8 ChatGPT for Customer Support Strategies & 53 High-Impact AI Prompts to Use

Boost your customer support with 8 effective ChatGPT strategies and 53 AI prompts designed to optimize interactions and improve service quality.

Aug 19, 2024

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8 ChatGPT for Customer Support Strategies & 53 High-Impact AI Prompts to Use

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With the rise of AI in customer support, there's been a noticeable shift in how businesses handle client interactions. Companies are no longer limited to basic decision-tree bots that churn out robotic responses. Advanced AI tools like ChatGPT can now understand human language and deliver accurate responses that improve over time. This advancement allows businesses to automate customer support and improve the quality of service customers receive and improve customer service KPIs. Imagine you reach out to a business on social media to ask about a recent purchase. You expect an answer quickly, but instead of a human, you get a message from a bot. This is the new age of customer support powered by AI tools like ChatGPT for customer support.

ChatBees.ai's AI customer support solution easily leverages AI tools like ChatGPT to improve customer service operations and enhance overall customer experience.

What Is ChatGPT & How Does It Work?

ChatGPT is an app built by OpenAI. Using the GPT AI models, it can answer your questions, write copy, generate images, draft emails, hold a conversation, brainstorm ideas, explain code in different programming languages, translate natural language to code, and more—or at least try to—all based on the natural language prompts you feed it. It's a chatbot, but a good one.

The latest version of ChatGPT is also multimodal, at least if you use the GPT-4o or GPT-4o mini model. In addition to text prompts, it can respond to images and audio. This opens up a wide range of real-world uses, like translating a conversation in real-time or helping you identify a restaurant dish from a photo.

Note: GPT-4o mini can't yet support all the same inputs and outputs as GPT-4o—for example, video and audio—but OpenAI says it plans to roll that out.

Exploring ChatGPT’s Evolved Capabilities and Extension Framework

Since its launch at the end of 2022, ChatGPT has become much more powerful and useful. It can search the web for answers to your prompts, interact with other apps through custom GPTs (what OpenAI calls its extension framework), and create images using the DALL·E 3 image model.

Of course, ChatGPT is also a way for OpenAI to get a lot of real-world data on how its models perform from actual users and serves as a fancy demo for the power of GPT, which could otherwise feel a little fuzzy unless you were deep into machine learning.

Understanding ChatGPT’s Contextual Memory and Interactive Features

One of ChatGPT's biggest features is that it can remember all the context from your conversation with it. If you tell it something in your initial prompt, it can recall it much later in the conversation.

You can also ask it to rework things and correct any mistakes. This makes interacting with the AI feel like a genuine back-and-forth. If you want to get a feel for it, spend five minutes playing with ChatGPT now (it's free!), and then come back to read about how it works.

How Does ChatGPT Work? An Overview of the Technology Behind the AI Chatbot

This humongous dataset was used to form a deep learning neural network [...] modeled after the human brain, which allowed ChatGPT to learn patterns and relationships in the text data [...] and predict what text should come next in any given sentence.

ChatGPT works by attempting to understand your prompt and then spitting out strings of words that it predicts will best answer your question based on the data it was trained on. While that might sound relatively simple, it belies the complexity of what's happening under the hood.

Supervised vs. Unsupervised learning

The P in GPT stands for pre-trained, and it's a super important part of why GPT can do what it can. Before GPT, the best-performing AI models used supervised learning to develop their underlying algorithms. They were trained with manually labeled data, like a database with photos of different animals and a text description of each animal written by humans.

While effective in some circumstances, these kinds of training data are costly to produce. Even now, there isn't that much data suitably labeled and categorized to be used to train LLMs.GPT employed generative pre-training, where it was given a few ground rules and then fed vast amounts of unlabeled data—near enough to the entire open internet. It was then left unsupervised to crunch through all this data and develop its understanding of the rules and relationships that govern text.

Enhancing Predictability and Appropriateness in GPT Through Fine-Tuning

GPT-4o was trained similarly, though its training data included text, images, and audio. This way, it could learn what an apple is and what one looks like.

You don't know what you'll get when you use unsupervised learning, so GPT is also fine-tuned to make its behavior more predictable and appropriate. There are a few ways this is done (which I'll get to), but it often uses forms of supervised learning.

Transformer Architecture

All this training is intended to create a deep learning neural network—a complex, many-layered, weighted algorithm modeled after the human brain—which allows ChatGPT to learn patterns and relationships in the text data and tap into the ability to create human-like responses by predicting what text should come next in any given sentence.

This network uses transformer architecture (the T in GPT), which was proposed in a 2017 research paper. It's essential to the current boom in AI models. While it sounds—and is—complicated when explained, the transformer model fundamentally simplified how AI algorithms were designed. It allows computations to be parallelized (or done simultaneously), significantly reducing training times.

Transformers vs. RNNs: The Advantages of Self-Attention Mechanisms

Not only did it improve AI models, but it also made them quicker and cheaper to produce. At the core of transformers is a process called self-attention. Older recurrent neural networks (RNNs) read text from left to right.

This is fine when related words and concepts are beside each other, but it complicates things when they're at opposite ends of the sentence. (It's also a slow way to compute things as they have to be done sequentially.)

Understanding Tokenization and Attention in Transformer Models

Transformers read every word in a sentence at once and compare each word to the others. This allows them to direct their attention to the most relevant words, no matter where they are in the sentence.

It can be done in parallel on modern computing hardware, which vastly simplifies things. Transformers don't work with words; they work with tokens, chunks of text, or an image encoded as a vector (a number with position and direction).

How Token Vectors and Attention Encoding Enhance Transformer Models

The closer two token vectors are in space, the more related they are. Attention is encoded as a vector, which allows transformer-based neural networks to remember important information from earlier in a paragraph.

And that's before we even get into the underlying math of how this works. While it's beyond the scope of this article to get into it, Machine Learning Mastery has a few explainers that dive into the technical side of things.

Tokens

It's also important how AI models understand text, so let's look deeper at tokens. GPT-3, the original model behind ChatGPT, was trained on roughly 500 billion tokens, which allows its language models to more easily assign meaning and predict plausible follow-on text by mapping them in vector space.

Many words map to single tokens, though longer or more complex words often break down into multiple tokens. Tokens are roughly four characters long. OpenAI has stayed quiet about the inner workings of GPT-4 and GPT-4o, but we can safely assume it was trained on the same dataset since it's even more powerful.

