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Conversational AI: The Secret Recipe for Enhancing Customer Experience

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Sameer is a seasoned business professional with close to three decades of experience across diverse verticals. He joined Zoom in 2019, prior to which he has successfully handled key roles across various companies such as West Corporation, Microsoft, IBM, Cisco and Datasoft Application Software, to name a few.

Companies have probably noticed that customers are impatient. When customers search the company’s website for answers or reach-out for customer service or support, they want answers immediately without any delay. Chatbots help businesses meet this demand by allowing customers to type or ask a question and get an answer immediately. However, the relevance of that answer can vary depending on the type of technology that powers the solution. Conversational artificial intelligence (AI) enables a natural exchange - much like talking to a customer service rep - that helps time-strapped customers get the information they need quickly and with minimal frustration.

Although some chatbots are rules based and only enable users to click a button and choose from predefined options, other solutions are intelligent AI chat bots. Artificial Intelligence gives these systems the ability to process information much like humans. However, the key differentiator of conversational AI is that it simulates human conversations using natural language processing (NLP) and natural language understanding (NLU).

Conversational AI in Customer Service

Although this technology is a natural fit to enhance customer support, it extends far beyond the realm of customer service. With customer centricity at its core, the application of AI becomes even more significant in a country as diverse as India where rapid digitization has fueled widespread smartphone adoption, bringing connectivity to remote corners of the country. The popularity of digital channels, combined with the power of AI, has opened new avenues for businesses to offer instant, interactive, and personalized experiences to consumers.


Additionally, machine learning and NLP enable conversational AI applications to use customer questions or statements to personalize interactions, enhance customer engagement, and increase customer satisfaction. Thus, many industries in India, spanning from healthcare and agriculture to human resource and finance, are also recognizing the potential of AI-powered solutions to improve their productivity and enhance customer experiences. Since chatbots powered by conversational AI can work 24x7, customers can access information after hours and speak to a virtual agent when customer service specialists aren’t available.

Conversational AI solutions are designed to manage a high volume of queries quickly, wherein even if a business receives an influx of inquiries at the same time, it can handle them and still provide quality responses. While customer service and support specialists often have a heavy workload, conversational AI can easily manage questions about accounts, payment history with knowledge base articles, and similar other references so that the team can focus on more complex issues requiring a personal touch. Additionally, companies can train conversational AI to understand and respond in their customers’ languages, helping them reduce labor costs by not having to hire a large team of multilingual customer support specialists.

Features like automatic speech recognition and voice search make interacting with customer service more accessible for more customers. A multi-language application also helps to overcome language barriers, enhancing the customer journey for more customers. Lastly, since a few people simply prefer self-service, conversational AI helps them to simply access information on their own without help from a customer service specialist.

Picking the Right Conversational AI Solution

While conversational AI is the way to go if businesses want to help improve their customer service, it is paramount for organizations to select the right kind of conversational AI that will serve their diverse requirements. For instance, Natural Language Processing is good for natural interactions and a good customer experience. Overall, the platform should handle basic queries without human help and forward more complex ones to agents. Most importantly, it should be capable of doing all this while simultaneously being able to integrate with other business applications.