As chatbots, artificial intelligence (AI) applications and social media drive the growth of self-service customer engagement, it’s clear the role of the contact center is changing and will continue to do so. According to Forrester, “Companies that master the interplay between AI, automation and human relationships will dominate their industries.”
Where does customer experience (CX) fit into the changing landscape? At first glance, it might seem that all this automation is making life easier for contact center agents and customers. But is it really improving the customer experience? The answer is an emphatic yes—as long as organizations follow a few key guidelines in the rush to offer a wider range of self-service options to their customers.
1. Put Customer Goals First
Some organizations view first contact resolution (FCR) as the ultimate measure of effective customer engagement, and cheer when their FCR rates go up with increased automation. But look again. FCR might measure operational efficiency, but it might not be a true reflection of customer satisfaction.
Many first contacts are falsely closed before issues are fully resolved. Just because a customer doesn’t hang up prematurely or doesn’t request escalation to an agent doesn’t necessarily mean the customer got what he/she needed. Customer satisfaction can actually drop with FCR as a prime metric; and frustration might increase with the number of callbacks as customers try to get the help they need.
A better approach is to focus on goal completion or issue resolution. Are you able to help customers achieve what they want to when they first contact you? Intelligent tools are available today to provide valuable guidance as you work to improve both assisted and unassisted customer interactions with your company.
Analytics tools ingest data from assisted service interactions—live chat logs, for example, or recorded and transcribed calls. They analyze the data to identify customer goals or intents, match them with tasks that are capable of being automated, and then pass them on to a virtual assistant for automation. This is information that can help you prioritize the interactions to automate and thus improve self-service.
You can also identify intents that are failing in automation and escalating to live agents, so you can improve how automation is recognizing and handling certain goals. It might be a problem with how the intent is identified, or how it’s mapped to the next action. Solving that problem improves both automated and assisted service by reducing the load on agents and letting them focus on resolving problems that can’t be automated. It’s a good example of why it is important to look at the entire customer journey as it crosses self-service and assisted service.
2. Use New Tools to Bring Self-Service to Life
Verint and Opinium Research have conducted global consumer studies that raise some interesting points about customer preferences for interacting with companies—and how those preferences have changed in recent years. While results of the new 2018 study show that most consumers value human interaction and want it to remain a part of customer service equation, especially when complex requests are involved, nearly two-thirds of respondents (63%) are happy to be served by a chatbot if they have the option to escalate the conversation to a human when needed. In fact, 41% said they cannot tell the difference whether they are being served by a chatbot or a human behind the screen.
What do these findings mean for today’s contact centers? The door is open for companies to implement more self-service options for customers. In the era of Google, consumers are far more comfortable interacting with machines in a conversational way to get the answers they need, unassisted by another human, and smart companies are taking advantage of this shift. The big question: How to do it right?
Technology is available today that brings self-service to life. Virtual assistant solutions gather contextual information to provide personalized answers based on a customer’s prior purchases, location and other factors. Natural language technology makes it possible for customers—through natural conversation in voice or text—to access the information they need and conduct transactions without the assistance of an employee. They are no longer lost in the seemingly endless limbo of the automated phone system.
An example of old and new… New self-service technology is like a super-employee—highly trained, perfectly informed and consistent, mindful of what the customer wants, and it can be everywhere at once, on any channel. Customers can simply talk or type questions as if they are speaking with a person. The technology figures out what they want and takes the best next action to achieve their goals quickly. Virtual assistants are to traditional interactive voice response (IVR) systems what laptops are to typewriters.
Consider the following scenario showing the differences between the old-school approach to automation and today’s modern one… Miranda is closing on a new house tomorrow, but she just learned that closing costs are going to be much higher than expected. She might need to make a withdrawal from her IRA, but first, she needs some answers. Miranda takes out her smartphone and opens her bank’s mobile app. She taps through a few dozen FAQs and finds answers to some related questions, but nothing matches her situation exactly. So, she calls customer service and gets a recording, then immediately zeroes out to speak with an agent—only to be put on hold.
With today’s latest self-service tools, however, Miranda could have a very different experience. She could open a virtual assistant from right inside her bank’s mobile app. She could tap her question in plain language and get the best answer selected from thousands of entries in the bank’s knowledge base. If she still has questions, she can reach a virtual assistant by phone. It will recognize that she was recently searching for answers about IRA withdrawals and ask some clarifying questions to quickly find the right answer.
3. Make It Seamless
As mentioned earlier, new global consumer research shows customer preference for human assistance when they have a complex transaction or question. While that preference will probably never change, what is changing is the definition of complexity. As shown in the example above, new automation tools make it possible for some very complex requests to be handled by virtual assistants. As technology advances, those capabilities will undoubtedly increase, while still leaving behind a field of inquiries that require human intervention.
The challenge is having a platform that enables customers to transition seamlessly from their self-service session to an assisted service interaction on phone, email, chat or social media without losing the context of their self-service session. New tools are available that make this seamless transition possible. So Miranda, in the above example, won’t have to start from square one providing the history of her request if she does need to speak to an agent. Her story will follow her every step of the way.
4. Build Trust
There’s one final key to making self-service successful: trust. Customers want to know that you are in their corner, that you value their time, that you understand their needs and that you’re doing everything you can to make it easy to do business together. It’s the reason self-service can be such a valuable tool in a company’s CX toolkit when done correctly.
That’s why CX professionals should be involved in every enterprise self-service automation project. Of course, your business goals will include handling greater contact volume with the same number of agents, reducing cost per contact and achieving higher self-service utilization across all intelligent channels for a lower escalation rate. But increases in CX ratings should also be top on the list of the returns you expect from your automation investment.