Training GPT-3: Human-Created vs. Synthetic Data

All the text tokens came from a massive corpus of data written by humans, at least for GPT-3. That includes books, articles, and other documents across all different topics, styles, and genres—and an unbelievable amount of content scraped from the open internet.

It was allowed to crunch through human knowledge to develop the network it uses to generate text. Researchers are running out of human-created training data, so GPT-4 and later models may also be trained on synthetic—or AI-created—training data.

The Role of Parameters in GPT-3 and GPT-4: More Isn't Always Better

Based on all that training, GPT-3's neural network has 175 billion parameters or variables that allow it to take an input—your prompt—and then, based on the values and weightings it gives to the different parameters (and a small amount of randomness), output whatever it thinks best matches your request.

OpenAI hasn't said how many parameters GPT-4 has, but it's a safe guess that it's more than 175 billion and less than the once-rumored 100 trillion parameters. Regardless of the exact number, more parameters don't automatically mean better. Some of GPT-4's increased power comes from having more parameters than GPT-3, but a lot is probably down to improvements in how it was trained.

Multimodal Training in GPT-4o: Handling Text, Images, and Audio

GPT-4o and GPT-4o mini are even harder to conclude about. In addition to text, they were trained on images and audio—which can also be broken down into discrete tokens—so their neural networks must have billions of additional parameters to deal with those additional modalities.

The corporate competition between the different AI companies means that their researchers are now unable or unwilling to share all the interesting details about how their models were developed.

Reinforcement learning from human feedback (RLHF)

GPT's initial neural network was entirely unsuitable for public release. After all, it was trained on the open internet with almost no guidance. To further refine ChatGPT's ability to respond to various prompts safely, sensibly, and coherently, it was optimized for dialogue with a technique called Reinforcement Learning with Human Feedback (RLHF).

OpenAI created some demonstration data showing how the neural network responds in typical situations. They created a reward model with comparison data (where AI trainers ranked two or more model responses) so the AI could learn the best response in any given situation. While not pure supervised learning, RLHF allows networks like GPT to be fine-tuned effectively. This process has continued with each subsequent release of GPT and is part of what has allowed the later models like GPT-4 and GPT-4o to be safer and more reliable.

Natural language processing (NLP)

All this effort is intended to make GPT as effective as possible at natural language processing (NLP). NLP is a huge bucket category encompassing many aspects of artificial intelligence, including:

Speech recognition

Machine translation

Chatbots

It can be understood as the process through which Al is taught to understand the rules and syntax of a language, programmed to develop complex algorithms to represent those rules, and then made to use those algorithms to carry out specific tasks.

How NLP Powers GPT's Response Generation

Since I've covered the training and algorithm development side, let's look at how NLP enables GPT to carry out certain tasks, particularly responding to user prompts. It's important to understand that ChatGPT generates the text of what words, sentences, and even paragraphs or stanzas could follow for all this discussion of tokens.

It's not the predictive text on your phone bluntly guessing the next word; it's attempting to create fully coherent responses to any prompt. This is what transformers bring to NLP.

The Process of Token Analysis and Response Creation in ChatGPT

The simplest way to imagine it is like one of those finish-the-sentence games you played as a kid. The simplest way to imagine it is like one of those finish-the-sentence games you played as a kid.

ChatGPT starts by taking your prompt, breaking it down into tokens, and then using its transformer-based neural network to try to understand what the most salient parts of it are, and what you are asking it to do.

Variability in Responses Based on User Prompts

The neural network kicks into gear again and generates an appropriate output sequence of tokens, relying on what it learned from its training data and fine-tuning. For example, when I gave ChatGPT the prompt, Zapier is… it responded by saying:

Zapier is a web-based automation tool that allows users to connect different web applications to automate repetitive tasks and improve workflows.

That's the kind of sentence you can find in hundreds of articles describing what Zapier does, so it makes sense that it's the kind of thing that it spits out here. But when my editor gave it the same prompt, it said:

Zapier is a web-based automation tool that allows users to connect different web applications and automate workflows between them.

That's similar, but it isn't the same response.

Asking What is Zapier?

What does Zapier do?

Describe Zapier

All get similar results, presumably because they occupy similar positions in vector space. GPT understands that the most salient word here is Zapier, and all the others ask for a summary in slightly different ways.

How GPT Uses Training Data and Randomness to Generate Unique Answers

That randomness (which you can control in some GPT apps with a temperature setting) ensures that ChatGPT isn't just responding to every single response with what amounts to a stock answer. It's running each prompt through the entire neural network each time, and rolling a couple of dice here and there to keep things fresh.

Its understanding of natural language also allows it to parse the subtle differences between, What is Zapier? and What does Zapier do? While fundamentally similar questions, you would expect the answer to be slightly different. Whatever way you ask things, ChatGPT is not likely to start claiming that Zapier is a color from Mars, but it will mix up the following words based on their relative likelihoods.

Multimodality in ChatGPT: Images, Audio, and More

While natural language processing is a huge part of ChatGPT, the chatbot has become increasingly multimodal over the past year. That means that using GPT-4o (and soon, GPT-4o mini), ChatGPT can also understand images and audio as part of the same prompt.

How GPT-4o Integrates Text, Audio, and Image Understanding

Could ChatGPT do that before? You're right. The crux is how it happens. Before GPT-4o, ChatGPT could understand images using a separate AI model that created a text description of the image.

It could listen to audio input, but a speech-to-text AI model converted the spoken words to text. In both cases, the text was passed to GPT, which responded with text or, in some cases, by prompting DALL·E 3 to create an image. With GPT-4o, the same AI model can understand the text, audio, and image inputs and output a response using text, audio, or images. It's a big step forward.

Ticket Resolution

Automated Ticketing System

Customer Service Knowledge Base

Slack for Customer Support

Ticket Triage

AI For IT Support

Ticket Handling Best Practices

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AI Ticketing System

8 Business ChatGPT For Customer Support Use Cases

ChatGPT can effectively handle customer inquiries and support requests. There are two angles to consider here:

The direct integration of ChatGPT into customer request handling procedures.

Customer service agents use ChatGPT to streamline their work while maintaining total control over customer communication.

The latter's effectiveness ultimately depends on the quality of the chat prompts. While many awesome ChatGPT prompts are available, businesses must consider their use and limitations carefully.

How to Use ChatGPT for Customer Service

AI tools like ChatGPT can help customer support agents significantly. It can provide efficient and round-the-clock assistance in some cases. Here are some aspects for which ChatGPT can improve customer support:

1. Offer 24/7 Customer Support Without Hiring More Employees

Customers would want 24/7 support so they never have to wait to resolve their queries. According to Hubspot Research, 90% of customers think an immediate response is important when they have a query. This includes customers all over the world in different time zones.

