Application of Generative AI Chatbot in Customer Service

Published in

Chatbots Life

10 min readMay 15, 2023

As the field of Artificial Intelligence (AI) continues to advance at an unprecedented rate, Generative AI is becoming an increasingly popular tool for businesses to transform their Customer Experience (CX) and engage customers in new and exciting ways. However, with new updates and features being launched every month, it can feel impossible to keep up or navigate how to leverage these powerful models.

In this blog post, we’ll explore some of the top use cases for Generative AI across multiple industries you can use to contain and convert your customers.

According to the results of a One Poll survey, the current state of customer service in CX (the customer experience) is pushing people to their limits. Specifically, 62% of respondents reported that they have stopped using a company specifically because of poor customer support, while 65% said that resolving an issue just doesn’t seem worth the time and effort involved. At Master of Code, we specialize in helping businesses leverage Generative AI chatbots to create impactful and engaging experiences for their customers. Our CX team has extensively researched the best use cases for this technology, and we’re excited to share our insights with you.

Why integrate Chatbots with Generative AI into customer service?

Improved Contextual Understanding

Generative AI-powered Chatbots can understand the context of a customer’s inquiry, allowing them to provide more relevant and useful responses. Customers appreciate when chatbots can accurately and efficiently provide the information they need, without requiring them to go through multiple steps or talk to a human representative. According to Salesforce, 79% of customers are willing to provide pertinent information about themselves if it leads to personalized interactions that make them feel recognized and understood right away.

Reduced Dependency on Human Agents

Simple chatbots are typically programmed with a limited set of responses and can only handle basic inquiries. Generative AI Chatbots can handle more complex inquiries without the need for human intervention, reducing the dependency on human agents. These chatbots can analyze large volumes of data and learn from previous interactions to improve their responses over time.

Richer Responses

With Generative AI Chatbots, businesses can provide more engaging and interactive experiences for customers by incorporating images, videos, and other multimedia content into their responses. For instance, in cases where customers need assistance with technical issues, a chatbot can provide video tutorials or step-by-step guides to help them troubleshoot the problem. Alternatively, if a customer is interested in purchasing a product, a chatbot can show images and videos of the product in use, providing a more immersive experience.

Cost savings for customer support

Compared to a traditional in-house team of customer service representatives, a Generative AI chatbot requires only a one-time investment in its development and deployment. An in-house team of 4 customer service reps can come at a high cost, with salaries and benefits alone amounting to $141,284, based on Cloudtask report. Adding a customer service manager at a salary of $45,726 and other expenses like hiring costs, office space, and software and hardware can bring the total cost to $259,955 per year. The high salary of each agent can significantly impact the budget of a company, making it a costly option for customer service. Expenses such as training, phone systems, office supplies, and other team members like trainers, analysts, and quality assurance coaches may add up to an extra $200K per year.

If your company has already implemented a chatbot solution for call center automation, you don’t need to start from scratch to integrate Generative AI into your customer service system. Master of Code specialists have developed an integration methodology called “Embedded Generative AI” which allows for the addition of Generative AI features into a customer’s existing Conversational AI platform. This approach helps reduce the costs and resources associated with building a new system from scratch.

Natural Language Understanding

Generative AI-powered Chatbots can understand and respond to customer inquiries more accurately:

Generative AI chatbots can understand and respond to customer inquiries more accurately, even when they use complex language, slang, or colloquialisms, leading to higher customer satisfaction rates.
Generative AI can also enhance the chatbot’s multilingual support capabilities, allowing it to communicate with customers in multiple languages, thereby increasing the chatbot’s potential user base. As per ICMI research, 79% of contact centers deal with customers who are not fluent in the primary language(s) provided by the contact center, and out of those, 60% expect customer service to be offered in their native language.
Generative AI can help to diversify dialogues, making the chatbot’s interactions more engaging and personalized, resulting in increased customer loyalty and retention.

