AI-powered assistants like Siri and Alexa have been around for a long time now. Similarly, chatbots using conversational AI are also being used by businesses to deliver human-like customer interactions and improve experiences.
In this post, we cover the basics of conversation AI, including real-life examples to understand how it can help improve your customer service.
Conversational AI is the type of artificial intelligence that can naturally talk or interact with humans. It uses natural language processing to understand the input, process information, and generate appropriate responses.
In practical terms, when a user inputs text, the conversational AI software utilizes NLP to determine the user’s intent and generate an appropriate response.
Through continuous interaction, the machine learning aspect of the AI improves response quality and accuracy automatically.
For call centers, conversational AI is helpful for enhancing customer service and agent efficiency. It allows businesses to provide instant, round-the-clock support to customers, improving satisfaction and loyalty.
By handling general inquiries, it enables human agents to handle more complex ones and improve the end-user experience.
Businesses use conversational AI technology for customer service in various ways. Here are some common types of conversational AI systems:
Rule-based chatbots respond to user input by following a series of established rules. They are organized as a dialog tree and often use regular expressions to match user input to human-like responses.
On the other hand, conversational AI is a technology that uses natural language processing to understand and respond to queries.
For example, imagine visiting a banking website and using a chatbot to quickly check your account balance. The chatbot responds promptly because this task is scripted.
Now, imagine using a conversational AI via a virtual assistant on your mobile banking app. Instead of simply checking your balance, you ask a more complex question like, “How do my spending patterns compare to last month?” The AI understands your query using NLP, analyzes your transaction history, and provides detailed insights into your spending habits over time.
Conversational AI can be applied across departments; it can help businesses:
Using natural language processing, conversational AI can understand customer queries and respond just like a human. It provides immediate, accurate, and consistent responses to general inquiries based on the knowledgebase. AI systems like chatbots and virtual assistants, can handle general inquiries and reduce wait times, leading to more satisfied customers.
AI can also track and analyze customer interactions and provide valuable insights to refine your customer service strategies.
Conversational AI can handle routine tasks, such as answering FAQs, processing orders, and scheduling appointments.
This allows human agents to focus on more complex and nuanced issues, therefore boosting efficiency and productivity.
Conversational AI offers 24/7 service. Therefore, customers can get assistance at any time, regardless of time zones or holidays.
Furthermore, conversational AI can handle multiple interactions simultaneously without degradation in performance.
This enables businesses to scale customer service during peak times or unexpected surges in demand, leading to cost savings and consistent customer experiences.
Conversational AI has become a key component in enhancing user experiences across various industries.
Here are two real-life examples for you to inspire from:
Amazon Echo devices, featuring the virtual assistant Alexa, have revolutionized home technology interaction. By simply speaking to Alexa, users can control smart home devices, play music, receive weather updates, and make online purchases.
This integration of conversational AI into everyday life has greatly enhanced convenience and user engagement worldwide.
Google Assistant, available on devices like smartphones and smart speakers, offers a smooth and intuitive user experience. Users can interact through natural language to ask questions, set reminders, and manage their devices.
This conversational AI technology by Google improves daily routines by making interactions more efficient and user-friendly.
Traditional customer service methods often fall short, leaving customers frustrated and dissatisfied. This is where conversational AI voicebots come into play.
Conversational AI voicebots are advanced systems capable of understanding and responding to human speech in a natural and engaging manner. Unlike traditional chatbots, these AI-powered voicebots can interpret and process complex queries, providing accurate and relevant responses.
Exotel offers an exceptional AI voice assistant designed to revolutionize customer interactions. It’s a leading communication solutions provider for customer engagement and experience that is used by 7000+ businesses across 60+ countries.
Exotel’s AI Voice Assistant is more than just a bot. It’s a conversational partner fluent in Hindi, English, and Hinglish. Designed for seamless integration and continuous learning, this voice assistant is always available to handle a wide array of tasks with ease.
It helps call centers to:
Exotel’s AI Voice Assistant is the ultimate solution for call centers seeking to improve operational efficiency, enhance customer engagement, and drive reliable and trusted customer interactions.
Here’s what our customers have to say:
Schedule a demo today and experience the future of customer engagement.
1. What are the Fundamentals of Conversational AI?
Conversational AI combines machine learning and natural language processing (NLP) to enable machines to understand, process, and respond to human language in a natural, conversational manner. Key components include Natural Language Understanding (NLU) for interpreting user intent, Natural Language Generation (NLG) for creating human-like responses, and continuous learning to improve interactions over time.
2. Is ChatGPT a Conversational AI?
Yes, ChatGPT is a conversational AI. It uses machine learning and NLP to engage in human-like conversations, understand context, and generate responses. It also continuously learns from interactions and improves its performance.