Cost-Effective Customer Service with ChatGPT

Every business would offer it if it weren’t for the heavy costs associated with hiring and training more employees. But ChatGPT can help businesses do this without hiring more people. How? By integrating ChatGPT into their customer service platform, businesses can offer real-time assistance regardless of the time zone or hour of the day.

While agents have shift limitations and can’t work around the clock, ChatGPT remains available without needing rest. This consistent availability can benefit businesses with a global customer base or those experiencing peak inquiry times outside regular business hours.

How can you do this?

Obtain access to the ChatGPT API. Integrate it into your customer service platform’s backend, ensuring incoming chat requests are directed to ChatGPT. Configure response patterns based on frequently asked questions and typical customer issues to allow the AI to provide timely and relevant responses.

A lot of companies are already using ChatGPT to provide round-the-clock customer services. Here are some familiar brands and the types of queries they resolve via ChatGPT 24/7 to deliver exceptional customer service:

Netflix uses ChatGPT to help customers with account issues, billing questions, and technical problems.

Amazon answers questions about products, shipping, and returns via ChatGPT.

Walmart leverages ChatGPT to help customers with order status, product availability, and shipping questions.

Tesla uses ChatGPT to answer questions about their cars, features, and settings.

2. Provide Customer Support in Multiple Languages

We function in a global economy, where more and more businesses are open to customers worldwide. This means that customers from all linguistic backgrounds will seek support from them. Hiring multilingual agents is one solution, but this is a costly affair.

ChatGPT can fill this gap by translating customer queries and responding to them in their preferred language, ensuring no customer feels alienated due to language barriers. This also opens a new level of personalization — providing customers with responses in their language and making them feel more comfortable.

How can you do this?

Integrate ChatGPT into your platform and enable the multi-language option. This will require some customization to prioritize your business's most common languages and ensure translations align with the nuances of your business’s terminology.

Some of your favorite brands are leveraging ChatGPT to provide great service to customers worldwide—in their languages. Here are some real-life examples:

Duolingo (staying true to its product) uses ChatGPT to provide customer support in over 30 languages. It can answer questions about Duolingo’s courses, features, and settings in any supported language.

Spotify provides customer support in over 60 languages with ChatGPT. It can answer questions about Spotify’s music, playlists, and features in any supported language.

3. Provide Better Contextual Comprehension for Chatbots

Chatbots have become essential in customer service. They can help businesses quickly resolve common customer questions without the need for agents. As we know, traditional chatbots are not the best at understanding context.

With ChatGPT, you can improve your customer experience in this department by a mile. Its deep learning algorithms allow it to understand the context better than traditional chatbots. Instead of just spotting keywords, it can grasp the essence of customer inquiries, ensuring more relevant and accurate responses.

How can you do this?

When integrating ChatGPT, use past chat logs (while maintaining customer privacy) to help it learn the typical flow of conversations and common contexts that arise in your industry. This training phase will help optimize its contextual understanding.

4. Handle a High Influx of Queries

Sometimes, you might experience a sudden surge in customer inquiries—it may be due to a marketing campaign, product launch, or some unexpected issue your product ran into. Whatever the reason, a sudden spike in customer queries can overwhelm your customer support team.

This is where ChatGPT comes to the rescue again. ChatGPT can help you tackle the situation cost-effectively—eliminating the need to rush hire and train more employees.

How can you do this?

Ensure that your hosting solution for ChatGPT can dynamically allocate resources based on traffic. Cloud-based infrastructures are optimal for this. Routinely review and update the knowledge base that ChatGPT accesses to ensure it can address queries on new products, services, or issues that may arise during such spikes.

5. Help You Scale Your Customer Service Economically

Scaling your customer support team can be costly and time-consuming, especially for budding businesses or ones with a tight budget. Growing businesses simply need more resources to handle customer queries as more prospects and customers contact them.

Instead of continuously hiring more staff to handle increasing customer inquiries, businesses can deploy ChatGPT to hold a substantial portion of customer interactions.

How can you do this?

Integrate ChatGPT as a first line of defense in your customer service chain. Allow it to handle general inquiries; if a query is too complex, it can escalate to a human agent. Monitor the system’s efficiency and make cost comparisons periodically to ensure the business saves money.

6. Help You Train Your New Hires

Training new support agents is not easy. While some may be freshers, others might have experience in the field but lack context in your industry or product. Training your agents is essential to delivering great customer service.

Instead of overwhelming your new hires with documents on your product and support guidelines, you can use ChatGPT to help them be floor-ready. Here are some ways in which you can leverage ChatGPT to train your agents:

Hold interactive Q&A sessions: You can use ChatGPT to create interactive Q&A sessions to train your agents. The agents can ask questions about company policies, products, or services.

Role-play with ChatGPT: Allow new agents to role-play as customers and use ChatGPT as the support agent. This will give them a perspective from the customer’s side and help them understand the kind of queries and responses they might encounter.

Show how to handle difficult situations: Handling an angry customer is difficult—even for the most experienced agents. To train your new hires to keep calm and handle angry customers effectively, create scenarios where customers are frustrated or angry. Let the new agents interact with ChatGPT to see how it manages and de-escalates such situations.

Regular Quizzes and Assessments: Utilize ChatGPT to conduct regular quizzes. The AI can create questions based on recent updates, ensuring agents always stay refreshed on their knowledge.

ChatGPT can help you do a range of things to train your employees better and simulate real-life scenarios to prepare them better. This will also save your experienced employees the time they would otherwise have to spend training your new hires.

How can you do this?

Use the OpenAI API to integrate ChatGPT with your company’s existing training software or Learning Management System (LMS). If you're starting from scratch, a cloud platform like AWS, Google Cloud, or Azure can host and integrate the LMS with ChatGPT.

Feed ChatGPT with essential company information:

Values

Mission

Policies

Culture

This ensures the model can answer basic orientation questions accurately. Connect your company’s product database or CRM system with ChatGPT. When queried, use API calls to pull specific data.

7. Use ChatGPT to Respond to Queries on Online Forums

Say an agent wants to respond to a negative review of your product on a product review website. They need to be crisp and to the point with their response since prospective buyers will read these reviews before they decide to buy your product. The tone of the response is also very important in these scenarios.

Your agent can simply contact ChatGPT to formulate a response with the right tone and within a specific character limit.

