Simple to Advanced Use Cases of Large Language Models (LLMs) in Contact Centers

LLMs can generate a large amount of human-like text without being explicitly programmed. Further, they can be fine-tuned according to specific needs or use cases. This is an exceptional skill and widens what can be automated at an organization. It is due to this skill that makes AI tools like ChatGPT, DALL-E unique & powerful, and our very own platform, Floatbot which is propelled by the powerful influence of Large Language Models (LLMs).  

LLM’s versatility and extensive range of use cases have solidified their role as the driving force behind numerous innovations. 

With this potential, it's no surprise LLMs are more than just a technology leap in contact centers.  

Addressing customer queries, performing sentiment analysis, helping human agents, and identifying customer patterns, the use cases of LLMs in contact centers range from simple to advanced. LLMs can automate, optimize, and streamline a lot of tasks that require human agents. Ultimately, this reduces wait times, increases customer satisfaction, enables round-the-clock support, and drives efficiency in customer resolution. 

In a nutshell, LLMs are an asset for your contact center regardless of the industry you’re operating in. 

The Modern Customer Service and Large Language Models

Customer service is evolving. Businesses and their contact centers are no longer relying on human agents to handle customer interactions. Not with the emergence of large language models. And, according to a survey, about 95% of global customer service leaders expect their customers to be served by an AI bot at some point in the future. This high percentage draws noteworthy attention to the benefits of LLM AI.  

This does not imply the decline of human agents; it just means that the agents are now able to focus on high-priority tasks that truly require their attention.  

While customer service has evolved, so have customer expectations. Providing round-the-clock support in different time zones and being available consistently on multiple touchpoints are critical customer expectations. Originally, the omnichannel approach involved siloed and disconnected mechanisms with a heavy reliance on human agents. But with LLMs, that has changed. Firms are able to provide customer support on multiple channels, 24/7 with precision. 

By automating routine customer interactions, LLMs can significantly reduce operational costs.  

LLM Use Cases in Contact Centers

LLMs come with a lot of advantages. But one that needs special attention is their ability to quickly understand and adapt to what customers need, especially when those needs change. This means you won’t need to keep shelling out money for ongoing training and assistance because a purpose-built LLM can handle this all by itself.  

With these advantages, it’s safe to say large language models are the future of contact centers. 

Now, let’s take a closer look at the simple and advanced use cases for LLMs in contact centers. 

THE SIMPLE USE CASES OF LLMs FOR CONTACT CENTERS 

Search Knowledgebases

With LLMs, agents no longer have to tediously go through vast amounts of data to identify accurate information to address customer queries. This addresses two major customer support concerns – resolving issues in the first call and decreasing the average time spent on each call. It’s a win-win situation for both the customer and the human agent. 

Provide Personalized Recommendations

Based on past purchase history and online behavior, LLMs can provide recommendations and offers to customers. This helps personalize the buying experience for them, boosting sales and retention rates. LLMs need minimal data to discover the likes and dislikes of a customer and connect two completely unrelated subjects to provide creative recommendations. 

Automate Customer Support

With cognitive search and self-learning abilities, LLMs are great at troubleshooting customer issues. They can quickly provide accurate solutions and if the issues require human assistance, the conversation can be seamlessly passed on to a human agent.  

Streamline Customer Onboarding

LLMs act like virtual guides providing clear instructions to customers to ensure a hassle-free onboarding process. From doing identity verification to gathering feedback, they navigate customers through each step. Additionally, LLMs can enable voicebots to optimize the process even more for customers.  

Create Context-Aware Conversations

LLMs remember past conversations. This helps in enabling context-based interactions to resolve issues quickly for the customers. If a customer poses a complaint regarding a product and returns a few weeks later regarding the same issue, the support team has access to previous conversations.  

THE ADVANCED USE CASES OF LLMs FOR CONTACT CENTERS

Enable Multi-Turn Conversations

Multi-turn conversations are nothing but a back-and-forth communication between the user and the LLM. The user puts forth an input, the LLM responds, and this exchange can continue until the customer’s issue is resolved. The ability to maintain context and coherence in a conversation is one of the key advantages of LLMs.  

Create Task-Oriented Virtual Assistants

LLMs are not one-dimensional. As a result, you can create unique virtual assistants that can perform different tasks - booking appointments, automating customer support, processing transactions, providing product information and recommendations, and the list goes on. Their multi-faceted foundation simplifies tasks for both customers and businesses. 

Perform Sentiment Analysis

LLMs have a great grasp on understanding complex sentences and linguistic elements which are crucial for sentiment analysis. Based on the context and relationships between words, LLMs can determine if the sentiment expressed is positive or negative.  

Provide Predictive Analytics

As previously said, LLMs have the ability to follow past transactions and browsing habits in order to project future patterns and behaviors. When properly applied, this data may support the development of successful marketing campaigns, improve consumer segmentation tactics, and ultimately increase the organization's level of profitability. 

Closing Thoughts

LLMs can understand different customers' intents and respond accordingly. Companies are recognizing the potential of LLMs and incorporating them into their contact centers to gain a competitive edge. In the coming years, expect to see LLMs become even more common in contact centers as they continue to evolve and improve. As LLMs become more dependable for businesses, developers and researchers are bound to find new ways to use them that were previously hypothetical. 

Floatbot is trusted by multiple contact centers across various industries and sectors for their ongoing needs. Whether you want to provide self-service agents, automate FAQs, generate leads, or handle complex queries, we have solutions that seamlessly integrate into your workflow. Our platform is scalable, secure, and affordable.  

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