Let me ask you something: how often do you roll your eyes reading or hearing that ChatGPT will disrupt all industries? Daily, I bet. 

Sure, statements like this are not exactly true yet. However, it would not be an exaggeration to say that the ChatGPT-4 technology by OpenAI is already changing (for good) how companies communicate with their clients.

But why and how? What’s hiding behind that? Is ChatGPT yet another buzzword or the actual value? In the article, we’ll figure this out, tap a toe into the ChatGPT technology itself, its capacity and limitations, and specify its benefits and drawbacks for the customer service niche. Also, we’ll try to explore how to incorporate ChatGPT into the business properly.

ChatGPT for customer service: is there any value?

The business-customer relationship has always been trouble – and unfortunately, it doesn’t get much better. The 2022 National Customer Rage Survey says that over 70% of respondents had issues with product or service-related contacts. One of the main reasons is the long wait spans on the phone when reaching out to customer support. 

Meanwhile, companies are trying to cut costs on their call centers and customer support staff. This, consequently, affects customer service interactions and customer experience overall.

And that’s when ChatGPT saves the day for both sides. Equally important is that businesses are ready for the new technology. According to ResumeBuilder’s survey, among 1000 businesses:

• 49% of respondents already apply ChatGPT;
• 30% of surveyed plan to do so;
• 93% of existing users consider expanding their ChatGPT usage.

Source: ResumeBuilder.com

Moreover, the survey shows that 57% of current business owners already use the technology for customer support. So, the niche is already up and running and will not stop anytime soon. 

Even well-known companies have already acknowledged the power of technology, enhancing their customer services: 

• Shopify, for instance, is launching Shop, its ChatGPT-empowered app, designed to accelerate customers’ search inquiries and create personalized recommendations.

• Instacart, a grocery delivery and pick-up service provider, is integrating the technology to generate value-added content for users, like receipts or ingredient recommendations

• Finally, Amazon leverages the best of all worlds for multiple purposes: from order tracking and product recommendations to customer support for issues including but not limited to account management, payments, billing, and product information.

Given the massive investment and significant support from different industries’ leaders, the demand and offer for ChatGPT usage for customer service will only grow.

Behind the scenes: What’s ChatGPT?

So, what is this marvelous ChatGPT technology all about? What keeps it up? Let’s find out.

ChatGPT (where GPT stands for Generative Pre-trained Transformer) is an AI-powered application developed and introduced by OpenAI company in November 2022. 

ChatGPT leverages Natural Language Processing algorithms and is based on Large Learning Model (LLM) trained on massive datasets, with human supervisors for “teaching.” 

Given this, ChatGPT can read, summarize, and translate text to generate the content for the particular prompts. The technology provides human-like responses with a conversational flow close to a dialogue with a natural person – respectively, it’s also called Conversational AI. 

From those interactions, the technology learns even more. It’s like you are meeting and talking to a new consultant in your favorite shop, and soon they become your first-hand assistant.

And that is only the beginning.  

As of May 2023, when we write this article, Open AI has already released the new GPT-4 LLM that works as a foundation for ChatGPT, with 1 trillion parameters. 

Why does it matter? Now, the technology has even more capabilities to recognize complex patterns and biases in datasets. Simply put, the enlarged amounts of parameters significantly accelerate and improve the ChatGPT’s output for the given input query. Not to mention, the evolving learning capacity of models and the speed of this process. 

Chat GPT for customer service: Ready or not?

Since GPT-4 APIs became available for developers, businesses got a chance to alter and enhance their customer service with this up-to-date technology. But is the tech ready? Let’s see.

The technology’s capabilities

For now, ChatbotGPT can provide the following resources: 

The memory of previous users’ inputs during the conversation. When a customer engages with ChatGPT multiple times, the system can recall the previous conversation’s context and seamlessly continue where it stopped. Moreover, ChatGPT can use previous conversations to personalize its responses to customers. It can recall customer preferences, past purchases, and other relevant information to tailor its recommendations or solutions. This creates a more personalized experience that can increase customer satisfaction and build brand loyalty.