8. Detect Sentiment in Customer Communication

Another customer service use case for ChatGPT is analyzing your client's tone of voice and, potentially, the emotions they're experiencing. It can also help you craft a response that fits each customer's sentiment.

If they say, I'm still waiting for you to fix my website, ChatGPT could help you craft a message where I apologize for the delay, thank them for their patience, and reassure them that I'm working on the issue. Remember that humans will always be better at detecting others' emotions. You should always double-check ChatGPT's output.

AI Customer Service Software

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Help Desk Process

Hubspot Ticketing System

AI Customer Service Agent

Real-Time Agent Assistance

Ticket Management System

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Service Desk Automation

Customer Service Automation Software

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Automated Customer Support

Help Desk Automation

7 Benefits of ChatGPT/AI for Customer Support

1. Writes Content: AI That Writes for You

You can’t write all emails and responses yourself. It’s impossible. The volume is just too high. You can ask ChatGPT to help you out, though. It doesn’t matter if you’re short on time or can’t find the right words.

Just tell the AI what you want to communicate. Provide it with some background information and mention the message you want to shine through your response. You can even suggest the tone of voice to use to fit your brand.

2. Round-the-Clock Availability: No More Graveyard Shifts

You no longer need to arrange for your customer service to work the graveyard shift. Using a conversational CRM bot like ChatSpot, you can take note of and resolve queries automatically.

How much can it get done? According to IBM, AI-powered chatbots can resolve as many as 80% of routine customer questions. This means you can keep the ticket backlog as minimal as possible. Your customer service team will only work on resolving queries that AI can't handle autonomously.

3. Speeds Up Your Team's Work: Get Answers Faster

If a customer has a question your team can't answer from the top of their heads, they won't need to search through the knowledge base. They can ask ChatGPT to run the search for them and quickly present the answer, another point for team productivity.

4. Helps Generate Savings: Cut Costs on Support Operations

All of ChatGPT's far-ranging capabilities can help you save on operational expenses. These include limiting your support agents' operating hours, automating responses to common queries, and handling more than ever.

5. Prioritize Tickets Based on Level of Urgency: Get to the Important Issues First

If highly urgent customer tickets come into ChatGPT, ChatGPT can prioritize them for attention by human agents. ChatGPT can help you deal with the tickets that matter most and ensure no issues fall through the cracks. While it would take your agents time to categorize and prioritize tickets manually, ChatGPT will be able to do this automatically.

6. Increased Customer Satisfaction: Happy Customers, Happy Business

No matter how their problems are resolved, customers will be more satisfied with great customer service. ChatGPT seems more human-like than its predecessors, fuelling the interest of customer service teams in this technology.

Customers don’t care whether a human or chatbot is dealing with their issue as long as it is resolved, meaning that chatbots have huge potential to enhance your customer service strategy.

7. Consistency in Handling Similar Customer Tickets: Improve Your Customer Service Quality

One drawback of ChatGPT is that it may return different answers to the same questions, but as long as the question is phrased correctly, ChatGPT should provide consistent answers. This offers superior customer service compared to the variation you might get from a team of agents who approach problems differently.

Optimizing Internal Operations with ChatBees’ AI Customer Support Software

ChatBees optimizes RAG for internal operations like customer support, employee support, etc., with the most accurate response and easily integrates into their workflows in a low-code, no-code manner. ChatBees' agentic framework automatically chooses the best strategy to improve the quality of responses for these use cases. This improves predictability/accuracy, enabling these operations teams to handle more queries. No DevOps is required to deploy and maintain the service.

Try our AI customer support software today to 10x your customer support operations. Get started for free, with no credit card required. Sign in with Google and start your journey with us today!

5 Limitations of ChatGPT/AI in Customer Support

1. Relying on ChatGPT can Provide Inaccurate Information

AI isn't perfect. It produces information that isn't 100 percent accurate. Since customer service is the face of the business, this can prove problematic and damage the company's reputation. ChatGPT can provide well-written answers, but we can't be sure that what it outputs is true. Sometimes, it won't admit to not having an answer and will make up information instead.

2. Relying on ChatGPT for Customer Support Lacks Personalization

Customers appreciate personalization. And while AI can relieve customer service teams from

repetitive work, it can't provide the same level of personalization as humans. This can result in a less satisfactory experience for customers.

3. ChatGPT Lacks Empathy

Certain situations — for example, when a customer is upset — require empathy. ChatGPT can suggest responses that sound empathetic. It might not be able to get the customer is situation fully. AI understands facts, not emotions, so it's best if human agents get involved whenever there is a serious issue to handle.

4. ChatGPT can Pose a Security Threat

ChatGPT isn't free from security threats. There are at least two potential scenarios that could happen. Prospective scammers could manipulate it — since it follows users' commands, those with bad intentions could feed it with harmful content to your brand.

Data breaches might occur — these can happen both on your company's and OpenAI's (i.e., the company behind ChatGPT) end. The latter admitted that hackers have already used a vulnerability in their code to access data. Both of these situations could have serious business consequences. Not only could it hurt the company's image, but it could also cause financial loss.

5. ChatGPT is Not Yet Fully Developed

Despite intense interest from customer service teams, ChatGPT is still in its early stages. Since the technology is in its infancy, it still has bugs that need to be worked out and might not be suitable for use in a professional customer service context.

While ChatGPT is more advanced than comparable chatbot technologies, it still needs to be ready for the general public.

Where to Integrate ChatGPT on Your Website

The Homepage: Your Site’s Welcoming Committee

The homepage is the first page most visitors see when they land on your website. Placing your ChatGPT here allows you to greet users as they arrive, offer help, and guide them through your site.

Product Pages: Your Virtual Sales Assistant

Product pages are where you can introduce your ChatGPT as a virtual sales assistant. It can:

Answer product-related queries

Provide recommendations

Even assist with purchases

Support Pages: Your 24/7 Customer Service Rep

Support pages are ideal for ChatGPT to shine as a 24/7 customer service rep. It can answer FAQs, offer troubleshooting tips, and direct users to additional resources.

Contact Pages: Your Immediate Assistance Tool

A chatbot on a contact page can provide immediate assistance, giving users a faster alternative to emailing or calling customer service.

Checkout Pages: Your Cart Abandonment Helper

Integrating ChatGPT on a checkout page can help reduce cart abandonment by promptly addressing concerns or confusion during checkout.

Use ChatBees’ AI Customer Support Software to 10x Customer Support Operations

ChatBees optimizes RAG with our AI customer support software for internal operations like customer support, employee support, etc.. It provides the most accurate response and easily integrates into workflows in a low-code, no-code manner.

