Contact Center AI

Rethinking the agent experience, part 1: Boost agent efficiency

CCW Digital recently conducted in-depth research for Nuance to assess how contact center leaders and agents see the state of the agent experience today. In the first of our series offering expert perspectives on the research findings, we look at why reducing agent effort is so important—and how to increase agent efficiency with AI.

Every day, your contact center agents play multiple roles as they engage with customers. They’re expected to find instant answers to inquiries—and help boost sales. They have to offer an empathetic ear to customers who are struggling to resolve an issue. And they must act as credible ambassadors for your brand in every interaction. Without the right tools and support, it can sometimes be overwhelming, leading to dips in agent efficiency, productivity, and engagement.

To understand the evolving role of the agent, and the best ways to equip them to succeed, we partnered with CCW Digital to conduct a global survey of contact center leaders and agents. In this series of posts, we’ll explore the survey results through several lenses—starting with how to empower agents to work more efficiently and deliver better business outcomes.

The barriers to an efficient contact center

One of the most valuable ways to think about increasing agent efficiency is to consider it as reducing agent effort.

Too often, agents expend effort tracking down basic customer details and product information across multiple systems. In fact, the survey revealed that the majority (57%) of agents have to access at least four separate systems to serve customers successfully, and 31% say they spend most of each customer interaction just looking up information. Worryingly, only 64% of agents say they consistently receive customer profile information when inquiries are escalated to them.

This disconnection between systems hampers agent productivity, increasing the time and effort of finding basic information to resolve simple queries. And as self-service increases and agents spend more of their working day handling complex issues, their effort—and frustration—will grow further.

It all adds up to a poor customer experience, as agents don’t immediately recognize customers and understand the context of the conversation, leading to repetitive questioning and a lot of dead air while agents search for information.

As customer engagement leaders evolve their strategies for contact center transformation—especially given today’s economic uncertainty and mandate to “do more with less”, increasing agent efficiency is one of their top priorities—not just to achieve vital cost savings, but to enhance customer satisfaction.

Increase agent efficiency with a helping hand from AI

The most obvious way to reduce agent effort with AI is to automate as many customer interactions as possible from the start. Increasingly, conversational IVRs and intelligent virtual assistants are handling the majority of routine inquiries—and the best systems are getting smarter all the time handling the most complex of transactions. But it’s when automated and human-assisted support work together that we see the true potential of AI in the contact center.

AI-powered customer engagement platforms understand customer intent and use intelligent routing and contextual transfers to escalate inquiries to the most appropriate agent, passing on the full context of the conversation. And as the agent begins to engage with the customer, AI is waiting in the background to help.

With an AI coach backing them up, agents can become hyper-efficient and deliver standout customer experiences in the moments that matter. Nuance Agent Coach, for example, monitors customer conversations and gives agents real-time insights, best-practice guidance, and recommendations to streamline engagements and reduce average handle times (AHT).

But perhaps even more importantly, Agent Coach gives agents more confidence. They have easy access to all the customer insights and product information they need, along with next best action recommendations based on your top-performing agents’ responses. The survey revealed that currently only 30% of agents have next best actions automatically surfaced, which means 70% are left to figure it out for themselves.

With AI guidance, however, every agent—even new hires—can breeze through simpler inquiries and focus on applying their empathy and creative problem-solving to more complex problems. Even better, they can also sell with confidence, as Agent Coach provides targeted cross-sell and upsell recommendations during the conversation.

Unify data and systems on a single cloud platform

Like all our intelligent customer engagement solutions, Agent Coach is part of the Microsoft Digital Contact Center Platform, to bring  together the right information, people, and insights directly into agents’ workflows.

This gives agents a comprehensive view of each customer and their journey across channels, and instant access to relevant articles held in different knowledgebases. Close integration with Microsoft innovations also enables agents to collaborate with experts throughout the organization with a single click, helping resolve complicated issues quickly and effectively.

Next time: improving agent satisfaction and retention

In the next article in this series, we’ll examine the survey results through the lens of agent retention. We’ll explore how AI can help make agents’ jobs more satisfying and rewarding—and reduce the high employee attrition rates that ramp up contact center costs and directly impact customer experience.

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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.