Contact center agents are one of the most important faces of any business. They’re on the front lines, interacting daily with customers, many of whom are not exactly happy to be speaking with a contact center agent in the first place.
These agents should be given the highest priority as it relates to the technology they are provided with to complete their jobs. However, customers often hear agents say, “I apologize. My systems are running slow. Please be patient.”
With access to fast and stable laptops, software-as-a-service (SaaS) applications, and internet speeds in the gigabyte (GB) range, how can a line of business (LOB) solution run slowly when customer satisfaction is on the line?
In the fast-pace world of contact center agents, ensuring smooth operations is paramount.
When a contact center’s LOB application runs slow, it can be the app, the endpoint operating system, the network, or the service provider. Typically, the answer can be any or all of the above.
But as many agents now work from home, we see most problems at the network layer. Business leaders for contact centers are measured on the customer’s satisfaction (CSAT). Still, without visibility into the supporting technology, the agents are often left to deal with customers with little support. Good luck!
In the fast-paced world of contact center agents, ensuring smooth operations is paramount. But managing and troubleshooting the array of issues that arise can be daunting. Organizations with call center agents need solutions to streamline troubleshooting processes and enhance the agents’ experiences.
Fortunately, there are best practices that can improve an agent’s experience, along with solutions that monitor and optimize virtual desktop infrastructure/desktop-as-a-service (VDI/DaaS), physical desktops, and local/SaaS applications to give the agents the best chance at achieving a great CSAT.
Data Collection
Efficient troubleshooting begins with accurate and timely data collection. For example, recording critical troubleshooting metrics, like central processing unit (CPU) activity every three seconds, can provide unparalleled insight into system performance. This real-time data enables IT teams to identify and address issues swiftly before they impact the productivity of an organization’s call center agents.
While it would take too long to go over every use case a call center agent could experience, the following examples provide insight into what organizations can quickly troubleshoot to help out their agents.
Proactive Notifications
Proactive problem identification is key to minimizing downtime. IT teams are empowered with proactive notifications, alerting them to potential issues such as application downtime or connectivity issues. Organizations can ensure a seamless digital experience for their call center agents by addressing issues before they escalate.
Hard drive failures, slow application load times, weak batteries, blue screens, and application crashes are annoying circumstances that cause agents to try fixing an issue themselves or call the helpdesk to troubleshoot. Fortunately, what can be measured can be notified.
Problem Scoring
Prioritizing the issues that impact the agents’ experiences can be daunting. If organizations can streamline the process, they can present a consolidated score of performance metrics, which highlights the most significant impact areas, guiding IT teams to direct their attention effectively.
Scoring dashboards across various domains, including VDI/DaaS, physical desktops, desktop applications, and SaaS/web applications, are invaluable tools that provide a comprehensive overview of system health.
If IT can delve deeper into issues via dashboards, they can uncover detailed insights into why a particular device or application is experiencing issues.
By drilling into the specifics, troubleshooters can pinpoint the root cause exponentially faster than traditional methods, eliminating the need to rely solely on end-user reports for troubleshooting. IT teams need to proactively identify and resolve issues, enhancing the call center agents’ experience.
Gen AI
Collecting lots of troubleshooting data and representing it with scoring is powerful, but sometimes IT teams need help looking at the data differently. Yes, custom reports are helpful, but sometimes answers are needed on the fly.
Generative AI (Gen AI) enables IT teams to ask questions about and represent data in unique ad hoc ways. Some Gen AI chatbots can access troubleshooting data and natural language queries and can help find complex problems across many machines without creating custom reports.
Script Actions
Scripts are a great way to get detailed troubleshooting data from a remote device. Without a digital employee experience (DEX) management platform, getting the script to run on a remote device can be problematic.
Fortunately, there are multiple ways to run a script on a remote device and various script languages that can run across Windows, macOS, and Linux. With this kind of technology, IT teams can run a troubleshooting script on a remote device in three ways:
- From a remote computer’s shell.
- Display the results in the device events.
- Store results in a custom database.
Remote Control
If IT teams have access to remote control functionality, that is sometimes the quickest way to troubleshoot a problem because they can see what the agent is experiencing.
To make remote troubleshooting more efficient and help agents get back up and running as quickly as possible, there are multiple ways for IT teams to remotely access an agent’s computer, including remote control, remote shadow, and remote shell.
Agent Satisfaction
Much effort is put into the customer’s CSAT, but what about the agent’s CSAT? Capturing the agent’s CSAT is vital because device metrics only tell half the story of an employee’s digital experience.
For example, if they are monitoring a system with a high CPU queue length, that suggests that the system is starved for CPU cycles and, as a result, applications might lag or become sluggish.
But these metrics show only the cause of a problem and how they might fix it. They don’t tell them how frustrated the agents were, how their productivity was impacted, or how stressed out they got. They don’t tell how they felt about their interactions with the system.
To ascertain how agents feel about their user experience, they need some kind of user sentiment reporting to query users to see what they are doing in an application and how they feel about their experience.
Capturing the agent’s CSAT is vital because device metrics only tell half the story...
CSAT will continue to be important and a focus for any organization with customers. However, those organizations with call center agents need to be concerned for their agents’ satisfaction.
By implementing the best practices in this article, organizations can help their call center agents improve overall satisfaction by monitoring and optimizing their devices, networks, LOB applications, and overall IT satisfaction. Begin today to improve your agents’ satisfaction and an increase in CSAT will naturally follow.