To stay competitive, customer support teams need to do more to improve customer experiences than post-call satisfaction surveys. Self-service is now the standard for most tier-1 issues, so customers who do call in for assistance expect a seamless, personalized experience—no matter how many other callers are in the queue. This puts a lot of pressure on agents to offer the best service possible. Luckily, innovative quality assurance (QA) agent tools can help.
Using advanced AI, these tools significantly reduce average handle time (AHT) by enabling agents to understand customer sentiment, identify areas for improvement, and pursue ongoing training. In turn, customer experience (CX) improves, while AHT falls. So what are the best QA agent tools for businesses looking to optimize their customer service? Let’s dive into it.
Real-Time Sentiment Analysis
Understanding how a customer feels—and how to fix it—is key to improving satisfaction. But like any skill, it takes time and experience for agents to learn how to interpret sentiment, then address issues appropriately.
Real-time sentiment analysis offers deep insights into customers’ emotions and needs. This QA agent tool analyzes live call recordings to identify key words or phrases, as well as tone. Positive and negative wording are both highlighted to improve issue handling over time.
The agent and their manager can review sentiment analysis results together to adjust their training and create strategies for success. When leveraged alongside other QA agent tools, sentiment analysis empowers agents to turn negative interactions into positive experiences.
Automated Post-Call Quality Scorecards
On large or overwhelmed customer support teams, finding the time to analyze the quality of every single call can be tough…or even impossible.
That’s where automated quality scorecards come in. This QA agent tool uses AI to automatically score every customer interaction, based on specific and customizable metrics. From call length to call silence percentage and agent overtalk, quality scorecards offer a holistic view of the success of every call.
By automating call analysis, customer support teams can easily discover new and better ways of meeting their KPIs. Each call is an opportunity for agents to learn and improve. This makes it much easier to reduce AHT and FCR in the long term.
AI-Powered Training and eLearning
It’s no secret that retaining customer support staff is tough, especially as call volumes and customer expectations rise. Unfortunately, the average customer support organization loses $600k annually due to agent attrition.
To combat this, teams can invest in QA agent tools like AI-powered training and eLearning initiatives. Ongoing training helps agents feel engaged and supported while encouraging them to strengthen their skills and efficiency.
It’s a lot like training an athlete. Consistent guidance and motivation create top performers. Using real-life examples or custom ones, managers can target learning to improve one agent’s performance or an entire team’s. By incorporating training into every agent’s workday, customer support teams can drastically improve KPIs and overall efficiency.
How do I get started with QA agent tools?
There are a lot of QA agent tool solutions out there. When it comes to reducing support costs, teams should beware of expensive, disparate point solutions. A support automation platform like Capacity that incorporates QA agent tools into its holistic support ecosystem is the best way to reduce expenses while boosting performance.
Want to learn more about reducing AHT and boosting CSAT with AI-powered support automation? Read our guidebook, The Future of AI for Contact Centers, to dive deeper into optimizing your support strategies with new tools.
The Future of AI for Contact Centers
Discover:
- The different types of AI
- A framework for applying support automation
- Tips for choosing solutions