ChatBees' agentic framework automatically chooses the best strategy to improve the quality of responses for these use cases. This improves predictability and accuracy, enabling these operations teams to handle more queries. No DevOps is required to deploy and maintain the service.

Step-By-Step Guide on How to Integrate ChatGPT on Your Website

1. Obtain API Keys from OpenAI

The first step to getting ChatGPT up and running on your website is to obtain API keys from OpenAI. These keys are the bridge between your site and the ChatGPT service, enabling communication and data exchange, which is why they're necessary.

To get your keys, here's what you'll need to do:

Create an account on the Open AI website.

Once your account is all set up, navigate to the 'API Key' section.

Follow the prompts to make a new API key.

Securely store your API key. You're going to need it for the ChatGPT integration process.

So far, so good? Let's move to step two.

2. Technical Requirements and Considerations

Integrating an AI chatbot like ChatGPT requires technical proficiency and understanding of your website's backend. Here’s what you need to have in place:

Server-Side Integration: You'll need server-side integration to connect with the ChatGPT API. This typically requires understanding a server-side language such as Node.js, Python, Ruby, etc.

Secure Transmission: To ensure secure data transmission between your website and ChatGPT, you must use HTTPS. This adds a layer of encryption, making it harder for unauthorized entities to access the data.

Frontend Development: You'll also need to create a user-friendly front-end interface for your chatbot. This means some knowledge of frontend development (HTML, CSS, JavaScript) is required to create an engaging chat interface.

User Privacy: Respecting user privacy is crucial when deploying chatbots. To gain trust, inform users that they're interacting with a bot and give them access to information regarding data usage policies.

Do you have your API keys and understand the necessary technical requirements? Then, it's time to move on to the ChatGPT integration process. In the next section, I'll show you where to place ChatGPT on your website for maximum impact.

How to Integrate ChatGPT on Your Website

Since all websites are a little different and many factors go into integrating ChatGPT into your website, I will provide a high-level overview of the steps below.

Step 1: Setup OpenAI's ChatGPT API

With your OpenAI API key in hand, you're ready to set up the ChatGPT API. Here's one way to do it using a Node.js server.

const axios = require("axios");
const OPENAI_API_KEY = "your-api-key-here";

axios
    .post(
        "https://api.openai.com/v1/engines/davinci-codex/completions",
        {
            prompt: 'Translate the following English text to French: "{text}"',
            max_tokens: 60,
        },
        {
            headers: {
                Authorization: `Bearer ${OPENAI_API_KEY}`,
                "Content-Type": "application/json",
            },
        }
    )
    .then((response) => {
        console.log(response.data.choices[0].text.trim());
    })
    .catch((error) => {
        console.error(error);
    });

Making a Translation Request with OpenAI's API

I'm performing a language translation using the Davinci Codex engine in this example. The first line imports the Axios library, and the second calls your API key.

Lines 3-16 make a POST request to a specified endpoint in the OpenAI API (or the URL:https://api.openai.com/v1/engines/davinci-codex/completions). This request includes a prompt for translation and a parameter (max_tokens) to limit the text the chatbot will generate.

The remaining code tells the system what to do if the request is successful and how to handle errors if not. In this case, if it's successful lines 17-19 will receive the translated text and log it to the console. If there's an error, lines 20-22 block the request from being executed and log the error to the console.

Step 2: Connect to the API

The next step is to connect to the API. This requires setting up a server-side route that calls the ChatGPT API and returns the response.

The code provided above is a good starting point. Start by replacing your-api-key-here with your actual OpenAI API key. You can create a server-side function that requests the API from your site.

Step 3: Add ChatGPT to Your Website's Backend

To add ChatGPT to your website's backend, you must set up a server-side function that requests the API. This function will send user input to ChatGPT and receive responses.

Full disclosure: There are many ways to approach this step, and I could probably write a full post on this part of the setup alone. To that end, we'll skip ahead a bit and show you what the code will look like once you've chosen a port for your server and defined a route that makes a call to the OpenAI API.

const express = require('express');
const axios = require('axios');
const app = express();
const port = 3000; // Choose a port for your server

// Middleware to parse JSON requests
app.use(express.json());

// Define a route that makes a call to the OpenAI API
app.post('/translate', async (req, res) => {
    try {
        const { text } = req.body;

        // Replace 'YOUR_OPENAI_API_KEY' with your actual OpenAI API key
        const OPENAI_API_KEY = 'YOUR_OPENAI_API_KEY';

        // Make a call to the OpenAI API
        const response = await axios.post(
            'https://api.openai.com/v1/engines/davinci-codex/completions',
            {
                prompt: `Translate the following English text to French: "${text}"`,
                max_tokens: 60,
            },
            {
                headers: {
                    Authorization: `Bearer ${OPENAI_API_KEY}`,
                    'Content-Type': 'application/json',
                },
            }
        );

        // Extract and send back the translated text
        const translatedText = response.data.choices[0].text.trim();
        res.json({ translatedText });
    } catch (error) {
        console.error('Error:', error.message);
        res.status(500).json({ error: 'Internal Server Error' });
    }
});

// Start the server
app.listen(port, () => {
    console.log(`Server is listening at http://localhost:${port}`);
});

Step 4: Create a Frontend for the Chatbot

After setting up the backend, you must create a front end for your chatbot. This includes designing the chat interface and scripting the interactivity. You can use a combination of HTML, CSS, and JavaScript here.

The CodePen below provides basic code for you to use. Note that the chatbot in the results tab will not respond properly because it is not connected to the OpenAI API.

Step 5: Test the Integration

After setting up the back and front end, it is important to test the integration thoroughly. This ensures that the chatbot responds correctly to user inputs and that the interface works as intended.

53 Expert-Approved ChatGPT Prompts For Customer Support Challenges

General ChatGPT Customer Service Prompts

These prompts will give you solutions for general customer service scenarios.

1. Generate 5 variations of call openings for customer service representatives of [company name]. Customers call with various queries and issues related to our [products] they have bought. The greetings should be polite and empathetic.

2. Act as a customer service rep in [Your Company Name]. Now share some examples of how you would open a call/ chat to address an irate customer.

3. Generate a call script to build rapport with a caller who is a potential customer and is curious about our products/services. Be polite and persuasive, but do not sound aggressively salesy.

4. Imagine you are a customer support representative at [your company name], and a customer has called you regarding an issue with our software subscription they have purchased. Connect with the customer while I troubleshoot their issues and build rapport.

