AI and the Rise of the Contact Center Super-Agent

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Jeff Epstein

Working in a call center isn’t an easy job. Call center agents often bear the brunt of customers’ frustration when something has gone wrong, field high volumes of routine, repetitive questions about things like package arrival times and account balances and are often faced with high turnover in their departments, creating a lack of continuity and stability. Couple these factors with a fear that companies might use AI to automate the contact center, and it’s no wonder agents are stressed.

But there’s good news: despite early concerns that AI would replace human contact center agents, we’re seeing that the opposite is true: the most significant improvements come when AI and humans work together. Not only is AI making agents’ lives better and creating more job satisfaction, but it has led to the rise of the “Super-agent” — a human-AI hybrid that is better positioned than ever before to get customers the answers and assistance they need, quickly, accurately and on any channel.

Improved Agent Morale

Companies looking to provide the best possible customer experience should also be focusing on the best possible agent experience. With a turnover rate of upwards of 49 percent for some, it can be difficult to recruit and retain the best agents — and when your best agents leave, so does their wealth of experience and knowledge, preventing it from being passed on to the more inexperienced staff that’s left.

A key part of improving the agent experience is through creating more manageable workloads to reduce stress levels. Enabling an AI-powered chatbot to field the more straightforward, repetitive customer questions — such as questions about order status, shipping times, product availability or account balances — allows agents to devote their time to more complex customer issues, challenging them to hone their customer service skills and creating a more engaged, satisfied workforce.

Agent-facing AI can also help agents get the training they need to learn quickly, whether they’re brand new to the team or a seasoned agent learning a new product, without turning to colleagues or supervisors. These AI-powered assistants can push the most relevant resources to the agent based on the conversation, providing them with the opportunity to learn and develop expertise in real time without pausing an interaction. According to a Robert Half report, creating a strong learning culture correlates with high retention rates, which in turn fosters a more rewarding working environment for agents, who are the heroes of customer service.

The Rise of the Smarter, More Productive Agent

Customers’ service expectations are high. According to Salesforce, 76 percent of customers think companies should understand their expectations and needs, and Accenture found that one third of customers who ended their relationship with a company did so because their experience wasn’t personalized enough. Companies collect vast amounts of data on each customer, giving agents more personalizing power than ever before — but finding and understanding all that information quickly enough to have an informed, tailored conversation with a customer can be a daunting, if not impossible, task.

That’s where AI-powered agent assistants come in: aside from helping customers get answers faster, agent-facing AI can be the digital assistant “sitting” on the agent’s shoulder, providing multiple benefits. Agent-facing AI can “listen in” on conversations, suggesting responses and resources for the agent to pass on to the customer or taking on common service requests that require agents to gather data or process a transaction. The assistant can complete those tasks for the agent, who can take back control of the conversation once the task is complete. Leveraging AI in this way also allows organizations to design customer engagement journeys that leverage the right type of agent at the right time, AI for data collection and routine workflows described above, and humans for more nuanced conversations and relationship building.

Agent-facing AI can start assisting an agent immediately when a customer engages, gathering some preliminary information about the customer so that agents come into the conversation informed with historical data from the company’s CRM system on previous interactions with that particular customer. This ability to reference previous interactions is especially important as customer service becomes truly omnichannel. Being aware of a previous conversation that a customer had with the brand on Twitter when that customer calls or emails is key to heading off any frustration that the customer might feel at needing to repeat themselves. More than half of all customers say they have to re-explain their issues when they call for help or for an answer, according to Salesforce, which means that agents are re-collecting information that already lives somewhere in the company’s system — time and effort that could be better spent helping solve the problem in the first place. It might also suggest a different protocol: if a customer has reached out with a similar issue on multiple channels previously, the system can flag that customer as high priority if they reach out again.

The Super-agent is much more than a personalization machine, though; beyond just deeper knowledge of a customer’s history, Super-agents have faster, more reliable access to all the company’s help resources at their fingertips. Thanks to agent-facing AI plugged into all of the help databases a company has, the agent doesn’t need to rely on his or her knowledge of where certain resources are, or have those resource memorized; the agent just has to ask the AI assistant, or have it “listen” to the conversation and suggest responses.

Companies know that good customer experience is a business imperative, not merely a nice-to-have — but that good experience starts with productive, engaged agents. When agents are happy and equipped with the resources they need to truly do their jobs well, customers receive more personalized experiences and the contact center continues to meet their KPIs, both in terms of the chat volume they can handle and the quality of their outputs. The AI call center revolution is here, and it comes with an agent superhero cape.



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