Generative AI Chatbot Use Cases in Customer Service

Generative AI Chatbot Use Cases in Customer Service for eCommerce

As eСommerce continues to grow, businesses are seeking innovative ways to provide personalized and efficient customer service. Generative AI chatbots are one solution that can make a significant impact on customer satisfaction and sales. Here are some cool use cases of using Generative AI in eCommerce for Customer Service:

Personalized Product Recommendations: With Generative AI, chatbots can analyze customer behavior and purchase history to recommend products that are tailored to each individual’s preferences. This not only helps customers find products they will love, but also increases the likelihood of a purchase and customer loyalty.
Upselling/Cross-selling: Generative AI Chatbots can also suggest complementary products to customers, increasing the likelihood of an upsell or cross-sell. For example, if a customer is buying a dress, the chatbot could suggest matching shoes or accessories.
Customer Reviews: Chatbots can help businesses gather customer feedback and reviews in a more efficient and personalized way. By asking specific questions and using sentiment analysis, chatbots can provide businesses with valuable insights into customer satisfaction and areas for improvement.
Product Search: With Generative AI, chatbots can better understand customer queries and provide more accurate search results. This saves customers time and frustration, and can also increase sales by helping customers find what they are looking for more easily.
Product Comparison: Chatbots can also assist customers with product comparisons, providing detailed information about similar products and helping customers make informed purchasing decisions.

Generative AI Chatbot Use Cases in Customer Service for Banking

Generative AI chatbots have tremendous potential to transform the banking industry by enhancing the customer service experience. Morgan Stanley, a leading financial services firm, is embracing the potential of OpenAI’s ChatGPT-4 technology. With a test group of 300 advisors, the firm plans to provide its network of 16,000 advisors access to the chatbot, streamlining access to the company’s valuable data and research. Here are some cool use cases of using Generative AI at Banking for Customer Service:

Fraud Detection: With the help of Generative AI chatbots, banks can easily detect fraudulent activities in real-time. The AI-powered chatbots can monitor customer behavior, detect suspicious patterns, and alert customers before the fraud happens.
Financial Literacy: Generative AI chatbots can provide financial literacy to customers. By analyzing customer data, chatbots can offer personalized financial education, including advice on saving and investing. Customers can interact with the chatbots to learn more about financial concepts, strategies, and best practices.
Financial Product Recommendations: AI banking chatbots can analyze customer data to recommend the best financial products, such as savings accounts, credit cards, and loans. The chatbots can also help customers compare different products and choose the one that best fits their financial needs.
Suggested Saving Recommendations: Generative AI chatbots can analyze customer data to provide personalized saving recommendations. Based on their income, expenses, and spending patterns, customers can receive customized advice on how to save more and improve their financial health.
First-tier support: AI-powered chatbots can handle basic customer inquiries and provide first-tier support. Customers can interact with chatbots to ask questions, receive account updates, and get general information about banking products and services. This frees up human customer service representatives to focus on more complex issues.

Generative AI Chatbot Use Cases in Customer Service for Insurance

As customer service becomes a critical component in the insurance industry, Helvetia has become the first-ever listed insurer to launch a direct customer contact service that utilizes OpenAI’s ChatGPT technology. The service aims to simplify the process of accessing insurance and pension products by using artificial intelligence to answer customers’ questions. Though currently experimental, this move demonstrates the potential Use Cases of Generative AI chatbots to transform the way insurers interact with their customers:

Customized quotes based on needs: AI chatbots can quickly provide personalized insurance quotes based on customers’ specific needs, such as age, location, driving history, and more. This helps customers to find the right insurance policy that meets their requirements.
Interpreting long-form policy information into digestible content: Insurance policies can be long and complex, making it difficult for customers to understand what’s covered and what’s not. Generative AI chatbots can interpret policy information and break it down into easy-to-understand content, helping customers make informed decisions.
First-tier claim registration and classification: AI chatbots can help customers register and classify their claims quickly and efficiently. With the help of natural language processing, chatbots can accurately interpret customers’ messages and direct them to the right department or agent, saving time and improving customer satisfaction.

