Chatbots have been in news these days. After people started praising ChatGPT for its ability to give almost accurate answers to every question a human can throw at it, Google too launched its chatbot, Bard. Therefore, it becomes more relevant than ever before to understand what it is and how the entire system of chatbot works. Zee Business spoke to Abhijit Mhetre, Senior Vice President (SVP) Marketing, Kore.ai, to explore more on every possible aspect of chatbots. Here are excerpts.

What exactly is a chatbot?

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A chatbot is a computer program that simulates a conversation with human users through text or voice interactions. It can be used to help users find information, complete tasks, or just chat.

How do chatbots work? 

 

Chatbots operate on understanding natural/human language input in text or voice format and respond accordingly in natural language. Chatbots use natural language processing (NLP) to understand and interpret the user's input and then respond with appropriate information or actions. The basic chatbots are designed to perform routine repetitive tasks such as answering customer queries, fulfilling basic requests, etc. 

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Types of chatbot

 

There are mainly two types of chatbots: Rule-based and self-learning

Rule-based chatbots: They use a set of pre-defined rules to understand and respond to user input. These rules specify the exact phrases or keywords that the chatbot should look for and how it should respond to them. These are very limited in their understanding as well as their functionality. 

ALSO READ | What is Bard? Google CEO Sundar Pichai explains the newly introduced AI chatbot

AI-powered or Intelligent chatbots: AI-based chatbots, popularly known as intelligent virtual assistants, use NLP and machine learning algorithms to understand and respond to user input. They can learn from interactions with users and improve their responses over time. With platforms like kore.ai and the recent advent of Large Language Models and Generative AI technology, they need minimal to no training to get started and they can be very sophisticated in their responses. 

In both cases, when a user interacts with the chatbot, the user's input is analyzed and processed, and a response is generated and sent back to the user. The chatbot may also access external databases or APIs to gather additional information to provide a more complete response to the user.

Some other forms of chatbots are mentioned below: 

Self-learning chatbots: These chatbots use machine learning algorithms to learn from interactions with users and improve their responses over time. They can handle a wider range of inputs and may be able to understand natural language.

Hybrid chatbots: These chatbots combine features of both rule-based and self-learning chatbots, using a combination of predefined rules and machine-learning algorithms to respond to user inputs.

Voice chatbots: These chatbots are designed to work with voice commands and dialogue. They are typically used in smart devices, home automation, and even at contact centers.

Overall, depending on the use case and the level of complexity of the task, different types of chatbots can be used.

Where all chatbots can be used? 

 

Chatbots can be used for a variety of support and services purpose to deliver delightful customer/employee experiences. Following are a few examples of where chatbots can be used for -

Customer service: Chatbots can be used to assist customers with inquiries, provide product or service information, and help customers navigate a website.

Retail and E-commerce: Chatbots can be used to assist shoppers with product discovery, product recommendations, help with online purchases, and track orders. Chatbots can help assist staff with inventory management, customer service, etc. 

Banking: Chatbots can be used to assist customers with account information, transactions, reminders and notifications, fraud detection, etc.

Healthcare: Chatbots can be used to assist patients with appointment management, answering basic questions, providing information about treatments, reminders and notifications.

Travel: Chatbots can be used to assist with booking flights, hotels, and rental cars, as well as provide information about destinations.

Marketing and Lead Generation: Chatbots can be used to engage with potential customers, provide information about products and services, and collect contact information for follow-up marketing.

HR and Recruitment: Chatbots can be used to assist with HR tasks such as answering employee questions, tracking vacation time, and helping with the training and recruitment process.

IT Support: Chatbots are widely used to help employees and support staff with IT support queries such as password issues, software or security issues, software upgrades, hardware troubleshooting and repair, etc.

How effectively chatbots can work?

 

Chatbots can be very effective in certain tasks and use cases, depending on the design, training, and implementation. Some factors that can affect the effectiveness of chatbots include:

Quality of training data: Chatbots rely on the data they are trained on to provide accurate and relevant responses. If the data is incomplete, inaccurate, or outdated, the chatbot's performance may be affected. The training data includes domain training, human language training, functional training, and company or brand-specific training. The more a chatbot can mimic a human-like conversation, the more effective it will be. This includes understanding idiomatic expressions, sarcasm, and context to provide more accurate responses.

Complexity of task: Chatbots are better suited for simple, well-defined tasks, such as providing weather forecasts or answering FAQs. The more complex the task, the more challenging it may be for a chatbot to provide accurate and helpful responses.

User interface and conversation design: The design of the chatbot's user interface, including the flow of the conversation and the use of natural language processing, can greatly impact the user's experience and the chatbot's effectiveness.

Machine Learning: Chatbots that use machine learning algorithms, such as self-learning or hybrid chatbots, are able to improve their performance over time by learning from interactions with users. These chatbots can become more effective as they gather more data and improve their understanding of user needs and intent.

Integrations: Chatbots can be integrated with other enterprise systems, such as CRM, ERP, e-commerce platforms, knowledge systems, and more, to provide more accurate, timely and actionable information.

Overall, chatbots can be very effective when used for the right tasks, with appropriate data and machine learning, in a well-designed user interface, and with proper integration with other systems.