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Building ChatBots for Customer Service: A Conversation with ChatGPT

Building ChatBots for Customer Service: A Conversation with ChatGPT

OpenAI released ChatGPT; since then, the AI chatbot has been taking the tech world by storm. With the amazing functions of ChatGPT, many people are dreaming about the potential of AI and how they can use it to impact their business, especially now that it has become so tangible and easy to play with.

While this new platform created by OpenAI has a chat interface, future applications could go far beyond what we currently know as a chatbot. Imagine an AI tutor helping to prepare for the SATs or a coding assistant helping software engineers to accelerate their work. 

On this occasion, we wanted to explore how to use ChatGPT to build a customer service chatbot. While the current version does not enable its service for this particular scenario, a conversation between our CTO Aníbal Abarca and ChatGPT gave numerous insights on its use and how to create a chatbot. Keep reading to see what we learned. 

A Conversation between our CTO and ChatGPT

Can I build a customer service chatbot for my company using ChatGPT?

CHATGPT is a large language model developed by OpenAI that can generate human-like text based on a given input. It is a research tool not intended for production use and is not specifically designed for building chatbots.

While CHATGPT may be able to generate text that can be used in a chatbot, it is not the optimal choice for building a customer service chatbot for several reasons:

  • CHATGPT is a general-purpose language model, not a chatbot platform: CHATGPT is not a platform or tool specifically designed for building chatbots. It does not provide features such as natural language processing (NLP) or machine learning (ML) that are commonly used in chatbot development.
  • CHATGPT is not intended for production use: CHATGPT is a research tool and is not intended for production use. It is not designed to be scalable or reliable enough for use in a customer-facing application.
  • CHATGPT may not be able to handle a wide range of inquiries: Chatbots must be able to handle a wide range of inquiries and provide helpful responses. CHATGPT is a general-purpose language model and may not be able to provide accurate and helpful responses to a wide range of customer service inquiries.

For these reasons, it is generally better to use a platform or tool that is specifically designed for building chatbots when building a customer service chatbot for your company. These tools often provide features that are tailored for chatbot development and may also offer pre-built chatbot templates and other resources to help you get started.

What are the benefits for companies of building chatbots?

There are several benefits that companies can realize by building chatbots:

Improved customer service: Chatbots can provide quick and efficient customer service by answering common questions and providing information about products and services. This can free up human customer service representatives to handle more complex inquiries and improve the overall customer experience.

Increased efficiency: Chatbots can handle a large volume of inquiries simultaneously, which can help to reduce response times and improve efficiency.

Cost savings: Chatbots can reduce the need for human customer service representatives, resulting in cost savings for the company.

Personalization: Chatbots can use data about a user’s preferences and history to provide personalized recommendations and information.

Availability: Chatbots can operate 24/7, benefiting companies with global customers or offering support outside of normal business hours.

Scalability: Chatbots can scale to meet the needs of a growing business without the need to hire additional staff.

Improved data collection: Chatbots can collect data about user interactions and preferences, which can be useful for improving the customer experience and informing business decisions.

I hope this helps! Let me know if you have any other questions.

What are the main challenges companies face when building chatbots?

There are several challenges that companies may face when building chatbots:

Determining the scope and functionality of the chatbot: It is important to carefully consider what you want your chatbot to do and how it will benefit your business. This will help you determine the scope and functionality of your chatbot and ensure that it can meet your needs.

Collecting and organizing data: Chatbots rely on data to provide accurate and helpful responses to users. Gathering and organizing this data can be time-consuming and may require significant resources.

Training the chatbot: Chatbots must be trained on large amounts of data to provide accurate and helpful responses. This process can be complex and time-consuming and require specialized knowledge and expertise.

Testing and refining the chatbot: It is important to test it to ensure it is functioning as intended thoroughly. This may require adjusting and fine-tuning the chatbot’s responses based on user feedback and testing.

Ensuring the chatbot can handle a wide range of inquiries: Chatbots must be able to handle a wide range of inquiries and provide helpful responses. This can be challenging, as users may ask unexpected questions or use language in a way that the chatbot is not prepared for.

Integrating the chatbot with other systems: Chatbots may need to be integrated with other systems, such as CRM platforms or databases, to access necessary data and perform certain tasks. This can be a complex process that requires careful planning and coordination.

Maintaining and updating the chatbot: Chatbots require ongoing maintenance and updates to ensure that they function properly and provide accurate and helpful responses. This can be a significant ongoing effort for companies.

What chatbot platforms could you recommend me to use? 

There are several chatbot platforms that you could consider using to build a customer service chatbot:

Dialogflow: Dialogflow is a cloud-based chatbot platform that allows you to build, test, and deploy chatbots on a variety of platforms, including messaging apps, mobile apps, and websites. It provides various tools and features for building chatbots, including natural language processing (NLP) and machine learning (ML) capabilities.

Botpress: Botpress is an open-source chatbot platform that allows you to build, test, and deploy chatbots on various platforms. It offers a range of tools and features for building chatbots, including NLP and ML capabilities, as well as pre-built chatbot templates and other resources to help you get started.

IBM Watson Assistant: IBM Watson Assistant is a cloud-based chatbot platform that allows you to build, test, and deploy chatbots on various platforms. It provides a range of tools and features for building chatbots, including NLP and ML capabilities, as well as pre-built chatbot templates and other resources to help you get started.

Microsoft Bot Framework: Microsoft Bot Framework is a chatbot platform that allows you to build, test, and deploy chatbots on various platforms, including messaging apps and websites. It provides a range of tools and features for building chatbots, including NLP and ML capabilities, as well as pre-built chatbot templates and other resources to help you get started.

These are a few examples of chatbot platforms that you could consider using to build a customer service chatbot. It is important to carefully evaluate the features and capabilities of different platforms to determine which one is the best fit for your needs.

I hope this helps! Let me know if you have any other questions.

Getting started with AI for your Business

Whether you are looking for ways to improve your customer service or exploring how to bring the power of Artificial Intelligence into your business processes and products, our team can help you discover, design, and implement AI solutions. 

Intelligence Everywhere brings AI to scale. Wizeline helps you build insight-driven solutions that deliver verifiable business results by producing evermore actionable recommendations. Learn more about the latest case studies from our Intelligence Everywhere practice: Scaling Up Data and Analytics Capabilities and Building a Knowledge Graph to Deliver Timely Info to Users.

Get in touch with a Wizeline expert to accelerate your innovation roadmap. Contact consulting@wizeline.com to start the conversation today!


Tajma Brown

Posted by Tajma Brown on January 18, 2023