Call centers in Asia are the backbone of customer care operations. Since AI and machine learning entered the competition, the call center industry has experienced a massive change. Call centers are getting better with the help of AI, which is changing how operators engage with consumers and making problem-solving much easier. 

A contact center’s most challenging objective is providing high-quality assistance to every customer who calls. But the good news is that contact centers are becoming increasingly efficient. The credit goes to generative artificial intelligence and machine learning. 

In 2023, automation was seen as the top priority by 91% of call center leaders. Brands must adopt new AI solutions in call centers to better shape customer service automation and customization. However, if you are still unsure about AI and machine learning, we have got you covered!

In this post, we’ll look at how AI and ML will set the future of call centers in Asia. We will discuss how AI is bringing evolution to Asian brands and reshaping their future!

Inside Call Centers – the Evolution of AI in Asia

The evolution of AI in Asian call centers can be broken down into these phases:

1. From Human Agents To Virtual Agents – Call Routing

Call routing was a technique that was performed manually before the advent of AI. The operators would physically link calls using switchboards. Later, they would guide the calls to the right endpoint based on the requests made by the customers. The process needed a lot of manual work, often leading to lengthy waiting and more mistakes. 

Now that we live in the digital age, intelligent call-routing systems have emerged. These used data and formulas to make decisions right away. To get as many calls as possible, these systems look at the time of day, the number of available agents, and the caller’s past. 

However, the addition of AI has made them more powerful. AI is capable of analyzing great amounts of data in real-time, making predictions about which agent would be most suitable for a specific client or query, and optimizing the allocation of resources. 

Natural Language Processing (NLP) and Machine Learning (ML) techniques enable virtual agents, chatbots, or conversational AI to fully understand and react to client inquiries in real-time. Intelligent chatbots like this save customers the trouble of waiting in line for hours and free up human agents to tackle inquiries that truly require human expertise.

2. Handling Calls Manually Vs. Automatically – Get Tickets Organized

Asian companies now use sentiment analysis and natural language processing (NLP) to automatically identify and tag tickets, assigning them to the relevant agent and support phase based on predefined rules. 

One big advantage of using AI to automate ticketing versus manual organizing is that it helps companies extend their support as they grow. Another one is that it cuts agents’ time spent on repetitive, low-impact duties. As a result, customer service agents are able to work on more vital challenges rather than answering basic or repeating queries. 

Using analytics, AI can learn from its mistakes and bring improvements in its operation with time. Artificial intelligence ticketing can adapt to evolving resolution procedures by categorizing and labeling conversations, allocating tickets, and keeping agents informed.

3. From Manual to AI-assisted QA and Voice Analytics

For quality assurance and performance evaluations, call center agents used to have to listen to agents’ whole call recordings. These days, AI-powered speech analytics technologies may review transcripts and recordings of calls to expedite this laborious process by recommending whether the agent met the criteria of the QA scorecard.

Moreover, AI can perform this immediately for all of an agent’s calls, eliminating the need for a supervisor to select calls to review randomly. This also decreases the likelihood of an unfair QA review caused by management selecting a particularly poor call randomly.

5 Ways to Enhance Call Center Experience in Asia – AI and Machine Learning

Applying AI and ML correctly can bring practical insights, boost agent proficiency, and decrease overhead expenses. You can get various beneficial results by using the two in different ways. 

For a more promising future, this might help Asian businesses in the following manner:

1. Customized Experience

Calls based on AI are just the start of a process that will give users a more personalized experience and better services. Second, there’s customer relationship management (CRM), which keeps track of and evaluates what a business does about its present and future clients. You may exceed your clients’ expectations with personalized care when you have a well-equipped CRM with AI call routing. 

This approach leverages analytics on client history data to strengthen commercial ties with them, focusing on retaining clients and growing revenue volume. Customer purchases, behavior histories, ads, and other topics could be linked to data. It begins with different entry points, like the company’s online presence, social media accounts, phone numbers, or email.

Take Alibaba as an example:

The recommendation systems used by the Chinese e-commerce giant Alibaba are powered by generative AI algorithms. Alibaba provides personalized product suggestions through various platforms such as Taobao and Tmall. These recommendations are based on an analysis of user behavior and preferences. 

Alibaba has been able to corner a sizable chunk of China’s e-commerce sector partly because of this high degree of customization. According to research conducted by PwC, retailers might see a massive rise in sales through personalization enabled by artificial intelligence.

Customization with Machine Learning

Online marketplaces can benefit from machine learning by providing customers with more tailored experiences that streamline their buying processes and encourage repeat business. 

Sellers may learn a lot about their customers by taking a bird’s-eye view of their profiles, which includes demographic information, past purchases, interest in products they haven’t bought, browsing habits, and search queries.

Sellers may send customers targeted check-ins, personalized recommendations, and timely promotions using machine learning to datasets comprising various client information and activities.

Inventory Management with Machine Learning

Customer service methods are associated with inventory management. If you’ve ever dealt with out-of-stock items or been notified that an item you ordered would be back-ordered, you’ll know what we are talking about!

Furthermore, efficient inventory management can prevent stock-related inquiries from ever getting to service agents by consistently keeping things in stock.

