Efficient customer service is crucial to the success of client-facing businesses. The $350 billion industry has transformed over the last couple of decades with the mass adoption of the internet and social media, taking the customer service channels for many businesses online. Although the increased connectivity provided by technology has helped facilitate customer service processes, it has also increased customer expectations.
To keep up with these expectations, businesses are finding ways to implement machine learning into their customer service processes in hopes of efficiently handling as many customer inquiries as possible.
Customer Service Needs
Although the internet can often provide answers to almost any question a customer could have, customers more comfortable speaking directly with a person will often reach out to customer service agents. This frequently results in customer service representatives spending large amounts of time answering very basic queries, which can be monotonous and frustrating for agents. To reduce the need for customer service reps to answer these types of questions, businesses have been using AI to offer answers for basic questions before transferring clients to a customer service agent.
This is done both on the phone and online through the use of chatbots that are often employed on a business’ website and Facebook page. Over the phone, automated recordings help navigate customer calls by asking questions that the AI will either be able to answer or transferring their call to the proper department.
Online, chatbots have become a huge resource for businesses to attain customer information, gather feedback, and provide customers with quick responses to standard questions. The use of chatbots and other forms of AI is expected to help businesses manage 85 percent of their relationships with customers by 2020.
Machine learning also facilitates security processes for businesses that handle sensitive customer information. In the past, customers have been required to verify their identity by providing personal information, a process that could take many minutes, especially if a customer forgot their answers to security questions.
However, many businesses are now using two-factor authentication to verify customer identity during customer service calls. This involves verifying two pieces of information: a security question, followed by phone verification. Customer service agents will use machine learning to send a code to the phone number on file with the company, and once a customer verifies they received the code, their identity is confirmed. This approach has improved security measures and can be completed quickly.
Growing Use of Tech in Customer Service
Overall, the use of AI in customer service has increased job satisfaction for customer service agents, as well as help businesses keep up with customer expectations. Businesses need to constantly look for ways to improve customer service. One of the results of implementing AI to help facilitate customer service has been giving customer service agents more time to handle complicated customer inquiries. Increased job satisfaction for customer service representatives and reduced call volume provides them with a greater opportunity to dedicate time and empathy to customers who need a human touch for their inquiries.
As more businesses use machine learning to automate routine tasks and data entry during customer service calls, call time should be reduced, leading to an increase in customer satisfaction. Currently, in a typical six-minute customer service call, 75 percent of that time is devoted to agents doing manual research. Only 25 percent of call time is spent interacting with the customer. AI can streamline this process by memorizing customer information and creating easier routes to accomplish tasks online.
This also provides customer service agents with more time to do important customer service work online, such as responding to customer reviews, which has become a high priority for businesses over the last few years.
As more customers go online to offer feedback or complain about poor experiences with companies, the need to moderate reviews and comments has grown. In the internet age, 88 percent of consumers trust online reviews as much as personal recommendations. Therefore, if a business receives many reviews, they must dedicate resources to responding to them. This will increase customer trust in a business, as well as its ranking with Google.
As more businesses implement AI, machine learning will become the standard for customer service expectations. Although the impact AI will have on jobs within the customer service industry is unclear, the new and rapidly advancing technology will soon provide efficient customer service to consumers looking for help. AI will also help improve the job environment for customer service representatives and open the door for better customer service and increased customer satisfaction. With the implementation of machine learning, the future of customer service looks to be promising.