Training to decline inappropriate requests. The system can identify and suitably respond to requests that are inappropriate, harmful, or violate ethical guidelines. More specifically, ChatGPT can be trained using ethical guidelines provided by its developers and human reviewers. These guidelines outline what is included in such content. By incorporating them during training, ChatGPT learns to recognize and decline such requests.
Continuous learning from the interactions. By learning from the interactions it has with users, ChatGPT can improve its responses and provide more accurate and relevant information over time. ChatGPT can learn from its mistakes and refine its understanding by interacting with users and receiving feedback on their responses. Besides, ChatGPT can stay up-to-date with the latest information and adapt its responses to changing customer needs. It can learn new industry-specific jargon, product updates, or policy changes, and hence, provide relevant and current information to customers.

The technology’s limitations

Yet, some gaps may require greater attention and consideration:

Occasional generation of inaccurate information. While ChatGPT is a powerful language model, it has some inherent limitations that can lead to inaccuracies in its responses. ChatGPT is trained on a vast amount of data available on the web, and its responses are based on patterns and information found in that data. However, there might be not so reliable sources, so inaccuracies or misinformation can be present in the training data. 

You probably already know about the case when ChatGPT provided links to websites with pirated content on the second attempt. And this is still happening. Here’s the screen from our writing team:

Unintentional generation of biased content. Despite efforts to reduce biases during training, ChatGPT may still automatically generate biased responses, which were previously learned from huge text datasets on the internet. If the training data contains societal, cultural, or gender biases, the model will learn and reproduce them in its responses. Biases present in the data can influence the language, recommendations, or decisions made by ChatGPT during customer interactions. At the same time, ChatGPT may lack context and rely just on statistical patterns rather than a comprehensive understanding.

Lagging with the updates. First of all, ChatGPT’s training data doesn’t extend further than September 2021. So it doesn’t have real-time information or awareness of events, updates, or changes that happened after that. Aside from that, information can change dynamically in customer service, including product updates, policy changes, or industry trends. ChatGPT may not have access to the latest information if it has not been included in its training data.

Every coin has two sides: pros and cons

It looks like ChatGPT and customer service might be the perfect match. Is it true? Let’s find out.

ChatGPT’s advantages for customer service

First, let’s look at the bright side of the moon. 

High speed of replies. ChatGPT can process and generate responses at an incredibly high speed. Consequently, it can provide real-time reactions to customer inquiries, significantly improving the customer experience. Furthermore, ChatGPT can handle a large volume of customer queries at the same time, reducing wait times for customers and enabling businesses to address customer needs more efficiently.

Human-like behavior. Due to its nature, ChatGPT can generate responses so well that it’s difficult to distinguish it from a real human. This allows customers to feel more engaged during their interactions. Also, you can program ChatGPT to recognize customers’ emotions, frustrations, and concerns, which provides empathetic reactions. Thus, ChatGPT engages customers in a natural and personalized manner, enhancing their overall experience.

Constant availability. Unlike human customer representatives who have such limitations as work shifts, breaks, and time zone differences, ChatGPT can operate 24/7, ensuring continuous availability for customers. Thus, customers can access support whenever they need it, regardless of the time of day or their location,  whether it’s during regular business hours, late at night, or even on holidays. It’s particularly valuable for businesses that operate globally or have customers spread across the world.

Higher customer satisfaction level. All advantages above combined significantly increase customer satisfaction, which in its turn leads to other, more feasible benefits. For instance, satisfied customers are more likely to become loyal customers, making repeat purchases and recommending the company to others, which will result in higher revenue and profits. Also, the churning rate will decrease. And last but not least, a high satisfaction level brings more reviews and feedback, which can improve a company’s reputation and attract new customers.

Disadvantages of the technology

The following are the challenges that still limit wider ChatGPT adoption for customer service.

