Contact Center AI

Rethinking the agent experience, part 2: Increase agent satisfaction

A man working in an office, talking into a headset.

In the second article in our series on rethinking the agent experience, we focus on employee retention and how AI can improve agent satisfaction and reduce the costs associated with high workforce turnover.

In a world where doing more with less is a growing strategic priority, contact center leaders are under pressure to reduce agent churn. McKinsey estimates that attrition costs contact centers $10,000 to $20,000 per agent. That means if your contact center with 1000 agents has a 10% churn rate, it could have a $2M impact on your bottom line. That’s why it’s imperative that leaders take action to increase agent satisfaction and keep experienced, knowledgeable employees in the organization for longer.

One of the key findings in our recent survey of contact center leaders and agents, conducted by CCW Digital, was the overwhelming scale of the agent attrition problem. Two-thirds of contact centers have annual employee turnover of 20-40%, and more than a quarter are seeing turnover of 40% or more.

In the past, high churn rates have led to the belief that agents don’t see a long-term career path in the contact center. Interestingly, the survey results show this isn’t the case; most agents don’t see their role as a dead-end job. Only 11% of agents say they don’t see a future in their role or a path toward career development.

So if it’s not a lack of career prospects that’s the problem, why do so many agents leave? And how can AI help contact centers increase agent retention?

The problem: mundane tasks make the working day dull and repetitive

One of the key factors that limit agents’ job satisfaction is the amount of time they spend handling routine inquiries and completing mundane admin tasks. Often, agents read through the same scripts time after time as they process returns requests and account balance inquiries. Then they have the tedious task of completing post-call admin. Before too long, the repetitive nature of an agent’s workload can wear even the most committed employee down.

When an earlier CCW Digital market study asked respondents to name the most urgent ways that AI should improve the agent experience, the answers were revealing. Nearly two-thirds chose “Empowering self-service so agents can focus on more complex conversations.” And two-fifths of respondents selected “Handling rote back-office/admin tasks so agents can focus on customer interactions.”

The solution: have AI handle routine tasks

Conversational IVRs and intelligent virtual assistants can now understand a huge number of customer intents and quickly resolve common inquiries in self-service channels. We typically find that organizations can automate at least 80% of interactions by taking an AI-first approach to customer engagement.

Ramping up automation allows agents to spend more of their time solving intriguing problems instead of just reading scripts. That makes their job more rewarding, but it also means they need more real-time support than they typically get, as we saw in the first article in this series.

What’s more, with Nuance Mix Builder—a new GPT-powered Copilot feature in our conversational AI tooling platform—creating chatbots will become much faster and easier. That will allow organizations to quickly increase automation and free up agents to focus on applying their skills in high-vlaue interactions.

Nuance AI-powered engagement solutions also use a continuous learning loop to make automated systems smarter over time. When conversations are escalated to a human agent, the AI learns how the agent resolves the issue, helping it understand more intents and further increase self-service containment.

And as for that tedious post-call work? AI can help there, too. Nuance Agent Wrap-up, for example, uses AI-powered speech recognition to dramatically reduce the time and hassle of completing routine documentation. Instead of typing, agents can simply dictate their notes directly into the CRM, and use Auto-Texts to insert repeatable blocks of text with a single utterance.

The problem: a lack of training and managerial support damages agent satisfaction

As the role of agents evolves from reading scripts and processing mundane transactions to engaging customers with complex problems, effective training and coaching will become even more important.

With many contact centers now operating a fully remote or hybrid working model, identifying training needs and coaching opportunities can be challenging. Remote workers, separated from the support of colleagues and supervisors seated nearby, are heavily reliant on their own expertise and knowledge.

The solution: use AI to coach agents and empower managers

AI-powered solutions have an important role to play here. Tools like Nuance Agent Coach can provide real-time guidance and proactively surface relevant knowledge and next best action/response, so even new hires can support customers confidently from day one. And analytics connected to supervisor desktops can alert managers when individual agents need additional support and automatically identify specific training needs across the agent population.

The bad news is that the survey found that only 23% of contact centers are using AI for training and development. But the good news is that there’s a huge opportunity for organizations to differentiate by using AI to provide real-time, personalized training and coaching, and build an engaged, high-performing workforce that delivers better customer experiences—and better business outcomes.

Up next: removing agents’ authentication burden with AI

Another repetitive, routine task that frustrates agents and customers is authentication. In the next article in this series, we’ll look at the problems with agents’ current role in authentication and how AI-powered solutions can enhance security while boosting customer and agent satisfaction.

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Tony Lorentzen

About Tony Lorentzen

Tony has more than 25 years of experience in the technology sector, spending the last 17 with Nuance where he is currently the SVP of Intelligent Engagement Solutions within the Enterprise Division. Before that he served as the leader of several teams at Nuance including Sales Engineering, Business Consulting, and Product Management. A proven leader in working with the cross-functional teams, Tony blends his in-depth knowledge of business management, technology and vertical domain expertise to bring Nuance’s solutions to the Enterprise market, partnering with customers to ensure implementations drive true ROI. Prior to Nuance, Tony spent time at Lucent and Verizon where he led teams that applied the latest technologies to solve complex business issues for large enterprises. Tony received a B.S. from Villanova University and a MBA from Dowling College.