WHY CALL CENTER AGENTS ARE NOT ROBOTS BUT HUMANS?
Call center agents, at their full potential, might have been regarded as robots because of their proficiency in speaking, evident in their tone, diction, and fluency of the call. But for a disclaimer, they are not robots! They are humans designed to be very good at communicating with their customers. They only use AI as their convenient right hand. Here’s why:
They are only using scripts for reference
Can they mock their potential client to the core of their being? Probably not. Customers feel mocked when they blather on incessantly without allowing them to express their issues. Scripts should only be used as a guide and a source of reference in the event that a customer asks a question about which they are unaware. They may easily do fast referencing with call center scripting tools. This fantastic solution also integrates with CRM call center software to provide them with crucial data and reports about the potential customer. They can be aware of any inbound calls directed to them in a matter of seconds in this manner.
They have empathy towards their customers while using Call Center Scripting Software
Even if their call center serves a million or more customers, the millionth consumer wants to feel like she or he is a part of the firm, just like the rest. Call center scripting software was designed to help them handle all clients with ease, regardless of their status or origin. That was then; today's customers are far more complex, and a single customer service agent's error can quickly tarnish their company's reputation.
While scripts are important, use call center reporting software in conjunction with them to provide a constant flow of information to the customer and prevent repeating the script exactly. Examine how prior clients with similar problems were helped in the reports to build a relationship with the customer. Moreover, use this call center reporting software tool to create personalized info about the client so that when he calls another time, other agents can readily know the kind of person he/she is.
They focus on the quality of calls rather than the number of calls
Many agent supervisors make the mistake of evaluating agents based on how many calls they can handle each hour. Agents should be evaluated based on the number of quality responses and assistance they provide to clients. The majority of call center phone systems come with open source call center recording software that records customer-agent talks. Disclaimer: Be aware of the rules and regulations in your area of operation that govern client privacy.
Business culture is being cultivated into the heart of every agent
The term "business culture" has a wide range of interpretations, but it often refers to a company's underlying principles and goals. Their products and brands are carbon copies of their culture. As a result, clients who find their brands appealing will undoubtedly enjoy the company's culture. When customers are enthusiastic about their culture, don't let them down by reading the scripts in a way that makes them reconsider their loyalty to your company. Agents are trained and cultivated with the core philosophy behind the business.
CALL CENTER AGENTS’ COLLABORATION WITH ALTERNATIVE INTELLIGENCE
How would you know if you're chatting with a human agent or a bot?
Agents don’t ploy empathy
Emotions between people are extremely difficult to understand and describe, and we feel that today's level of AI lacks cognitive empathy. As a result, purposefully engaging in a sympathetic conversation with your human or AI/chatbot might be eye-opening. The Empathy Ploy demands you to take an emotional stance and communicate with the human or AI/chatbot on an emotional level. Either interaction can be beneficial, but it's easier to tell if you're interacting with a human or an AI/chatbot right away. We are not ready for AI therapists as a culture.
Agents can’t be dissociated
Any data can be accessed by a linked AI at any time and from any location. Simply ask Alexa. As a result, a relevant challenge question over chat cannot be one for which the answer is stored in a database. There are two factors required for the Two-Step Disassociation (thus the name): a. Make an assumption that the AI/chatbot is unlikely to be able to relate to; and b. Pose a question that is connected to that premise.
Agents don’t have a circular logic
This is all too familiar to programmers, but it can help us in our game of identifying human vs. AI/chatbot. So in order to determine if it is a bot, we must know if there are recurring patterns of responses to build a circular logic test. For instance, the predicted delivery date would not have been repeated by a human person or a wiser AI/chatbot. Instead, s/he or it would have said something like, "Let me check with the carrier about the delivery status." Please wait a moment."
Humans are way more logical about ethical Dilemma
This is a significant difficulty for AI developers and, by extension, AI/bots. What does the AI do if the outcome is A or B? Consider the rise of semi- and fully-autonomous self-driving vehicles. Which is the better course of action when faced with the choice of hitting the dog crossing in front of the automobile or swerving into the car next to us? humans are way more logical with that and have the tendency to significantly pose an aggressive appeal.
The Kobayashi Maru is similar to the Ethical Dilemma in that it has no positive viable result. It's not a bad/better decision scenario: it's a fail/fail scenario. Only use this in the most desperate of UI/bot challenges after all other options have failed.
How is AI being used for customer services?
While AI is still in its early stages, its capacity to cut operational costs, personalize the customer experience, deliver actionable information, and improve customer agent efficiency are just a few of the ways it can revolutionize the way customer service organizations operate today. In fact, executives claim that the most significant motivation for implementing AI is to improve customer experience (53 %).
The following are the 6 ways in how Artificial intelligence (AI) is being used in call centers:
Through Call Routing Prediction
This technology relies on customer behavior profiles to give AI technology a comprehensive understanding of the customer journey and customer personas. Meaning customer service (and the customer experience overall) can be hyper-personalized to each customer. The software will analyze natural tendencies and communication habits to match each query with the best-equipped agents to handle specific types of customers and queries (based on personality, communication style, and call history), ensuring that tickets are closed quickly and effectively to free up time across the board. To get started with AI, firms must first develop criteria for determining the personality traits of specific agents, average ticket time, and competence on specific subjects.
Through IVR or the Interactive Voice Response
Most of us have interacted with interactive voice response (IVR) during our customer support interactions. This is when you respond to recorded questions such as your native language, name, account number, and so on. It's true that many of us dislike this type of AI because we've had calls where we had to repeat the information. This technology, on the other hand, continues to advance. Humana and IBM's Data and AI Expert Labs collaborated on a solution that allowed the life insurance business to route 60% of its over 1 million monthly calls to AI with predefined responses. This type of IVR is for firms that receive a lot of inquiries concerning routine, particular pre-service questions that don't require a human call center operator, such as hours, eligibility, copay, or bank statement information.