Resource-consuming tech. As a powerful language model, ChatGPT requires significant computational resources to function optimally. Consequently, running ChatGPT at scale requires a robust and well-equipped infrastructure. Apart from that, bold integration of ChatGPT into the infrastructure is not enough – the model should be trained, tested, supervised, and fine-tuned. All of these require a significant amount of resources – human, time, and money.

Non-reliability. If the data that ChatGPT has been trained on is not diverse enough, or if the algorithm faces input that it has not been trained on before, it may generate irrelevant responses. This lack of reliability can damage customer experience and lead to dissatisfaction with the company’s services. Therefore, ChatGPT should always be accompanied by human agents who can support it when necessary.

Low customization out of the box. While ChatGPT is a powerful language model which can understand and generate human-like responses, it may lack the specific knowledge, context, or industry expertise required for a particular customer service scenario. Of course, it can be trained, but such customization will require a long time. With out-of-the-box capabilities, ChatGPT has a broad understanding of various topics and can engage in general conversations. However, it may not immediately capture the service details or company-specific information that is essential for delivering tailored customer support.

Lacking security of data. The technology still raises concerns regarding the privacy and security of sensitive information shared during conversations. For example, if the data stored by ChatGPT is not adequately protected, it could be vulnerable to unauthorized access and potential data breaches. This could result in exposing customer data, leading to privacy concerns and potential misuse of personal information. The world has already seen a huge leak of sensitive corporate data into ChatGPT from Samsung staff.

How to integrate Chat GPT into your business properly

We can agree that the technology is powerful enough to integrate it into various company systems. But such a crucial thing as customer service is no playground. Equally important is that ChatGPT, no matter how reliable it s, won’t work alone. 

Even at the present stage, it should rely on a company’s knowledge base and human staff that will supervise, lead, and correct it where necessary.

So the step-by-step implementation is another crucial aspect here. Let’s review it closer. To properly integrate Chat GPT into your customer support pipeline, it is important to:

Spot out common questions. There definitely must be the most frequently asked questions that your current or potential customers search for. These usually include more precise descriptions of the product/service features, personal account details, additional documentation, etc.

Use your knowledge base to “teach” ChatGPT. One of the greatest perks of ChatGPT is the possibility of enriching the model within the relevant niche to make answers and outputs more exact. So basically, you can use the company documentation and internal guides or train the LLM with customers’ inquiries and correct answers. However, the security of data becomes questionable in this case because particular parts of this dataset reside in OpenAI’s repository. Consequently, this may result in data leakage. 

Integrate the prepared ChatGPT into your chatbot. Once your LLM is drilled enough, you can incorporate it into your customer system (and chatbot, respectively). The NLP layer will handle the query/input and build the answer according to the ready dataset learning from the content resource, which is the knowledge base.

Test, refine, iterate. The finest results for ChatGPT in your customer service are only possible through constant testing. This process will highlight the need for model alteration or more accurate fine-tuning to your needs.

Get into Conversational AI with Unidatalab

Writing about ChatGPT and Conversational AI technologies, we can’t help but share our own experience from Unidatalab and how our solutions solve the technology constraints. 

As we mentioned, low customization is still a concern preventing businesses from integrating ChatGPT. The Conversational AI from Unidatalab found a way to resolve this issue.

Our technology leverages ChatGPT in a non-generic way. When a customer makes the input, the query first goes to a company’s database and its history of communication with other customers. These two elements together shape the contextual layer.  After the prompt goes through this context, it proceeds to ChatGPT and gives a customer the relevant answer.  

These are not empty talks. The Unidatalab R&D team has already delivered a Consulting bot for an e-Commerce business. 

A European company specializing in e-commerce sales was growing rapidly and faced an increasing demand for customer support resources. They asked us to develop an online consulting system addressing their problems, which would also help them retain current customers and gain new ones. Where we started, what were the challenges and processes, and what we achieved  – you can find all these details in our full case study. 

If you consider applying the power of Conversational AI – let’s discuss it!