What is Conversational AI?
Conversational AI, or conversational Artificial Intelligence is the technology allowing machines to have human-like conversational experiences with humans. It refers to the process that enables intelligent conversation between machines and people.
Along with understanding what conversational AI is you should also be familiar with operational AI and its function within customer support.
AI for operations, or operational AI, often means using natural language processing to automatically tag and triage incoming customer inquiries, building more accurate demand forecasts, routing and distributing workload optimally among teams, and empowering agents with recommended knowledge and responses.
AI for conversations, or conversational AI, typically consists of customer- or employee-facing chatbots that attempt a human conversation with a machine.
Operational AI helps perform an operation or a function that allows for knowledge intake, while conversational AI helps with the back-and-forth between customers and agents for any customer support interaction.
AI for operations and conversations eventually have to work together to make the entire customer support process successful for both agents and customers. Operational AI can help triage and label tickets while conversational AI can carry the back and forth between customers and the company.
What Are Chatbots?
A chatbot is a computer program that simulates human conversation, either via voice or text communication. Organizations use chatbots to engage with customers alongside more classic customer service channels such as social media, email, and text.
In customer service, companies use chatbots to boost agent productivity while enhancing the customer experience to make for happier customers who are satisfied with what you can offer.
There’s a big difference between a chatbot and genuine conversational AI, but chatbot experiences can differ based on how they function. Traditionally, chatbots are set to function based on a predetermined set of if-then statements and decision trees that give answers based on keywords. That is a rules-based chatbot.
Chatbots vs Conversational AI
The main difference between Conversational AI and traditional chatbots is that conversational AI has much more artificial intelligence compared to chatbots. Basic chatbots were the first tools to emerge that utilized some AI technology. These days there are chatbots that leverage natural language processing and machine learning to understand what a user is searching for and to have conversations with customers where the machine is returning humanlike responses.
The problem with traditional chatbots is they aren’t built with trueAI. This is because they are rule-based and don’t actually use natural language understanding or machine learning. You only get an answer if you put in what the chatbot is searching for. When it comes to customer support, chatbots just aren’t enough to truly meet the needs of customers.
Are Chatbots and Conversational AI The Same?
Traditional chatbots and conversational AI are not the same. Chatbots are not true artificial intelligence because they function based on if/then statements and decision trees. True AI does not rely on human effort to create decision trees for incoming support queries to then try to answer queries based on keyword matching. Conversational AI offers more of the true AI experience since it is not trying to match human language with a keyword.
With a chatbot, you’d have to be exact with your verbiage in order for the machine to give out the answer you’re searching for based on user inputs.
Consider the scenario of a chatbot used by an e-commerce company. One of the most common questions customers will ask about is the status of their shipment.
If you ask the chatbot, “Where is my package?” then you’ll get an exact answer depending on how the decision tree has been built out. But what if you say something like, “My package is missing” or “Item not delivered”? You may run into the problem of the chatbot not knowing you’re asking about package tracking.
A better customer experience would be a chatbot that is powered by conversational AI that actually learns from the input being given and produces an answer based on analyzing the incoming customer queries and using contextual awareness. True AI will be able to understand the intent and sentiment behind customer queries by training on historical data and past customer tickets and won’t require human intervention. This form of a chatbot would understand what is being asked based on the sentiment of the message and not specific keywords that trigger a response.
With the proper AI tools, messages that don’t explicitly say, “Where is my package?” will still be understood to be asking the location of an item. This goes a long way for many scaling customer support teams and enables them to automatically deflect incoming customer queries with artificial intelligence while still maintaining high customer satisfaction.
Chatbot vs. Conversational AI: Examples In Customer Service
We’ve seen artificial intelligence support automated answers to customers’ most asked questions. Whether customers are getting help from knowledge base articles or from a chatbot that automatically sends a response, AI is making these solutions possible.
Chatbots and conversational AI tools are not the same thing. Basic chatbots rely on pre-determined decision trees that require exact keyword matching to return the right output for the given customer input.
Conversational AI makes great customer service possible by understanding the customer’s sentiment and intent and allows it to provide a quicker resolution for the customer, regardless of how they ask their question.
If you’ve ever tried to seek out customer support, then you’ve likely come in contact with both typical chatbots and conversational AI.
Chatbots for customer service, as mentioned, sit on the front of a website and allow customers to speak with an artificial agent to solve simple inquiries. Repetitive questions that companies see everyday are handled well with a chatbot since support teams can manage incoming customer questions better and answer them efficiently. Complex customer issues is where things get tricky.
Because customer expectations are very high these days, customers become turned off by bad support experiences. These days, customers and brands say they care more about the customer experience than ever before, so it’s important to have the right tools in place to bring those positive experiences to fruition.
With the help of conversational AI, you can improve customer interactions within your support system.
A chatbot powered by conversational AI can level up your support process. Conversational AI chatbots don’t require you to ask a specific question, and can understand what the intention is behind your message. You can think of this process how you would think a digital assistant product would work.
When you ask Siri or Alexa, “What’s the temperature?” or “Is it cold out?” that program is working through algorithms to tell you what the weather is for the day. It’s looking for the intent of the message and pumping out the correct information.
So when customers ask a conversational AI bot a question that sounds a little different than previous questions it has encountered, it can still figure out what they’re trying to ask.
Creating a conversational AI experience means you’re working to improve the customer experience for the better.
If a support organization wants to ensure that they’re creating the type of experience that makes a customer feel like their needs are understood whenever they seek support, then it’s absolutely critical to implement a tool that understands the intent, sentiment, and tone of the customers. A traditional chatbot just can’t get the job done.
So if the experience you put your customers through matters more to them now than the quality or price of the product or service you offer, what are you doing to improve that experience?
With AI tools designed for customer support teams, you can improve the journey your customers go through whenever they need to interact with your business.
Companies like Route have found solutions to their support issues with the help of customer support AI, making it possible for their support teams to deflect up to 40% of support tickets with automated workflows that serve customers right away.
By 2035 AI technologies are projected to increase business productivity by 40% and you should join along for the ride!
With CX playing such a large part in what companies offer, the time to strategize and improve yours is now.
You can make the most of your strategy by looking into customer support AI solutions. AI solutions like those offered by Forethought are powered by machine learning and natural language understanding that can learn from your data and understand the intent of a customer inquiry.
If you’re interested in learning more about the intricacies behind operational AI and conversational AI, check out our webinar that features Alan Pendleton and Seth Earley, leaders in the CX and AI spaces. They have a lot more to say about the power of AI for conversations and operations.