Multi-turn conversations are more human-like interactions with AI than simple "question and answer" single-turn conversations common with the earliest conversational AI assistants.
What are multi-turn conversations, why do they matter, and why do they make all the difference in optimizing customer service and maximizing customer satisfaction?
What are multi-turn conversations?
In a multi-turn conversation, the AI system maintains a context of the ongoing dialogue, allowing it to understand and respond to subsequent user inputs more accurately.
In a conversation, a turn is a single back-and-forth where one person says something, and the other responds. In linguistics, this is known as an utterance, but in AI, this is known as a turn.
In AI, a single turn is much like a virtual assistant. For example:
Conversely, with its natural flow and multiple utterances, a multi-turn conversation makes the interaction between the user and the AI more comfortable and intuitive.
This could look like:
The importance of context in multi-turn conversations
So why are multi-turn conversations such a big deal?
For example, a customer service problem mightn't be solved in just a single conversational turn.
Sometimes, a solution means that a customer has more questions, given that new information has been given. To understand follow-up questions, the AI needs to remember the context of the conversation, or the user has to provide all the context again in a single turn.
In our first example about the weather, if you asked, "And tomorrow?" the AI wouldn't likely understand. You'd have to ask, "What will the weather be like tomorrow?".
AI can understand requests within the context of the current conversation and allows users to speak far more naturally with AI assistants, voicebots, and callbots. In AI, this is known as "context retention".
Regarding development, there's quite a difference between AI capable of multi-turn conversations and single-turn conversations. Like many aspects of AI, very natural and human-like interactions are some of the most challenging to replicate.
In human conversations, we remember the context and the information given to us, which is why personal pronouns can work as we remember who we're talking about.
Why are multi-turn conversations important for customer service?
When using AI for customer service, the efficiency of multi-turn conversations can completely change the customer experience, making it more productive and effective.
AI capable of multi-turn conversations allows customers to speak more naturally with AI agents without providing all the context again.
This means customers don't have to go through every detail individually in a series of single-turn conversations. Instead, the AI can remember information provided early and even request missing information, considering what's happened.
Users don't like following a script provided by AI using single-turn conversations; instead, being able to contextualize information through multi-turn conversations provides more natural conversations.
Multi-turn conversations allow users to interrupt the AI, provide information or alter it while the AI is speaking, or even return to a previous conversation after answering a new request.
This adaptability of AI in multi-turn conversations provides users with a sense of convenience and flexibility.
Using multi-turn conversations, even buying movie tickets is much easier. Unlike the old automatic ticketing systems, where the user would have to go through the purchase process following the script, they can now make their request very naturally.
- “Hi, I'd like to buy two adult tickets for the latest Marvel movie this weekend at 7:00 pm”.
The AI can then ask for missing information, such as:
- "For the screening on Friday, Saturday, or Sunday?"
How conversational AI handles multi-turn conversations
It may sound evident to our human brains, but retention is essential to ensuring that conversational AI can handle multi-turn conversations.
Thanks to context retention, conversational AI remembers the conversation history, using the information provided to it to generate more appropriate and relevant responses.
However, there's a big difference between context retention and automatically understanding user intention. After all, language can sometimes be vague, and it's good for users to remember to contextualize requests if they could be misconstrued.
When a conversational AI lacks enough context, it can produce awkward and inaccurate responses. Depending on the AI's accuracy, the more turns a conversation has, the more accurate or inaccurate it can become.
Accurate AI solutions, like YeldaAI callbots, will become more accurate with each turn in the conversation. This is incredibly important in customer service, where people want fast and accurate solutions to their problems rather than just general solutions.
Consider using multi-turn AI for your customer service today!