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Preventing Burnout: The Human Benefits of Machine Learning

If you’ve ever worked in customer service, or even had a conversation with a customer service agent regarding a question, problem, or complaint, then you know that this line of work is no cakewalk. Customer support teams are in the service business, after all, including all the ups and downs that come with it. With online support agents in particular, the tasks tend to be repetitive and monotonous.

That’s not to say that great customer service environments don’t exist. After all, support leaders make a point to hire agents who are upbeat, engaged, and patient, no matter what happens throughout the course of a day. These people are innately driven to help people, to drive empathy at scale and solve whatever problems come their way.

Yet, when agents find themselves overwhelmed by issues like growing backlogs, manual ticket classification and time-consuming triage, the pressure of spending long hours just trying to staunch the flow of endless incoming queries can become too much.

Maggie Armato, Pinner Support Manager, has experienced the challenges of employee burnout firsthand. “To be honest, I’ve found that one of the hardest things with support is employee retention,” she says — especially if they are stuck responding to tickets eight hours a day.

When agents can’t see the light at the end of the tunnel, they begin to feel exhausted, disengaged, and negative about their work environment or duties. In a word, they begin to experience burnout.

Preventing Burnout: The Human Benefits of Machine Learning

What is burnout?

According to the U.S. National Library of Medicine, burnout is a psychological term referring to exhaustion and diminished interest resulting from severe stress, conflict, and feelings of being over-worked or even under-challenged. Three primary symptoms of burnout include emotional exhaustion, disengagement, and reduced performance. People experiencing burnout may feel drained, overloaded, cynical, and even listless or distracted. Some even develop digestive problems or trouble sleeping.

In the workplace, agents experiencing burnout may show signs of negativity of apathy. They may begin taking days off work due to exhaustion, and show diminished interest or indifference in their day-to-day tasks.

Unfortunately, burnout is not an uncommon affliction. According to a study by Toister Performance Solutions, 74% of contact center agents are at risk of burnout.

“These are all potentially harmful issues,” Jeff Toister writes. “Emotional exhaustion can make it difficult to project friendliness and caring to customers. Alienation from job-related activities might mean an agent gives less effort and rarely goes the extra mile. The result of all that is reduced performance.”

As a support manager, you rely on your agents not only to tackle the influx of customer inquiries and problems that come in on a daily basis, but also to transmit your company’s tone, values, and overall mission in every response. You need your agents for the team to function.

Learn how Wise Support integrates with Zendesk and Salesforce platforms.

How can you relieve the pressure and reduce the seemingly endless onslaught of tickets to ease their exhaustion, rekindle their spark, and reignite their curiosity and passion for career development and growth?

Machine learning can help

You may think of machine learning as a purely data-driven automation tool that does our thinking for us. With apps that can uncover patterns in customer issues, prioritize incoming tickets, and quickly respond with consistently-approved macros, it seems like machines can do it all.

It’s a common misconception, however, that these tools are designed to replace human customer service agents altogether. Many people fear that using machines in place of people can potentially lead to catastrophic outcomes like those illustrated by Microsoft’s chatbot, Tay. Instead, it’s important to understand how these tools actually augment and benefit human customer service workers’ outcomes. Human agents are essential to successful customer service, and machine learning can actually reduce strain and prevent burnout in the long run.

Here are some ways intelligent automation tools can create tangible results for your support team:

  • Assist agents. Machine learning tools don’t replace human agents; they make their lives easier. Machine learning can help relieve the mindless burden of low complexity, repetitive tasks, which are exactly the kinds of tasks that can burn out an agent.  Intelligent response tools can automatically classify tickets for triage and reporting purposes so agents don’t have to. They can also automatically respond to simple, recurring inquiries, effectively taking over the most mundane manual work. These actions help focus on more interesting and challenging issues and avoid feeling burned out.
  • Improve productivity. One of the functions of intelligent recommended response tools is to reveal the best templates so that agents can find, adjust, and send answers quickly and easily. This promotes more consistent responses from agent to agent and helps them do a better job solving an even higher number of customer problems than they could before. Not only does this make the agent’s life a lot easier, but the faster and higher quality answers make customers happier. And when customers are happy, support agents feel rewarded, motivated, and more productive.
  • Empower staff. Your support staff is made up of talented individuals. While they likely have great capacity for tedium, they also offer enormous potential for contributions beyond the dull, repetitive tasks. Machine learning can empower agents not only to spend more time solving knotty issues for their most important customers, but it can also free them up to spend time on more strategic projects — such as enhancing the team’s content library, discovering and fixing the root causes of customer issues to decrease future ticket volume, and relaying the customer voice to help inform engineering and product development.

Back at Pinterest, Maggie Armato recently introduced Wise Support on her customer service team. In just a few months, she was able to relieve her agents from spending too much time on simple, repetitive responses. The quicker turnaround times and more accurate answers not only improved customer satisfaction, but created extra capacity for agents to do more big-picture thinking and create team-wide improvements — making the team happier overall.

“If they have projects and problems to solve, that’s huge for people,” she says, going on to say that it makes her agents excited to learn and want to stay. “The future will be critical thinkers in support,” she says. All thanks to machine learning.

Ultimately, you and your support agents are all in this together for the good of your customers and your business. Consider how implementing machine learning can help improve the customer experience while also relieving the burden on your human agents.

Download our ThredUP Case Study to further understand how machine learning transforms customer support.

Thredup Case Study

Topics: Machine Learning, Customer Success, Customer Support