Machine learning can assist retailers in finding the sweet spot between having just enough inventory and having too much. Using analytics powered by AI, you can quickly get dynamic predictions based on logistics, product inventory,  and sales trends in the past.

2. Voice-Activated IVR

Interactive voice response AI is something that the majority of us have dealt with. One example is when you phone a customer support number, and an automated voice asks for personal information. It asks for your name, member number, and the purpose of calling. Even though many customers hate IVRs, they are useful in resolving over 60% of calls automatically.

According to the experts, call center operations are simplified when organizations provide these AIs with clear answers, reducing agent workload. You can benefit from this AI technology if your business gets thousands of monthly calls. 

Through natural language processing (NLP), AI-powered IVR systems can more conversationally comprehend and interpret callers’ natural language inputs rather than rely on predetermined menu options. The result is an experience that is easier to use and more intuitive!

3. Optimizing Workflow With Automation

The potential of automation to enhance efficiency and productivity is recognized by call centers worldwide, and this trend is gaining steam in the Asian market. The use of AI is helping to improve employee experience and streamline operations across a variety of sectors around Asia Pacific. 

The industrial sector relies heavily on automation systems and robots powered by AI. Their presence greatly helps workplace safety, streamlines manufacturing, and decreases manual labor. For example, companies like Foxconn have implemented thousands of robots powered by artificial intelligence to boost staff productivity and well-being in China.

During the COVID-19 outbreak, customer service demand skyrocketed for electronics multinational Sharp, as it did for many other companies. Sharp Electronics Indonesia decided to automate to increase customer happiness, speed up consumer care and service, and improve accuracy and efficiency.

Daily, Sharp Electronics Indonesia usually gets over 1,000 inquiries from customers. In the light of this case study, it used to take 33 hours to input all the call data manually. But now, thanks to automation techniques, that time has been cut in half to just 20 hours. Not only that, but total production has increased by 60%.

4. Using Generative AI in Customer Service

Even while call centers have yet to completely accept the change by the rapid development of generative AI in the past year, all indications are that the technology is paying off. Through the interpretation of language, tone, and even vocal signals, generative AI algorithms can do real-time sentiment analyses of customers. 

Remember that there’s no need for AI-generated material that sets humans against bots. While AI copy can certainly enhance human-created written messages, it should not be seen as a replacement for it. 

Using this strategy, agents can avoid burnout, overcome language problems, or keep things interesting for different customers. AI content generators can provide responses that are identical to previous ones without requiring humans to type them out repeatedly.

Customer centers greatly benefit from this capability since it allows them to quickly detect and resolve customer dissatisfaction, increasing customer loyalty and retention. Generative AI technologies help improve customer relationships by knowing and empathizing with them.

According to a recent study by MIT Sloan School of Management experts and Stanford Digital Economy Laboratory, call centers that implemented generative AI assistant tools had an average productivity increase of 13.8%. This was evaluated by the number of customer issues addressed per hour.

5. Automated Chatbots & Voice Assistant

Chatbots are software applications that may replicate conversations between humans using text or voice. Their ability to understand and provide natural-sounding answers to user inquiries is an outcome of the combination of machine learning and natural language processing.

A whopping 68% of individuals, regardless of age, have interacted with a chatbot, according to one survey. That number is likely to rise as AI keeps getting better. So, call centers must provide intelligent chatbots for consumers to get their questions answered whenever it’s most convenient. 

Chatbots enable your call center to assist clients even when agents are unavailable, thanks to their ability to run around the clock. Here is an example:

Voice assistants and chatbots powered by generative AI have been developed by various leading technology companies in the Asia Pacific, including Baidu and Tencent. 

Both Baidu’s DuerOS as well as Tencent’s WeChat AI helper provide consumers with voice-enabled virtual assistants that can handle tasks, answer questions, and deliver personalized recommendations. This can alter how customers engage with their gadgets and services.

Conclusion

With the help of machine learning and AI, call centers in Asia may streamline routine processes, conduct more thorough analyses, speed up response times, better personalization, enhance first-call resolution, and—most importantly—improve the customer experience!

The reality is that AI will modernize and improve the environment of call centers in Asia, even though some people may be concerned that it will replace call centers. Well, that is not the reality as analyzed above.

AI makes it possible for call center agents to be more effective issue solvers by providing them with capabilities such as intelligent call routing, automated self-service, and real-time support and analysis of client behavior. Modern technology empowers them to deliver exceptional customer experiences quickly!

That is exactly what some Chinese business giants, like Alibaba, Baidu, Tencent, Sharp Electronics Indonesia, and Foxconn have been doing. With ideal customization and automation, businesses can focus on more important aspects to enjoy overall growth. You might overlook the bigger complications at the back end if you are still tangled in minor communication issues or customer complaints. 

No, AI will not put call centers out of business. Instead, it is an efficient tool that will positively impact customer service in the future!

Author: Greg.B

Executive with 25 years of proven success in call center management and revitalizing business units. Proven career record of producing multimillion-dollar profits through pinpointing operational inefficiencies and encouraging the revitalization of employee morale and corporate culture change.