ChatGPT has started a boom of Large Language Model (LLM) innovation. This new wave of Artificial Intelligence makes it easier than ever to have helpful, human-like conversations with machines.
Naturally, Customer Experience leaders have a vested interest in understanding how LLMs can improve their contact center.
Replicant has gathered data from hundreds of millions of customer interactions to become one of the first solutions in production using LLMs to deliver 90% resolution rates for customers.
This cheat sheet provides an overview of the key things CX leaders should know about LLMs like ChatGPT.
How can LLMs improve CX?
LLMs are essentially trained on the entire internet. With billions of parameters and exponential computing power, they can process and respond to almost any question naturally and informatively in fractions of a second. LLMs far outperform legacy chatbots in their ability to quickly and accurately identify customer intents from natural, unstructured questions.
What are the biggest CX limitations of LLMs?
LLMs are not without their risks. They are oftentimes more focused on providing an answer than providing the right answer. This can lead to hallucinations – instances where the LLM makes up words or actions if it doesn’t know exactly what to say – and inaccurate or inappropriate responses.
In addition, LLMs don’t have the security and compliance to be trusted with sensitive customer data or PII. For these reasons, contact centers should never connect customers directly with LLMs.
How can contact centers leverage the benefits of LLMs?
The power of LLMs are accessible through a reliable Contact Center Automation platform that prioritizes enterprise scale and the voice channel. A solution must have high-availability telephony, omnichannel, out-of-box integrations, conversation design, analytics, A/B testing and more.
Once these requirements are in place, LLMs can immediately increase call resolution rates, lower handle times, and accelerate time to value by cutting deployment times down to just weeks.
How does Contact Center Automation eliminate LLM risks?
Contact Center Automation platforms only rely on LLMs for specific tasks like intent recognition, not to provide answers directly to customers. They have guardrails in place to prevent LLMs from receiving customer information or any data that could be sensitive or private. This means that contact centers are always in full control of exactly how their machine will respond to customers and there are never any surprises.
What does an LLM deployment look like for CX leaders?
Leveraging LLMs in your contact center is as simple as deploying Contact Center Automation. As a customizable and scalable solution, CX leaders often begin by automating a single call driver (usually something common and high-volume like Account Management) and scaling to new use cases from there.
Once a use case is chosen, a solution is integrated into the necessary systems like CCaaS and CRM and conversations are customized to your brand. In a matter of weeks, a solution can be designed and deployed with up to 90% resolution rates on day one.