers using traditional methods
U-Analyze uses analytics and insights from 100% of interactions across channels. It improves business processes and extracts actionable insights into customer conversations.
- Enabled 100% call monitoring
- Customized and flexible dashboards
- Identified gaps in the IT helpdesk process
- Improved agent soft skills and IT skills
- Recognized leaders and laggards with automated scoring
- Auto-generated reports on a daily and weekly basis
The customer interaction analytics solution enabled 100% monitoring of calls. The solution also provided auto generation of customized and advanced reporting, helping the company to identify targeted training to agents, leading to enhanced customer service experience. All customer-agent interactions were monitored on different parameters such as agent performance trends, individual agent performance, location, and other considerations. Unlike the conventional method of measuring customer satisfaction through an after-call-survey, the company could now assess customer satisfaction with 100% call monitoring, thus arriving at CSAT scores in a uniform and unbiased manner.
Want to learn more about call center monitoring?
Uniphore has worked with countless BPOs to develop and deploy effective call center quality monitoring solutions. It you’d like to learn more about how our industry-best conversational automation platform can improve your call center monitoring operations, please contact us to speak with an expert and schedule a demo.