5. We are a company that [enter what your company does]. Suppose you are a customer support executive. You need to gather essential information from our customers to suggest the most suitable solutions [that cater to their needs]. How would you do it?

One prominent feature of ChatGPT for customer service is that it remembers the previous conversation with a user and builds on it. If you need further information or suggestions on the answer it offered, you can ask in the next prompt. For example, your customer may not like your agent's solutions. You can ask ChatGPT about what it would do in such a situation.

6. What if the customer doesn’t like the solution you provided and asks for other options in the above scenario?

ChatGPT Prompts for Customer Support Handling Product or Service Inquiries

7. A potential customer has called to inquire about [Your product] and its capabilities. [Explain a little more about your product]. How would you handle the call as a trained and persuasive customer service agent? You need to try and convert the caller.

8. Act as a technical support executive in [Your company]. An existing customer has approached me regarding [a product/service your company offers] and shares an additional feature/idea for the product. You cannot promise to execute the request or make the decision immediately, but you have to honor the customer’s efforts. Generate an exemplary conversation.

9. Act as a customer service agent for [Company Name]. Our [Software Product] currently has a bug that causes it to crash upon opening. Many people who have bought the product cannot use it currently. Many want to return the product, but we want customers to wait. As a customer service agent, you should understand customers’ frustrations and politely encourage them to wait as the team works on a fix. The response should reflect empathy.

10. A customer reaches out to us to inquire about our product and asks how it differs from similar products in the market. As a diligent and persuasive customer service agent, provide the customer with relevant and satisfactory information. [Add a brief about your product]

11. We are a service provider. We offer fixed packages with fixed pricing. However, customers sometimes want to create their packages to make the service suitable to their needs. How would you deal with this situation as a solution-oriented customer support agent? We are customer-centric and occasionally allow personalization on special requests.

For other challenges, tweak these AI customer service prompts and generate scripts for your agents in real-time.

ChatGPT Prompts to Manage Complaints and Issues

12. We are a [Industry name] brand. Act as a customer service representative for us. One of our customers placed an order showing that the product was delivered. However, the customer claims that they didn’t receive it. Assist the customer and offer a resolution.

13. Can you offer an exemplary response as a customer service agent to a customer inquiring about the benefits of our [your product] in French? [Explain a little about your product and its key features.]

14. Act as a customer support executive for our product-based company. The customer contacts you and tells you they placed an order and paid online but haven’t received an order ID. You have to probe the issues and offer possible solutions.

15. A customer purchased a [Product] from our website but received a damaged product. As per our policy, we will consider a product replacement or return only when the product is delivered damaged and reported within 7 days. The customer called on the 10th day. Assist the customer as our customer service representative. Be polite and empathetic, and offer a solution.

16. A customer is very upset and wants to speak to senior management since they have been complaining about [state the issue clearly]. As a customer service rep, try to resolve the issue on your end, but if the customer is adamant, ask for contact details to schedule a callback. Create an exemplary conversation.

ChatGPT Prompts to Assist With Billing And Payment Queries

To create a prompt for billing and payment inquiries, brief the issue and explain your company’s billing or payment policy briefly, and ask the ChatGPT chatbot to generate a response.

17. Our service-based company charges [your billing model] for subscriptions. The customer contacted our support team to inquire about the billing cycle and the total monthly amount deducted. Act as a customer service agent and assist the customer.

18. A customer claims that their previous bill is still showing due. However, they made the payment last week. As a customer support executive, you assist the customer with the bill payment history and resolve the issue.

19. Customers need to update their payment information on their accounts so that their next payment for their subscription to our service goes smoothly. You can help customers update their payment information by sending an encrypted form to fill in the details directly into the system without third-party interference. Act as a customer service representative and assist the customer.

20. A potential customer is interested in our product [Product Name]. We offer [Mention the product category] products and post-purchase services. As our customer service agent, explain our pricing, upfront charges, and recurring fees to the customer when using the product.

ChatGPT is already aware of many general processes for solving account-related issues.

21. Imagine you are our diligent and polite customer service agent. One customer needs help setting up their account and creating a profile on our app. Our product is [brief what your app is about]. Guided and helped the customer on the call.

When you begin to type questions to ask ChatGPT, you can command the roleplay first and then proceed to explain the scenario like this:

22. Act as a customer service agent for [Company name]. Consider the below scenario and generate a sample conversation where you guide the customer: One of our clients has purchased a team version of our software and needs help setting up different profiles under the admin account. Our software allows custom feature allocation to different people based on their designation in the organization.

23. Act as a customer service agent for our software company. A client has purchased a multiuser package of the product. A few of the users have forgotten their passwords. Probe the issue and guide the client with the password restoration process on the admin panel.

24. Take our company's customer service agent role [Company name]. We run an e-commerce store [or specifics about your company]. One of our business partners' usernames has been deactivated since they have been inactive for a long time. Assist the customer in restoring their username and reusing the account.

25. A customer calls to report an issue with login. They are trying to get into their account on our app. As a concerned customer support agent, assist the customer with their login issue.

ChatGPT Chatbot Prompts to Provide Technical Support

You should brief the course of action in the prompts to let the AI generate an actionable response.

26. One of our customers cannot log in to their account because it shows an error. Ours is a software service company, and the customer has bought a subscription to one of our apps. Act as a technical support agent and assist customers with their login issues.

27. Our website has a glitch. Due to this, customers cannot place orders, view recent orders, or track the order status. Generate 3 variations of an empathetic script for our customer service agents to deal with anxious and impatient customer queries regarding the issue.

28. A customer needs assistance with the technical process behind how our software works. Summarize the following knowledge base article to give step-by-step instructions for customer service agents to guide the customers. [Insert the article’s link]

29. We sell [product type] through our app and website. A customer has contacted us to complain about technical issues with their [product]. Act as our technical support executive and assist the customer by troubleshooting their issue.

30. Generate a polite and clear script to guide customers toward the self-help knowledge base and chatbot for their generic queries and issues.

31. Imagine you are a technical support agent for [Company name]. A customer calls and complains that one of the software's most important features is not working. You check and find out that it’s an issue on the customer’s end. Generate an exemplary conversation where I guide and assist them in troubleshooting the problem while maintaining empathy and patience.

ChatGPT Prompts to Handle Shipping and Delivery Concerns

You can use customer self-service software and link it in the ChatGPT prompt to turn it into an actionable guide for relevant queries.

32. Our company recently held a sale that led to a huge number of orders, which caused the order processing to take time and prevented us from shipping many of the orders on time. Generate a script for handling frustrated and confused customers to help them understand the reason behind the delay and assure delivery.

