Generative AI in Customer Service: 5 Ways It's Changing the Game


In 2023, the question isn’t whether your business is leveraging Generative AI; rather, how? Marketing, sales, customer service, human resources, and several other functions can use Generative AI to become more efficient and innovative, and make tangible impact in their roles.

Let’s take customer service, which is the focus here:

Traditional AI is like a chess player predicting their opponent’s next moves. It offers customers quick service but has certain key limitations: lack of contextual understanding, lack of natural language processing (NLP) capabilities, poor or complete lack of personalization, lack of human touch, limited learning and adaptation, among others.

One reason is that traditional AI relies on predefined rules and algorithms to make decisions and process data. Generative AI, on the other hand, is more creative as it’s powered by large language models (LLM) that are pre-trained on large volumes of data and help in the creation of original and diverse content.

Generative AI is inherently capable of engaging in real-time conversations where it can offer personalized responses and adapt to various user inputs. Also, as it excels in contextual understanding of a conversation or query, it’s able to respond more accurately and coherently, enhancing the user experience.

Let’s look at five ways Generative AI in customer service is proving to be a game-changer:

1) Pull Information Directly from Web Pages

Let’s say, a customer wants to change an address that’s listed on their account. They could ask a Generative AI Assistant how to update this account information and get appropriate instructions. 

This is an example of how Generative AI helps with instant query resolution.

Here’s how it works: once the customer asks the bot, it searches for help center articles with instructions to update account details. Rather than asking the customer to find the necessary information, the bot generates a summary of the information and provides precise instructions to help the customer edit the address.

Thus, by connecting the AI Assistant to the help center, knowledge bases and FAQ sections, it gets instant access to the latest information, which it shares with the customer upon inquiry.

With Contakt, by Haptik, enterprises can build an AI Assistant using unstructured data sources (PDFs, CSVs, FAQs, blogs, websites, and more) and deliver end-to-end customer experience at scale, improving customer satisfaction and winning loyalty.

2) Effortless Ticket Summaries and Tailored Responses

Another fascinating capability of Generative AI in customer service is its ability to summarize support tickets and auto-populate them with relevant information with no manual effort.

Moreover, it can analyze the sentiment of a customer’s query and understand whether they are satisfied, frustrated, or feeling neutral. This enables support agents to send tailored responses and resolve queries faster and more efficiently.

3) Transform Call Center Operations with Data and Insights

Generative AI in call centers improves the feedback loop by analyzing and summarizing large volumes of data from customer interactions, agent performance metrics, and more. This helps drive data-driven decision-making, deliver personalized customer support, and improve processes. Call centers can gain valuable insights from identifying trends and patterns in customer queries, agent responses, and overall performance, and use them to streamline operations and alleviate costs. 

Insights also help improve customer experience and drive customer satisfaction, which contributes to business success, growth, and revenue generation.

4) Reinforce Customer Relationships with Personalized Responses

Large language models have the capability to remember context from previous customer interactions. This allows support agents to send personalized responses to customers, reinforcing the customer-brand relationship.

Contextual understanding driven by LLMs helps iterate on customer responses until they are completely on-brand. Agents can use this capability to provide feedback and fine-tune AI’s suggestions to ensure the responses are in line with the brand’s guidelines, and accurately represent the voice and values of the company.

5) Proactively Support Customers and Trigger Loyalty

Customers appreciate when businesses go out of their way to anticipate customer needs and address them even before they arise. In fact, according to a study, 72% of customers reported high satisfaction levels when they were offered proactive support. 

Generative AI’s predictive capabilities help improve customer support by using data-driven insights to preempt customer needs and deliver personalized experiences that drive customer retention and loyalty.

Moreover, proactive support helps reduce call center tickets and ensure a hassle-free customer experience.

The Takeaway

Generative AI is a key asset in delivering unparalleled customer service and unlocking customer satisfaction and loyalty. However, while Generative AI in customer service makes it all the more efficient and intuitive, it’s important to be aware of possible misinterpretation or bias in AI-powered responses. This will not only maximize the potential of the disruptive technology but also ensure that accuracy and fairness in responses are retained.