AI has evolved over the years and is becoming more and more valuable. As a result, many businesses are now investing in AI.
WHO being used by businesses to improve customer experience as well as employees working at the company. Not only can AI cut down on the time it takes customers to get help, especially when AI can make quick arrangements, such as changing or canceling a reservation, but it can also help your staff save time. Valuable time can be spent on other tasks.
By 2026, the conversational AI market is expected to reach 18.6 billion dollars. Not only is it growing rapidly, but more than half of companies believe conversational AI is disrupting industries and believe that their competitors will most likely implement such technology.
As you can see, conversational AI is becoming an important part of many businesses marketing strategy and customer service.
Understanding conversational AI and implementing it in your business is essential, which is why today we’re looking at the ultimate guide to conversational AI in 2022.
What is conversational AI?
Conversational AI is like an upgraded version of a simple chatbot. It is used to send automated messages and chat between computers and humans. It’s still a chatbot but can have a more human-like conversation.
They can communicate like a human by understanding the intent of sentences and then responding in a text that simulates human text. The idea is to use these chat chatbots to interact with customers and make them feel like they are talking to a real human.
This allows them to feel more important and their experience is personalized.
One chatbots are also faster and can solve smaller problems that may take longer for humans to respond to and fix.
Chatbots: Who Invented Them?
ELIZA was the first recorded chatbot in the history of computer science in 1994. It was created by Joseph Weizenbaum at MIT. Here, the term “Chatterbox” was created.
ELIZA worked by recognizing keywords or phrases from the input and then using those keywords to send back a preprogrammed response. Obviously, this means that ELIZA is not very personalized and often gives the same response to different phrases or sentences.
For example, if you mention your family, such as, “My father is a fisherman,” ELIZA will respond, “tell me more about your father.”
ELIZA recognizes the word “father” and has an automatic response associated with that word. So whenever the word “father” or “father” is written, it will provide the same answer.
Tell me the difference between conversational AI and a traditional chatbot.
It is easy to confuse Conversational Ai with a regular chatbot, but there are enough differences to separate them from each other.
Conversational AI is at the core of what makes chatbots and virtual assistants so popular.
Conversation AI uses machine learning to allow it to analyze and understand what humans are writing. From there, it can generate a response that corresponds to the user’s text.
Chatbots can use conversational AI, but there’s a lot that doesn’t. For example, basic chatbots often use predefined or programmed responses with rules instead of AI deciding the answer.
Conversational AI is not rules-based and chooses to respond according to the context and intent of the user to respond.
A recent study shows that by 2030, the conversational AI market will reach $32 billion. It is currently being invested by a lot of companies with no end.
How does conversational AI work?
Conversational AI uses a structured platform that can send individual outputs depending on the input.
Using machine learning, conversational AI can continue to learn and expand the range of queries it can successfully answer or respond to. This is because every time a user talks to the AI, it can check the context and intent of the user’s response, thus learning new questions that may require similar answers.
It seems simple at first, but machine learning is much more complex than questions and answers. Therefore, there are correct AI structure is important.
Here are some of the key components that make up conversational AI’s natural language processing.
- Machine Learning (ML). Machine learning is the part of AI built around algorithms and datasets that are constantly evolving and improving. These algorithms learn from previous messages with humans, learn human responses to specific questions and answers, and what the correct response is to human responses. .
- Natural Language Processing (NLP). This is a language learning method that works in conjunction with machine learning. It’s currently in use, but with deep learning all around, most conversational AI will switch to deep learning to help AI understand language better.
- Parse received input. This is the part where the AI analyzes the text sent by the user and scans it to find out the context and purpose of the message.
- Dialogue Management: After NLP is performed and the input has been analyzed, the AI needs to respond with an appropriate response. Conversation management is where the AI decides which answers are most appropriate to send to the user, using previous processes to select answers.
- Reinforcement Learning: Finally, AI and user feedback is stored. Then, machine learning analyzes the input and output and whether they match exactly. From there, the machine learning can check if the user intent and the AI’s answer match, and learn how to better respond to the following similar inputs.
What is conversational AI used for?
Most people have encountered some form of conversational AI before and may not even know that they are talking to an AI instead of a real human. Some chatbots are easy to spot, but some are not.
There are many uses for conversational AI. For example, if you’ve ever talked to customer service using messenger on their website, there’s a good chance it’s a chatbot. It’s frequently used for customer service at this point because FAQs are easily programmed as replies to the chatbot, as well as managing bookings, schedules, and cancellations.
IT Desk Service
Conversational AI can also be used for IT desk service, helping with basic IT queries and troubleshooting. Instead of keeping IT staff busy all day with simple fixes, chatbots can help people who might otherwise have simple fixes and solutions. Chatbots can still send users to real people if the problem can’t be fixed.
Conversational AI can also be used to advertise and sell products. These bots can be set up to offer promotions or just sell and send them to target audience. If you have a well-established chatbot, it should be able to call the person by their first name and possibly know some basic information about them.
These bots can cause users to sign up or move down the funnel towards your product page.
Many businesses forget that conversational AI can be used to collect data.
With countless interactions every day, your conversational AI program will be able to store all the information gathered throughout the day and provide specific analytics on the day’s activities and messages.
- Record all customer messages and calls.
- Make all chats searchable, so you can identify issues customers may be having.
- Track specific keywords related to issues on all calls and messages and seek answers from customers.
- Collect necessary data such as call time, number of daily responses and results of the responses for the day.
Examples of conversational AI across industries
Conversational AI is used in many different industries for different uses. Here are three examples of conversational AI used in different industries.
SmarAction is scheduling automation software with built-in conversational AI that can understand booking queries, which we all know can be more complicated than just giving dates and bookings.
This AI excels at understanding natural language and can handle any problem or scheduling request the user may have.
IBM created the Watson Assistant, and who better to create a conversational AI that can handle customer transactions?
This AI assistant can work in many industries, including fashion and healthcare.
It can answer simple questions, execute transactions and contact dealers when the need arises.
A study has shown that companies using Watson Assistant can reduce processing times by 10%, improving customer satisfaction.
Cognigy is a great conversational AI tool that enables efficient customer service 24 hours a day.
Cognigy is best used for customer service, optimizing the time it takes for customers with questions to get the answers they need.
A lot of airlines use this software. This is especially the case after Covid when airlines have to deal with many customer service issues due to flight cancellations and refunds. Here, AI like Cognigy can be used to reschedule or refund eligible customers without contacting a customer service representative.
If you are looking for more conversational AI tools, check out this list Best conversational AI tool.
With so many uses for conversational AI, it’s no wonder it’s slowly taking over specific business areas. Of course, that doesn’t mean you never need to talk to a real person, but with simple tasks, conversational AI can speed things up when real humans are too busy with other, more important things. .
Featured image credit: Photo by Andrea Piacquadio; Bark; Thank you!