33. A customer contacts us to request a concession in shipping charges. We cannot reduce the shipping charges since it is an international delivery, and charges are non-negotiable. Act as a calm and empathetic customer service agent and convince the customer that the charges are reasonable.

34. A customer ordered from our [e-commerce website/online store] but hasn’t received the tracking information yet. It’s been more than 24 hours. The customer contacted you, our customer support agent, to inquire about the same. Please assist the customer.

35. A customer’s order was delivered, but one item is missing. The customer calls to inquire about the issue. You, a customer service representative, assist the customer with the issue. [If the item was shipped separately, add the info in the prompt].

36. A customer wants to return a recently delivered item. Our customer service team is required to encourage exchange in place of returns. Act as a customer service representative and probe the reason for the return. Suggest exchanging it for another item. If the customer rejects it, assist with the return process.

ChatGPT Prompts to Manage Cancellations and Refunds

The first response to a cancellation request should always be retention. When you write ChatGPT prompts for customer support, try to retain the prompt when the customer asks for cancellation. A subtle effort to probe why the customer wants to cancel and offer a solution instead may help you avoid losing a valuable customer.

37. We are a service-based company and charge monthly for subscriptions. The customer had set auto-renewal of subscription every month. They want to cancel it. Act as a customer service agent who is empathetic and persuasive and tries to retain the customer

38. Per our cancellation policy, a customer must cancel a [purchase/subscription] before the [order is shipped/ renewal of subscription]. A customer contacts us and asks to cancel the product while the shipment is halfway through/ after renewal. Act as a customer support agent and assist the customer.

39. A customer has purchased a non-returnable item. However, they received the damaged product. The customer contacted us to request a refund since the product is useless for them now. Proceed to assist them in this scenario as a customer service executive

40. How will you deal if the customer is adamant about receiving a refund? We do make exceptions if we lose a loyal customer.

AI Customer Service Prompts to Close the Conversation on A Good Note

The conversation-closing script should also make the customer feel valued and welcomed. The agent’s tone must convey excitement to make the customer happy when the conversation ends.

41. Ask the customer if they are satisfied with the resolution you provided today as a customer service agent. If they say yes, proceed to close the call. Generate an exemplary conversation.

42. Generate 5 variations of closing calls with customers unsatisfied with the solution you provided as a customer service representative. You should sound empathetic and willing to offer further assistance.

43. Generate a few variations of personalized thank-you emails to send to customers after a purchase. Ensure that the emails include a coupon code as a token of appreciation for future purchases.

44. As a customer support executive, close a conversation with a customer on a friendly and polite note. Also, educate the customer about our self-help resources for future reference and encourage them to leave feedback based on their experience with customer service today.

ChatGPT Prompts Asking for Customer Feedback

You can use ChatGPT customer service prompts to create feedback forms and relevant questions or integrate feedback surveys with thank-you notes.

45. What questions should be included in a customer feedback form for their interaction with the customer service team?

46. Could you please generate 5 variations of customer feedback survey templates to be sent to customers after interacting with the customer service team?

47. Please create 5 variations of a nice thank you note to be sent along with the feedback survey form after customers’ interactions with our customer support team.

ChatGPT Prompts for Customer Service Dealing With a Disgruntled Customer

48. A customer’s project is hindered due to a glitch in the software they have paid for. They are extremely angry that they disrespect you, a customer service representative. Be empathetic and patient, and handle the situation to avoid losing the customer. You have to probe the issue and provide an apt solution, too. Generate an exemplary conversation.

49. A customer gets angry upon being notified about violating service terms. Act as a customer service agent and explain to the customer the limitations of their package. Suggest that they upgrade the plan according to their needs. Be empathetic and polite despite the rude tone the customer may be using.

50. An irate customer calls in and is very frustrated. Instead of speaking about the issue, they are just rambling. You are a polite and empathetic customer service agent. You have to calm the customer down and probe the issue. Assist accordingly.

Additional prompts

51. Can you provide some practical tips and strategies employers can use to address employee resistance to adopting CRM software? Please write a knowledgeable article on this topic and outline some specific steps that can be taken to overcome common causes of this issue and foster a culture of collaboration and innovation in the workplace.

52. Prompt to analyze customer sentiment based on specific data. Analyze customer sentiment based on the following data: Hi there, I recently purchased your product and was disappointed with the quality. I’ve tried contacting customer service but haven’t received a response yet. Can someone please help me with this issue?

53. Act as a customer survey creator. As a customer experience professional at a SaaS business, we recently added some new features to our business texting platform. We’d like to send a survey to our existing subscribers to learn more about their experience with our product, identify areas where we can optimize it, and potentially leverage the feedback for future marketing campaigns. Could you help us create a brief survey with five questions to help us achieve these objectives? Thank you.

Will ChatGPT Replace Customer Support Agents?

In January 2023, a CEO made headlines when he declared he was making 90 percent of his customer support staff redundant, thanks to a chatbot built in-house. He was lambasted across the board for his absolute disregard for both quality of service and respect to his employees. Despite this, many of us working in customer service read it with more than an ounce of trepidation. We have to wonder what it would look like if AI were to take over certain customer service jobs completely.

Knowledge manager?

Customer service agent?

QA specialist?

The ChatGPT Knowledge Manager Replacement

Could ChatGPT write your knowledge base? Many customer service leaders agree that, in the best-case scenario, customers can solve a problem themselves. Our Benchmark Report found that 73 percent of customer service teams plan to invest more in proactive customer support.

This is made possible by providing a help center, knowledge base, or FAQs with information about your product, the customer journey, and answers to common issues that crop up for other customers. ChatGPT is proficient in text generation. Is it logical to outsource the role of knowledge base writer to AI?

The Pros of Using ChatGPT to Write Your Knowledge Base

ChatGPT undoubtedly exhibits prowess in efficiency. Only a machine can churn out legible content at 1,000 words a second. When the average person types at 40 words per minute (not even accounting for the planning and ideating that goes into content creation), this is the speed that dreams are made of.

The content may not be original or inspiring, but it can be easily directed. If you’re skilled enough in prompting, you know to include things like make the tone formative and matter-of-fact. The output will be informative and matter-of-fact. The biggest pro that eyes will be drawn to, though, is the cost savings. You are saving significantly on employee hours and potential expenses related to training and supervision. No matter what salary your knowledge base creator earns, ChatGPT is – checks notes – free.

But what does it cost your customers?

