Conversational AI powers contact center tools like virtual agents and chatbots. It uses machine learning (ML) and natural language processing (NLP) to help customers and give them a great experience with a brand.
It powers channels such as AI chatbots or virtual agents. Artificial intelligence enables these tools to comprehend human language and conduct human-like interactions with customers.
For some callers, AI can handle their entire request. This frees up human agents to handle complex cases and enables calls to be instantly directed to an agent that can appropriately handle the call.
In 2023, the rise of ChatGPT and other open-source conversational AI has led to massive changes in the field. Understanding what these tools are and the changes on the horizon can help you better understand how to pivot your use of them and take full advantage of this exciting innovation.
What is conversational AI for contact centers?
Conversational AI is a general term for the engine that makes tools like AI-powered chatbots, voicebots, and virtual assistants usable for contact center agents. In short, it enables companies to deliver better customer service and acts as an invaluable support tool for human agents.
Shorter wait times and improved customer satisfaction results.
What is an example of conversational AI?
One example of conversational AI is a virtual agent.
You’re likely using one already but, in short, virtual agents are used by contact centers to provide 24/7 service to answer customer questions. They are especially helpful for frequently asked questions and basic account queries.
Unlike IVR systems, virtual agents can actually process and understand the context of what a customer is saying on the phone.
This allows them to identify customer needs quickly and accurately. From there, the AI can easily answer the question or route the customer to the most qualified, available agent.
With conversational AI, virtual agents can now provide much more natural, two-way dialogues while finding and solving customers’ problems. It now goes beyond basic, scripted answers to actually establish an intelligent, human-like interaction with your customers.
Conversational AI trends and statistics.
Conversational AI can be quicker, simpler, and easier than solving an issue with a human agent. In fact, 84% of CX professionals believe customers expect a 24/7 self-service option from brands. 80% of CX professionals also believe that AI can and will provide a better contact center experience for customers.
AI isn’t relegated to customer service, either.
Voice assistants, like Alexa, Siri, and Google Home are used by nearly half the US population. These assistants use conversational AI tech to answer questions and perform basic tasks – like making a shopping list, re-ordering your favorite products, or setting a reminder.
In 2020, many brick-and-mortar businesses were forced to adapt to e-commerce and a different way of offering customer service. This meant increasing their online presence and, for many, that also meant employing some of the newer technology that has advanced over the years, like AI-powered service options like chatbots.
Now, customers expect to see AI tools and chatbots on various social media platforms.
This, combined with the release of ChatGPT in late 2022, has led to the AI market size being set to $208 billion, with a projected growth of 46% in 2023. And companies that have recently adopted AI in their processes are already seeing significant cost savings and revenue upticks.
But what effect will this have on the daily operations of contact centers? And can you trust a conversational AI to care for your customers effectively?
How does conversational AI work?
Using technology such as natural language generation, machine learning, and natural language understanding, conversational AI can provide exceptional text-based or voice assistance.
Need an example? Let’s look at the steps that an AI chatbot takes to leverage conversational AI that’s been trained with company-specific keywords:
- Input generation—the customer either says or types their request.
- Automatic speech recognition (ASR)– allows the AI to break down the sounds it receives through your phone speaker and arrange them into words. The simplest version of ASR requires specific words to be spoken, while higher-level technology can accept normal human speech patterns, including slang and mispronunciation.
- Input analysis—natural language processing (NLP) cleans up the request so the artificial intelligence engine can understand it better. Natural language understanding (NLU) may be applied to enable the artificial intelligence engine to comprehend more nuances behind the request.
- Natural language generation—the AI engine formulates a human-like response and sends it back to the customer.
To fully understand these steps, you’ll need to familiarize yourself with some terms used in AI development, such as:
Machine learning is a key component of artificial intelligence. It means that the system can learn and improve itself over time, without a human needing to input additional information.
This process is based on pattern recognition. The AI engine uses neural networks to spot patterns in data and then provide outputs.
When setting up your customer service software, we help our clients identify and input keywords that are specific to their products, brand, and customers. The AI features then use that foundation to build upon. Over time, Talkdesk developers and data scientists review and will correct these outputs if they are off course. Then, the AI engine will gradually produce more and more accurate outcomes.
The initial human input—and later the correction—is what we refer to as training the AI.
This used to be a difficult, time-consuming, and expensive process. As AI has advanced, innovators at Talkdesk have created a way for the AI to learn on the job through our AI Trainer.
It uses human-in-the-loop (HITL) technology, which lets agents and supervisors engage directly with AI machine learning. It’s code-free and can be done in a few clicks. Sometimes, the agent simply needs to follow some on-screen prompts to help train the AI.
As a result, your AI tools stay highly accurate and fine-tuned to the changes that happen in your business, without the need to bring in AI data specialists for updates.
Natural language processing (NLP).
Natural language processing enables AI engines to pull words from a text or voice-based conversation and interpret meaning. It uses the literal meanings of each word, along with context-driven insights.