Through Conversational AI
Nowadays, conversational AI is commonly referred to as chatbots. This is when an AI-powered online chat option is available at a call center. And it's a vital type of customer service, given that 85 percent of consumers want to message businesses, up from 65 percent last year. As you can see, chatbots have become one of the most popular ways for customers to contact customer support. Customers can interact with website material and self-service support choices in a live environment without having to meet with a service representative, giving them the ability to address problems on their own time and reducing the pressure on service teams. Chatbots' strongest feature is their capacity to minimize call volume, allowing call center operators to focus on more difficult issues rather than basic, repetitive questions.
Through Emotional Intelligence AI
Emotional intelligence AI, which can track client sentiment during a phone contact, is another type of artificial intelligence used in call centers. When a consumer gets angry, for example, their voice may rise or there may be a long pause in the conversation. This sort of AI is trained in a variety of languages and cultural situations, making it adaptable to a variety of linguistic and cultural approaches. It can detect the caller's mood by analyzing the tone of voice and linguistic cadence. This AI will also track how many times an agent interrupts a customer and the tone of both the consumer and the support representative's voice, and it will provide immediate feedback (through popup messages) to the agent so that they can understand how the customer is feeling during the call.
Through AI-Powered Recommendations
Other AI tools, like the emotional intelligence AI mentioned above, can make recommendations to a customer service representative during a call. Sentiment analysis is also used by this technology to figure out what a customer is trying to accomplish. It can then make recommendations to the support representative for the best options. This shortens call times and gives customers a more tailored and pleasant experience. The technology can determine how many times a consumer has called or mentioned canceling their account, and then assign that customer a risk score so that agents are informed of the situation throughout the conversation.
Through Call Analytics
In Call centers, one of the most common uses of AI is to give in-depth data on-call times, first resolution, and other metrics. These technologies can detect patterns and have access to client data, allowing them to determine if customers are having a good or bad experience. AI can deliver more comprehensive statistics than a human customer service manager since it measures client sentiment, tone, and personality. Now that we've talked about how AI is utilized in contact centers, you might be thinking, "How will AI affect my customer service team? Will it replace call center agents?" Let's take a look at that.
The Future of AI-Call Center Collaboration
Call centers have changed dramatically in a short period of time. Omnichannel customer care has evolved from agents merely answering client phone calls to a variety of other customer interaction channels such as web calls, live chat, and video chat. Call centers are expected to experience even more changes in the coming years as the technology becomes a more dominating aspect in customer service. We examine the future of contact centers, from the Internet of things to the changing role of agents.
Prediction of the Changes to Come
The Hybrid Model
Call centers have become a hybrid of customer contact channels, and the future of call centers will see an increased hybrid setting - a mix of human agents and Artificial Intelligence (AI). Artificial Intelligence (AI) will become cheaper to deploy, more efficient, and more accurate as it becomes more advanced, providing several benefits to call centers in terms of productivity and cost.
AI can assist in providing a completely smooth customer experience, and more and more companies are beginning to use AI-powered customer service. As a result, the future of call centers will necessitate a combination of AI and human engagement. With technologies like AI chatbots dealing with FAQs and easy client concerns, the hybrid model will see automation and self-service rise to boost productivity.
Meanwhile, human agents are freed up to deal with more complicated queries and problem-solving, still providing personalized and human-centered customer service when needed.
There will be more live Chat
Live chat has become the most common consumer communication medium in the previous ten years. Over 40% of customers prefer to contact a firm via live chat over email or social media, and 41% of customers expect a website to have live chat as a contact option.
With a satisfaction percentage of 73 percent, live chat is also the most popular customer contact channel, with only 44 percent choosing phone calls! Furthermore, it is an excellent technique for considerably increasing lead generation.
Chatbots, on the other hand, will not be able to replace live chat due to specific constraints. Future call centers will adopt a hybrid model of live chat, as previously mentioned: chatbots will answer FAQs and easy queries, with the flexibility to transfer off to an agent when faced with difficult issues.
Video Chats with customers will be feasible
Support via video chat takes live chat to the next level. While it has all of the advantages of live chat, such as greater customer satisfaction and leads and sales, it also provides a more personalized experience.
Agents can not only have face-to-face conversations with customers, but they can also demonstrate their products and services. This aids in bringing the in-store experience online, which has grown in popularity since Covid-19 forced the closure of numerous brick-and-mortar establishments.
Right now, video chat software is undergoing a lot of development. For example, the talkative video chat feature has just been updated to include support for iPhones as well as the option to screen share and go full screen. We expect future call centers to make considerably more use of video chat as the technology improves.
Call centers can be mobile
Customers interact with businesses mostly through their mobile phones. In 2018, mobile and tablet devices accounted for 58 percent of online traffic in the United States, compared to 42 percent for desktops.
This doesn't mean that mobile is taking over from desktop (total time spent on websites is still higher on desktops), but it does indicate that firms must pay equal attention to their mobile profiles. Allowing consumers to multitask on their mobile while using a contact channel, much like they can on a PC, will be a crucial feature of call center mobile capability. For instance, when using live chat, you could be able to view multiple online pages.
Mobile compatibility is growing, as is the use of mobile apps for customer care. Mobile apps are expected to become a highly important consumer interaction channel in the future of call centers due to high levels of client involvement.
The Application of the Internet of Things
The Internet of Things (IoT) refers to internet-connected objects that can communicate with one another. "The Internet of Things is made up of devices - from simple sensors to smartphones and wearables - networked together," says techUK's CEO.
This interconnectedness of devices opens the door to proactive customer assistance in the future of contact cente