Unlock New Performance Insights With Agent Screen Recording

Reliable data, conversation monitoring software, and analytics are the tools call centers need to evaluate agent performance. Most call centers use common metrics to evaluate agent performance, such as:

• Customer Satisfaction (CSAT)
• First-Call Resolution
• Service Level Percentage
• Average Handle Time (AHT)
• Abandon Rate
• Cost

Call center software, such as Level AI, provide insights from existing data and an interface that allows call center leaders the ability to monitor agent performance across support channels. Additionally, Level AI allows contact center teams to build custom reports from other data sources, such as BI (business intelligence) tools.

The best contact center analytics are designed to uncover meaningful insights, organize your most important metrics, and answer questions about call center agent performance from a single location.

Here are 7 ways to improve call center agent performance:

1. Adopt advanced NLU (natural language understanding) software that understands customer intent. For example, Level AI uses NLU to provide contact center agents answers and solutions to almost any customer inquiry in real-time with exceptional accuracy. Most CCaaS (call center as a service) software relies on NLP (natural language processing) technology. NLP models rely on keyword matching, which is highly inaccurate and time consuming.
2. Eliminate avoidable calls. By providing solutions to the most common customer issues without involving a live agent, you’ll give agents more time to spend on the most important customer support issues.
3. Train call center agents in real-time with AI software. Use advanced contact center software that can train your agents in real-time, such as Level AI. This allows for independent learning and reduced agent onboarding times.
4. Monitor a higher percentage of call center agent conversations. You can monitor more support conversations with technology that can accurately monitor more than 1-2% of agent conversations. Level AI, for example, accurately monitors 100% of agent conversations.
5. Use the best call center metrics for your business. Re-examine your call center metrics, make sure your goals are clear and agents know how they are being evaluated. A great way to manage and communicate your most important call center metrics is to maintain a QA (quality assurance) scorecard.
6. Utilize call center analytics tools. Know what’s happening in your call center with analytics that can accurately report your KPIs and house data from multiple BI (business intelligence) tools in one location.
7. Build call center quality assurance rubrics over time. Provide call center agents a clear process for solving common problems and utilize modern contact center software to learn how to solve more complex customer support scenarios.

Call center software is typically separated into two categories based on where it’s hosted: on-site, or in the cloud. Cloud-based contact center software is now commonly referred to as CCaaS, or Contact Center as a Service.

Until recently, the large majority of call centers still used locally installed software. However, in 2022, the majority of companies have either adopted or are planning to adopt cloud-based solutions, such as Level AI.

To further break down the type of software call center agents use depends on whether the call center is primarily inbound, outbound, or a mixture of the two. Additionally, not all call centers are simply making voice calls. Many contact centers use a mixture of voice call software, email software, and chat software.

CCaaS software has become popular largely due to new platforms that offer contact centers the ability to monitor the performance of their agents across all communication channels. Level AI, for example, monitors 100% of support agent conversations across voice calls, email, and chat.