6 use cases for generative AI in customer service

Generative AI is sparking innovation in many areas and the contact center is no exception.  

In customer service, generative AI can predict customer needs, enabling proactive and tailored support. It can auto-generate customer replies, assist agents in real-time as they engage with customers, automate notetaking and summarization, and even develop personalized training materials for agents.

In this article, we’ll explore six innovative uses of generative AI in customer service, and we’ll examine the benefits of using generative AI, from improving efficiency and accuracy to enhancing personalization and customer satisfaction.

Six generative AI uses for customer service.

1. Automatic summary to reduce after contact work time.

Generative AI effectively summarizes interactions, significantly reducing after contact work (ACW) time.

A prime example of this is the Talkdesk feature automatic summary. Powered by generative AI, it summarizes the topics discussed during an interaction, saving valuable time and providing crucial information follow-up conversations with the same customer.

Automatic summary allows agents to spend less time on administrative tasks and more time delivering exceptional customer service. In fact, it has been shown to shave 30-60 seconds off after call work.

2. Using generative AI for sentiment analysis.

Sentiment analysis involves analyzing customer interactions to understand their emotions and sentiments. When powered by generative AI, sentiment analysis allows you to see the hidden layers of customer communication, such as cultural nuances or ambiguities, giving insights into how they feel and what they want.

Talkdesk Interaction Analytics™ is a prime example of this technology in action. It leverages generative AI to capture, transcribe, and analyze every customer interaction. It identifies key conversation moments, topics, and sentiments helping businesses understand customer intent more clearly. With this information, businesses can uncover trends that lead to improved customer experience.

But Talkdesk Interaction Analytics doesn’t just review customer conversations for topics and sentiment trends; it goes a step further. With generative AI, it detects emerging topics, uncovering valuable insights and opportunities—even unexpected ones. It empowers businesses to not only understand customers but also anticipate their needs and deliver truly exceptional customer experiences.

3. Leveraging generative AI for virtual agents.

Instead of responding with generic, pre-programmed responses, generative AI allows virtual agents to understand the context of the conversation and respond naturally and conversationally. This results in interactions that feel less like a conversation with a machine and more like a conversation with a human.

Talkdesk Virtual Agent handles common customer queries like orders, returns, and billing. If complex cases require empathy and expertise, the virtual agent seamlessly redirects customers to a human agent. This results in a faster, frictionless customer service experience.

4. Responding to reviews with generative AI.

Responding to customer reviews promptly and appropriately is crucial for maintaining a positive brand image. When customers take the time to leave a review, they’re providing valuable feedback about their experiences with your business. Responding to these reviews shows you value their feedback and demonstrates your commitment to customer satisfaction.

Generative AI enables automated responses to customer reviews, ensuring timely answers while freeing up valuable time for customer service agents. It doesn’t just churn out generic responses but uses the information in the review to generate a personalized response.

For example, a customer praises your fast delivery service. The AI system could respond by expressing gratitude for their positive feedback and reinforcing your commitment to maintaining this efficiency level. 

“Thank you for recognizing our fast delivery service! We’re thrilled to hear you had a great experience. Your feedback encourages us to continue working hard to ensure all our deliveries are as prompt as yours.”

On the other hand, if a customer complains about a faulty product they received, the AI could express regret for their negative experience and assure them that immediate steps are being taken to resolve the issue. 

“We’re truly sorry to hear about the faulty product you received. We understand the disappointment it has caused, and we’re taking immediate action. Our team is arranging for a replacement to be sent to you as soon as possible, and we’re reviewing our quality control processes to prevent similar issues in the future.”

5. Applying generative AI to knowledge bases.

Solving customer queries quickly and accurately has a major impact on customer satisfaction. The longer a customer waits for a resolution, the less satisfied they will be. And accuracy is crucial—if a customer has to call back because their issue wasn’t resolved the first time and gets a different answer, it leads to frustration and a negative perception of the brand.

Generative AI powers knowledge bases to provide agents with quick and accurate information during customer interactions. The AI system understands the context of the customer’s query and provides the agent with the most relevant information.