For example, the word “free” could refer to something that is received at no cost (i.e. is the product demo free?), or it could mean that someone is available during a certain time (i.e. I am free on Tuesday at 10 a.m.).
NLP empowers conversational AI to tell the difference between these two situations.
Natural language understanding (NLU).
Natural language understanding is a subset of natural language processing. While NLP can categorize what the customer is talking about in a general sense, NLU goes deeper.
It can understand the sentiment, deep context, semantics, and intent of the request.
As an example, say a caller tells a Talkdesk virtual agent that they’re calling in to claim a free product. NLP would allow the AI to understand that by “free”, the caller means “no cost”. NLU would kick in to scan the system for any free product offers that are relevant to the customer on the phone, walking the user through the steps needed to claim their product.
Talkdesk’s integrated AI might also direct that caller to a live agent, automatically providing the information they need to present a relevant offer. And it happens right in the agent’s Workspace application.
NLU is built to overcome obstacles such as mispronunciation, sub-optimal word order, slang, and other natural parts of human speech. As NLU systems advance, they’re even beginning to understand nuances like sarcasm to reduce the possibility of misinterpretation.
Automatic speech recognition.
Conversational AI doesn’t actually pick up on full words. These are too complex to handle, especially over the phone, when you may be dealing with static, background noise, or other interference.
So how does it come up with an appropriate response to normal speech?
The AI breaks down the soundwaves it receives into phonemes—small, distinct sounds that differentiate one word from another. English has 44, including, for example, the “p”, “b”, and “th” sounds.
Automatic speech recognition is what allows conversational AI to distinguish between “pat,” “bat,” and “that” with impressive accuracy.
Five benefits of using conversational AI in your contact center.
As AI technology grows, so do its benefits.
Think of IVR systems, which have made human operators all but obsolete for part of the customer journey. It’s simply quicker, easier, and cheaper to set up an IVR menu than it is to require all callers to wait for a live operator.
These and other benefits make conversational AI transformative for contact centers, optimizing the way they interact with customers.
1. Save time for customers and agents.
In a perfect world, your customers would never have to wait for an agent. Their issues would be resolved accurately and efficiently in a single call, and they could get help on their schedule, even if it’s outside normal business hours.
Running a contact center of human agents to meet this standard would be unrealistically costly and most likely impossible.
With conversational AI, however, you can.
And you can provide better support to your human agents in the process. On a call, internal tools like virtual assistants can pull up relevant shortcuts and next steps in real time. Afterward, ChatGPT technology provides features such as automatic summary that decrease wrap-up time and increases the accuracy of your agents’ notes.
2. Increase customer satisfaction.
Conversational AI and virtual agents create a streamlined customer experience and increase customer satisfaction ratings.
The call queues are shorter, due to AI’s capability to handle simple requests, while virtual assistants give real-time support to agents who are actively on calls, helping them find solutions faster.
3. Improve customer engagement.
Conversational artificial intelligence tools enable customers to locate relevant information, without having to spend time on the phone with an agent. This improves their opinion and sentiment toward the brand.
When a company provides helpful, efficient tools to customers, they are more likely to enjoy the brand and increase their engagement. This leads to a lower customer churn rate and higher referrals or positive reviews.
4. Enhance information accessibility to customers.
Accessibility limits can strain any customer’s relationship with a company. Customer service that’s only available in certain languages, at certain times, or via certain channels can shut entire sections of your customer base out.
A conversational AI bot is easy to reach at any time of day and can be organized to be available through a number of voice and written channels. You can even set up multilingual chatbots at a fraction of the cost that it would take to run multiple contact centers in different languages.
Virtual assistants can make the next best steps for your live agents clearer to prevent mistakes, and even send reminders to your customers to take time-sensitive actions.
5. Close sales 24/7.
Rather than wait for an agent to schedule a call for a sale and onboarding, conversational AI allows your customers to buy the moment they’re ready to.
Your AI can answer questions, offer suggestions, and even help users determine the best solution for them within your product or service line.
The gap between being ready to buy and having the chance to buy is a massive conversion killer. AI closes this gap by being available 24/7 and simplifying the sales process.
Final thoughts on conversational AI.
AI technology doesn’t just have the ability to transform call centers in the future—you can start using it today.
Many contact centers have relied on automation tools like the touch-tone or speech-based interactive voice response for several years. But, while they are important, traditional IVR lacks a good flow of conversation.
On the other hand, conversational AI tools—like AI chatbots and virtual assistants—facilitate helpful, human-like conversations and responses that can help both customers and agents. Some companies immediately see value in using the virtual assistant as a modern version of the IVR by integrating it with the existing IVR routing engine.
Talkdesk Virtual Agent™ leverages conversational AI technology, to provide 24/7, personalized support to customers. It not only uses powerful artificial intelligence technology but also includes human-in-the-loop training, to give your virtual agent a headstart when it comes to understanding the needs of your unique customer base.
Ready to drive a better customer service experience with conversational AI?
Request a demo to see the Talkdesk Virtual Agent today.