Customers Deserve Great Experiences … and So Do Your Agents

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It’s a tough time to be a customer service agent. While many customers are using self-service for simpler issues, they’re demanding more from agents to solve complex problems, which have only been exacerbated because of the pandemic. And while agents are striving to resolve sensitive cases relating to people’s health, finances, insurance, and more in the most timely and empathetic way possible, many do not have the tools to properly do their jobs.

A recent survey by Pega uncovered that more than half of customer service agents say they botch how they record customer requests during service calls, and nearly 40% admit they regularly fail to understand their customers’ needs because they get distracted. The cause? Outdated technologies that are bogging agents down with manual, cumbersome searches, and error-prone data entry. With nearly 40% of respondents citing slow resolution as a leading frustration for their customers, and a of tools to achieve a speedy, effective resolution, agents are in a tough position to get their jobs done.

It’s time to rethink the software service agents are using. We are now at an exciting inflection point in the customer service industry when tools are available to reduce the amount of manual data entry typically required of agents, while intelligently guiding them throughout customer conversations. These tools help ensure issues are quickly resolved in a way that improves interactions, rather than creates frustration.

When considering high productivity tools to improve agent experiences and in turn create happier, more loyal customers, there are four factors to consider:

Real Time Is of the Essence

Customer interactions require agents to be in the moment, so why shouldn’t the technology they’re using do the same? Eighty-seven percent of agents surveyed said the ability to immediately access knowledge centers in real time would allow them to respond to inquiries quickly and directly. When selecting a solution, it’s important to look for something that can operate in real time, as any delay in service can be the difference between a frustrated and a happy customer.

Agents need technology that offers real-time guidance as the conversation is happening. This could include anything from a prompt for what questions to ask, or a recommendation for useful information to share based on what’s being discussed. When it comes to service, every second counts, so real-time technology is critical in getting service issues quickly and effectively resolved.

AI Should Enhance Agent Experiences, Not Replace Them

Conversational AI technologies have been on the rise for a few years now. These digital technologies, including contextual self-service, intelligent virtual assistants, and interactive voice response (IVR) systems can help quickly solve service issues while reducing stress on agents. However, many times service issues still need to be escalated to a human agent, which requires a higher degree of empathy and deeper knowledge.

These conversational AI tools can now be used by agents to help enhance their jobs, not replace them. Using a combination of real-time AI, natural language processing, speech-to-text analytics, and intelligent automation, these tools can act as co-pilots alongside agents to help guide them through every interaction, surfacing new insights and guidance to achieve the best outcome possible. This helps enable agents better respond to customer needs in a way they were never able to before.

In an age of chatbots and IVR, customers are still seeking help from actual humans — especially when it comes to sensitive topics. Conversational AI — when paired with a human agent — can create powerful and effective service experiences that can turn a one-time customer into a customer for life.

Hands-free Is the Way To Be

Agents have made it very clear that some of the worst parts of their job involve manual data entry and searching for information that takes them out of the moment with the customer — frustrating the agent and customer alike. More than half of agents (54%) blame the need to switch between applications to enter customer information for what’s slowing them down, and a similar percentage (51%) are bogged down by searching for customer information.

Look for solutions that listen to live interactions and automatically enter data into the system as soon as an agent begins chatting with a customer. These solutions should also recommend service actions to take based on the conversation, while surfacing contextual knowledge so the agent knows exactly what to take and what information to offer at the moment. This should all be done without the agent lifting a finger, helping them focus on the customer instead of clunky, hard-to-navigate technology.

Reduce Training Time, Not Quality

Contact centers have notoriously high turnover rates, which means organizations face a constant influx of new agents requiring training to adhere to their brand guidelines and regulations. Instead of focusing on training programs themselves, look for solutions that offer features like real-time script adherence to help guide even the most novice employee through a customer interaction. This can take the guesswork out of service conversations by providing agents cues to resolve the issue as quickly as possible, ensuring consistent and positive experiences for both agents and customers, while also allowing organizations to focus less resources on training and more on empowering their agents to deliver excellent service.

With the technology available today, there is really no excuse for poor service anymore. If agents have the tools to do their jobs more effectively and empathetically, they can in turn create happier, more loyal customers. Customers want and deserve quality experiences, but so do agents, and the two go hand in hand.

Sabrina Atienza is director of product management, speech, at Pegasystems, joining through the acquisition of her company, Qurious. At Qurious, she served as founder and CEO, leading a team of machine learning engineers building real-time speech recognition and natural language technologies, as well as managing fundraising, recruiting, and sales. Prior to Qurious, she was a software engineer at Tealeaf (acquired by IBM) working with big data and web-scale analytics. She has been featured in media outlets such as FastCompany, WSJ, Forbes, VentureBeat, and Bloomberg, and has been recognized in Forbes’ list of 30 Under 30.

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