Living Large with AI: The Rise of Large Language Models (LLMs)
Each and every customer interaction is not only to provide an excellent customer experience, but also a chance to learn more about customers and their unique needs. Large language models (LLMs) help unlock these possibilities and more. But what are large language models exactly?
What Is a Large Language Model?
A large language model is an artificial intelligence that has been trained on a massive amount of language data with a high parameter count. The data can come in the form of customer interactions, support tickets, chat logs, or any other form of textual data. As for parameters, Techcrunch defines them as “a value the model can change independently as it learns.” Models with more parameters are more reliable than those with fewer.
The advantage of using a large language model is that it can be trained to recognize and understand a wider range of linguistic patterns than other models. As a result, it can provide more accurate and nuanced translations, identify customer needs more effectively, and provide more accurate recommendations.
Another recent article from Forbes defines large language models this way: “LLMs are usually very large (billions to hundreds of billions of parameters) deep-neural-networks, which are trained by going through billions of pages of material in a particular language, while attempting to execute a specific task such as predicting the next word(s) or sentences. As a result, these networks are sensitive to contextual relationships between the elements of that language (words, phrases, etc).”
This technology allows contact centers to use artificial intelligence and machine learning to predict customer needs and provide a more personalized customer experience, since large language models can be used to process huge amounts of data in real-time, allowing contact centers to better understand customer needs and preferences. It is now also possible to identify a customer’s intent, as today’s technologies can make use of NLU (natural language understanding), which goes beyond word-by-word transcription to establish the customer’s objective or concern during their inquiry to the call center.
In a contact center, large language models make it possible to quickly and efficiently analyze customer interactions and extract insights that can help agents provide better service. With this technology, your contact center can:
- Detect recurrent customer issues
- Identify areas where your customer service could be improved
- Recommend products or services that might be of interest to customers
The future of contact centers is exciting, and large language models are a key part of it.
Three Practical Applications for Contact Centers
By leveraging large language models and AI, you can improve customer service in contact centers. Here are a few examples:
- Predictive call routing technology can use a caller’s speech patterns to match them to an agent best able to handle their issue.
- Interactive Voice Response (IVR) systems can use speech recognition technology to address customer queries before they even reach an agent.
- Using AI, call centers can route calls faster, enabling customers to get the help they need sooner and with better results.
In the future, AI will only become more ubiquitous in call centers. As the technology continues to develop, more and more contact centers are using AI to improve customer service. Increasingly, companies are exploring how they can leverage AI in their own contact centers. By doing so, they can not only stay ahead of the curve and provide their customers with the best possible service, but also ensure they remain competitive, as their competition begins adopting AI solutions as well.
Troubleshooting and Tuning for Optimal Performance
There also exists the ability to use language models to troubleshoot and tune performance in contact centers. Language models can be used to help identify problematic areas in conversations between customer service representatives and customers. This allows you to optimize the customer experience by swiftly resolving issues before they become bigger problems.
The ability to accurately detect and analyze customer feedback is critical for staying ahead of customer needs. Large language models allow you to identify the nuances, tones, and emotions from customer interactions so that you can tailor the experience even further. With the help of these models, contact centers are better equipped to handle difficult customers and difficult situations more effectively.
What’s Next? Large Language Models for Contact Centers
One of the biggest advantages of using large language models for contact centers is that they can quickly learn and adapt to changing customer needs. This means that you won’t have to constantly pay for additional training and support, as a purpose-built language model can do this autonomously. Plus, LLMs can even be used to provide personalized customer service, as they can recognize different user intent and respond accordingly. Large language models also allow you to quickly scale your contact center operations with minimal effort. With these advantages in mind, it’s clear that large language models are the future of contact centers.
With an automated contact center, businesses can solve problems faster and provide more accurate solutions. Businesses that invest in large language models now will have a strong foundation for success in the future.
Conclusion
The contact center’s goal is to provide the best customer experience possible. The contact center thrives if it can predict customer needs and desires, and then respond thoughtfully, accurately, and quickly. A large language model can help significantly with this because it utilizes massive quantities of data. Contact centers utilizing LLMs are able to provide a better customer experience while reducing costs and improving their overall efficiency and accuracy.nnLearn more about AI-powered solutions like these for your contact center. Schedule a demo with Level AI today.
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