It's trite to say that happier customer service agents mean happier customers and shareholders. But it's true. Happier agents perform better, are more productive, and stay in their jobs longer, which helps with turnover, one of the costlier factors in managing customer service operations. Yet, as contact centers automate more work and deflect more of the straightforward inquiries, agents have to solve the harder issues. They also have to be empathetic and emotionally resonant with customers.
Agents who can do it all are called superagents. They are highly skilled and better compensated than lower-tiered agents. They might even have revenue goals they have to meet. And this job function becomes appealing to Gen Zers who are just entering the workforce. This generation brings expectations for consumer-grade technologies that help them be more productive and focus on work that matters. They want to make an impact to customers. They have come of age constantly learning and adapting to new technology.
Customer service organizations staffed with superagents have a greater need for effective, modern technology to empower them to understand the customer, arm them with the right knowledge, and focus them on work that matters. Because if you don't give agents the right technology to help them be successful at their jobs, they will leave.
Today, organizations manually knit agent desktops together from a range of technology components to make operations smarter and more streamlined so they can provide better customer service experiences. But customer service managers don't always have clear road maps on how or in which order to adopt these technologies and understand their additive value. These are the problems that I commonly see that must be addressed with modern agent technologies, and here is what to do about them:
Problem 1: Agents don't have enough context about your customers and their interactions. Many customers are authenticated on a website when they call customer service. Contact center managers know which channels customers use before reaching out to the contact center; they just aren't doing anything about it. Not only do agents not have visibility into these customer interactions, but they also frustrate customers by asking for data that they have already provided.
What to do: Make sure you pop customer information, such as their value, health and context, to your agents. You can even surface data like household information, life events or conversational style to your agents. This data helps agents personalize interactions and guides them to the right next steps.
Problem 2: Agents don't have the right knowledge and data. Agents spend an inordinate amount of time searching for the right information from a knowledge base or CRM system. They wade through interaction logs to understand recent conversations. They don't understand which products customers have bought or their value to the company. They can't use customer knowledge to personalize interactions and keep customers happy.
What to do: Make sure you integrate knowledge management into your agent desktop. Pass customer and inquiry details into your knowledge base search so you can proactively surface relevant content to the agent. Add automation to classify cases or auto-fill case forms. Explore generative artificial intelligence to automatically summarize customer history so agents can quickly come up to speed.
Problem 3: The agent desktop has too many applications. Customer service agents use dozens of disconnected applications in the course of resolving a single customer issue, often duplicating data from application to application or performing repetitive, manual tasks. These actions that can take up 15 percent of an agent's day. Managers can't enforce standardized processes. Agents take a long time to get trained on processes and applications, and their frustration with their tool sets causes them to turn over quickly.
What to do: Start with a modern customer service agent solution that provides omnichannel inquiry capture and workflow and integrated knowledge management. Layer on efficiency tools, such as robotic process automation or digital process automation. Follow with solutions to make service more effective, such as cognitive search, agent-facing chatbots, and agent collaboration.
Problem 4: Agents aren't adequately skilled. As self-service technologies get better, contact center agents handle harder issues from more frustrated and anxious customers. Agents spend more than 10 percent of their workdays reaching out to subject-matter experts and leads for help. Managers struggle to train and coach their employees to handle the technically and emotionally more complex interactions. Yet, these interactions, if done well, are rare moments in an increasingly digital-first world where companies can directly connect with customers to nurture and strengthen relationships.
What to do: Agents don't have time to take day-long or even hour-long training classes. Learning needs to evolve to be continuous to keep up with new product introductions or emerging issues. How do you recommend the right training? Speech and text analytics can continuously monitor and score customer outcomes. Quality scores drive just-in-time coaching on specific subjects that could be only minutes long. And training is surfaced right in the agent desktop.
Kate Leggett is a vice president and principal analyst at Forrester Research.