Generative AI Chatbot Use Cases in Customer Service for Automotive

In today’s digital age, customers expect quick and efficient service from businesses in every industry. This is especially true in the automotive industry, where customers often have questions about complex technology and maintenance. Here are some use cases of using Generative AI chatbot at Automotive for Customer Service:

Personalized car manual assistance: By pulling information from long-form car manuals, Generative AI chatbots can provide personalized assistance to car owners, guiding them through complex maintenance procedures and helping them better understand their vehicle.
Predictive maintenance: With Generative AI chatbots, car owners can receive alerts and recommendations for predictive maintenance, helping them prevent issues before they become major problems. By monitoring a car’s performance and maintenance history, the chatbot can recommend the best course of action for keeping the car in top condition.
Model comparison: Generative AI chatbots can assist customers in comparing various car models, providing insights into the features, performance, and cost of each. This helps customers make informed decisions about which car best meets their needs and budget.

Generative AI Chatbot Use Cases in Customer Service for Telecom

The telecom industry is poised for increased investment as more telcos explore the potential use cases of ChatGPT. By integrating this technology into their customer service channels, telcos can provide automated, round-the-clock support, personalized product recommendations, and quick handling of customer inquiries and issues, all while reducing wait times and improving customer satisfaction. Additionally, Generative AI can be used for translation to better serve a geographically diverse customer base, ultimately enhancing the customer experience and cutting costs for telcos.

Technical support: A generative AI chatbot can assist customers with technical issues related to their telecom services, such as internet connectivity problems or device troubleshooting.
Personalized product recommendations: A generative AI chatbot can analyze a customer’s usage patterns and preferences to provide personalized product recommendations for telecom services. For example, if a customer frequently uses streaming services, the chatbot can recommend a plan that includes unlimited data for streaming.
Billing inquiries: A generative AI chatbot can assist customers with billing inquiries, such as explaining charges on their bill or helping them understand their payment options.

Generative AI Chatbot Use Cases in Customer Service for Travel/Hospitality

Here are the use cases of Generative AI in Travel/Hospitality for Customer Service:

Visa/Entry Requirements: Chatbots powered by Generative AI can assist customers in obtaining visa and entry requirements for their desired destination. They can provide real-time information on visa requirements, document checklist, and other important information to ensure a seamless travel experience.
Hotel Reviews Across Multiple Domains: Chatbots can gather and analyze hotel reviews across multiple domains, providing customers with the most relevant information about hotels, including ratings, reviews, and amenities. This can help customers make informed decisions when selecting a hotel.
Itinerary Builders: Chatbots can help customers plan their travel itinerary based on their preferences and budget. They can suggest activities, restaurants, and places to visit, and provide real-time information on weather, traffic, and other factors that could impact the itinerary.
Hotel and Destination Recommendations: Chatbots can recommend hotels and destinations based on a customer’s budget, preferences, and travel history. They can provide real-time pricing and availability information, and help customers book their desired hotel or destination. Over the past year, we’ve helped our clients invest in Conversational AI innovation and increased 7.67x weekly bookings or conversion rate 3x higher since the chatbot was launched, while avoiding several common mistakes during the planning and scoping phase.

Generative AI has competencies that include making long-form content concise and digestible, pulling information from multiple domains, and offering personalized, contextual solutions with vast variability. By leveraging these competencies, businesses can create unique experiences for their customers that are tailored to their needs.

It’s worth noting that these are just a few examples of the many use cases for Generative AI Chatbot in Customer Service. The possibilities are virtually endless, and as technology continues to evolve, businesses are sure to find new and innovative ways to incorporate it into their CX strategies.

At Master of Code, we’re passionate about helping businesses leverage the power of Generative AI chatbots to transform their customer service. If you’re interested in learning more about how you can use this technology to create engaging experiences for your customers, we’d love to chat!

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