The Cons of Using ChatGPT to Write Your Knowledge Base

ChatGPT is unable to understand the greater purpose of the task contextually. Providing customers with accurate & useful information is crucial. If ChatGPT doesn’t grasp the context well, it might end up sharing information that’s wrong, unhelpful, or doesn’t match what the business aims for.

This issue points towards generative AI’s potential to hallucinate. ChatGPT’s hallucination refers to its capacity to generate responses that may be contextually plausible but factually incorrect or fictional. It may produce responses that sound reasonable but are not grounded in reality.

The Role of Tone in Effective Customer Communication

Your communication should not be a machine. Customers are driven by emotion, and tapping into that emotion greatly affects communication. Effective customer service means adopting the right tone of voice for your customers.

It’s about understanding how your company wants to portray itself, mirroring your customers' language, and striking a tone that matches the rest of your communication. Knowledge managers instinctively infuse it into self-service content to create a consistent and authentic customer experience.

Challenges of Brand Voice in AI-Generated Content

Consider how tone affects these sentences, both with the same meaning: The weather forecast indicates rain tomorrow. It looks like we’re in for rain tomorrow! ChatGPT has been trained on massive amounts of data from disparate internet sources and diverse publications.

There is no denying that ChatGPT’s writing style is generic. ChatGPT will struggle to capture and reflect the unique brand voice because it tries to write like everyone. It doesn’t try to write like you.

AI as a Tool, Not a Replacement for Human Expertise

The clear answer is that you cannot depend on AI alone to write your knowledge base. The cost savings are huge, and a faulty knowledge base will cost you far more in the long run. It will only lead to more customers contacting your support team since self-service capabilities are lacking.

But that doesn’t mean your Knowledge Manager, Team Lead, or whoever is in charge of maintaining a help center has to hack it alone. ChatGPT for customer service is a tool, not a replacement—you can find many artificial intelligence tools to aid your writing and help speed up the process.

Could Chatbots Replace Your Customer Service Agents?

This may be one of the most pivotal questions of this customer service era. Chatbots have functioned as AI-driven tools, adept at providing scripted responses to basic inquiries. Their limitations have been immediately evident.

This often causes huge frustration for customers who want more nuanced conversations – not ones in which FAQs are repeated. More recently, generative AI has taken the wheel. Generative AI enables chatbots to engage in two-way conversations resembling human chatter. Nearly half of enterprise business leaders believe chatbots are becoming indistinguishable from customer service workers.

There’s a Good Bot

When discussing bots, we must consider that many companies have different definitions of chatbots. Not all bots are made the same. A generative bot will be able to converse more fluidly with customers but is prone to error (as discussed above regarding ChatGPT).

An automated bot relying on conversation design will readily spit out facts but cannot offer substantive dialogue with your customer. This doesn’t mean there are good and bad bots; it has more to do with how they are deployed, for example, in which circumstances, whether or not the customer is aware, etc.

The Argument for Bots

Yet again, chatbots' cost-effectiveness speaks to their power. Customer service agents require a salary, a desk, appropriate breaks, etc., while a chatbot can work all day hours without complaining.

It doesn’t need food, water, or friendly interactions. And it offers answers or at least fast responses. If bots were to replace humans without careful planning and complete consideration, you’d be doomed to fail. But, organizations are increasingly taking a measured approach to bot implementation.

Bot Best Practices

You need quality data for a quality bot. This means examining past support interactions to detect reoccurring questions and giving the chatbot the right answers.

Businesses usually outsource this. For example, Ultimate helps companies install, train, and automate chatbots with careful consideration for their uses. No-code chatbot builders like SendPulse or ManyChat let SMBs create and integrate chatbots with ChatGPT.

The Argument Against Contact Centers of Full-fledged Bots

Wait, you might argue chatbots are smarter now. They have better understanding, are more complex, can show empathy, and are more accurate. But they are not perfect. You see above the pros and cons of chatbots in black and white. Your customers’ judgmental capabilities are multifaceted. They will often still be able to discern a real human from a machine, often leading to annoyance when they cannot reach a human service agent.

We use the example of self-driving cars to illustrate this point. These cars cannot drive drunk or text and drive; they have far better logical capacities in times of stress than many human drivers. Yet these crashes will always make the headlines. This is because people trust machines less than each other.

Human Connection in Customer Service

Customer satisfaction ranks too high on any company’s priority list to consider this option. 60 percent of customers are still frequently disappointed by their chatbot experiences. Customer experience is about more than speed and availability.

If you want your customers to be happy with your company's customer service, you need human contact center agents. This doesn’t mean abandoning bots as useless; using them where appropriate means unlocking human potential, giving your agents more time for higher-value tasks, more personalized service, and complex issues—and excellent customer service.

Balancing Automation and Human Touch in Customer Service

We cannot replace humans and people doing customer service jobs with chatbots and robots. They have to supplement each other. When it comes to customer experience, if you cheapen your investment in your support infrastructure, you’re also cheapening the result.

You want to create this great, efficient customer experience with a robot that can answer you in 2.5 seconds. But if you take out the humanity of that, you lose the people behind the checks and balances of everything. All you’re doing is just going back to those days when we would punch zero furiously on a phone tree, trying to get to a person that doesn’t exist.

How Can AI Make Customer Service Agents Better Humans?

The great bot debate proves that personal, human customer support is now more important than ever. When facing specific issues, most customers prefer speaking to a customer service agent rather than a machine. This does mean that the most complex, hardest-to-solve problems will land in your agents’ laps, but that doesn’t make their job easier.

While the noise about chatbots rings loudest, there are other ways that generative AI can help agents improve their jobs and, subsequently, provide excellent service to needy customers. Most teams have started using AI, but they also agree that they can enhance its use.

It begins with breaking down the tasks that customer service agents undergo.

You need to analyze each task to see where generative AI may augment those tasks—for example, paying particular attention to tasks that lead to burnout and inefficiency.

No team should apply AI to every aspect of customer service: the winning companies will augment their teams, not replace them.

For example, AI can:

Automatically translate messages into different languages

Summarize conversations into bullet points to make escalation faster and smoother

Turn bullet points into eloquent messages for when you want to explain things carefully to a customer

Agent Assist tools can suggest relevant knowledge-based articles or solutions.

It will view AI as the ultimate assistant for agents. For example, 81 percent of customers are happy that companies use their data to offer better, personalized recommendations. AI can look at a customer’s entire purchase history and proactively recommend suggestions to the agent to give to the customer. This doesn’t only help the agent; it also helps the customer and the bottom line.

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