How Chatbots and AI Technologies Are Transforming the Call Center Industry

What is a Chatbot?

A chatbot is an AI software that can converse with a user. It simulates natural language through messaging applications, websites, mobile apps, and the telephone. Chatbots can answer basic questions, assess customer needs, and reduce the need for a human response in many cases. For example, if a company uses a chatbot to respond to inquiries about a store’s hours and location, a human has more time and bandwidth to field more complicated questions.

AI technologies can: 

• Increase productivity
• Provide transparency
• Ensure accountability
• Improve staff training
• Reduce stress
• Increase job satisfaction
• Lower costs
• Cut customer wait times

In addition, chatbots can:

• Provide 24/7 availability
• Handle routine questions
• Handle higher call volume
• Enable customer service providers to deal with more complex tasks 

Chatbots can also fall short in customer service when companies design their processes so callers can’t easily access a human. What may be a significant cost advantage for companies can be a huge minus for customers. This tactic also is used on websites that hide their contact links.

Analytics Insight estimates that the number of AI-powered voice assistants will reach eight billion by 2023. Further, AI-powered chatbots are estimated to reduce business costs by $8 billion by 2022.

Call Center Work Conditions

The call center industry employs many millions of people around the world, in rich and developing countries. According to Forbes, India was the market leader for many years, but the Philippines moved to the top spot in 2011. Call centers employ around 1.3 million people in the U.K. and more than 6 million in the U.S.

Working in a call center is a stressful, high-pressure, results-oriented job. According to Analytics Insight, it’s an industry with a high turnover rate. Call center workers are continually leaving, being replaced, and being trained. Call center managers generally oversee hundreds of workers while working to achieve company targets.

Pandemic Impacts

When the pandemic hit, companies that continued to operate found themselves reconfiguring their call centers so staff could work remotely — which isn’t always possible for employees in developing countries. 

According to Forbes, back in 2014, the CEO of Telstra, Australia’s largest mobile phone company, predicted that within five years, there would be no people working in its call centers. In reality, the industry has seen modest growth, but call centers are undergoing a technological transition. The article predicted that post-pandemic call volumes would probably remain stable, but more customer exchanges will be managed digitally.

AI and Chatbots Technologies

CMS Wire asserts that AI is transforming customer service call centers by providing real-time feedback, predictive analytics, and in-depth analysis. Some of the significant technological advances include:

Natural language processing (NLP) is the ability of computers to understand text and spoken words. IBM explains that NLP drives computer programs that translate text from one language to another, respond to verbal commands, and rapidly summarize large volumes of text — even in real-time. Forbes wrote one of the exciting advances in NLP systems: detecting a customer’s emotional state over the phone or keyboard.

AI Coach helps improve the emotional intelligence of call center professionals. The software can gauge how well a conversation is going in real-time and provides coaching to improve engagement and reduce stress. It also provides measurements of customer perception and other business insights.

Interactive Voice Response (IVR) is the automated menu of options customers can select when they first call. Early versions may have helped companies reduce call volume, but they didn’t make customers very happy. Since, AI and machine learning have improved the technology. For example, an AI-enabled system that provides accurate answers to customer questions was built using IBM’s natural language understanding (NLU) software. According to CMS Wire, IBM worked with Humana to create the Provider Services Conversational Voice Agent with Watson. This solution achieved an average of 90-95% sentence accuracy. 

Ttec, a global CX (customer experience) technology and services firm, argues that engineering a customer-centric IVR design can improve customer satisfaction by guiding callers to the help they need quicker.

Analytics are more accessible now that phone conversations are easily converted to text. Companies then analyze the calls and track customer interactions. 

Predictive Behavioral Routing (PBR) uses AI and analytics to match call center customers with specific customer personality models. The intent is to personalize the customer experience better and provide a greater chance of positive interaction. PBR was first introduced and patented by Mattersight Corporation in 2014.

That was all about AI and Chatbots.

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Career Opportunities for AI and Chatbots

In this write-up, AI and Chatbots we learned that as companies, governments entities, and other organizations move to expand AI in their customer service operations, career opportunities in AI will expand because companies need professionals to create and manage chatbots. In addition, the average annual AI engineer salary in the U.S. is over US$110,000 (INR₹8187025).

Simplilearn can help you get a foothold in this exciting, evolving field with our AI ML Course, offered in partnership with Purdue University. If you have any questions in the article AI and chatbots, leave a comment below.