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What is Conversational AI? Explanation from how to make to introduction examples in 2022!

Conversational A

There are many people who want to introduce interactive AI, but do not know how to make it.

In this article, we will comprehensively explain the types of interactive AI and the actual flow of making them.

Through this article, I hope that you will deepen your understanding of conversational AI and that it will serve as a foothold for its introduction.

Table of Contents

  • What is Conversational AI?
  • Types of interactive AI
    • Chatbot
    • Voice chat
  • Conversational AI – How to make
    • ① Clarify the purpose of making
    • ② Read data
    • (3) Let the model learn
    • ④ Try to use
  • Interactive AI that can be created with no code
    • Cognigy
    • KUZEN
    • hachidori
  • 5 Case Studies of Conversational AI
    • Airline Lufthansa – 24/7 support
    • Sawai Pharmaceutical Co., Ltd. – Improved search convenience
    • Yamato Transport – helping with logistics problems
    •  GEICO Virtual Assistant – Human Chatbot
    • Add Value Co., Ltd. – Increased closing rate
  • In conclusion

What is Conversational AI?

Conversational AI is an AI that is created for the purpose of having a computer automatically converse with humans.

It is used in marketing, sales and customer service where communication is required.

Integrating natural language processing (NLP) and machine learning (ML) into the system is critical to the use of conversational AI. This allows you to accurately interpret customer conversations and automatically return the right answers.

Types of interactive AI

There are also two types of interactive AI:

  1. Chatbot
  2. Voice chat

I will explain each.

chatbot

A chatbot is a word that combines “chat” and “bot” and is a program that automatically conducts conversations.

It can be said that chatbots have evolved with the development of artificial intelligence, but at this point we have not yet reached the level where artificial intelligence can understand the deep meaning of words and interact with them. It learns from pre-input data, estimates the user’s intentions, and gives the optimal answer at that time.

Chatbots are also divided into two types: rule-based type and automatic learning function type.

The rule-based type is also called a scenario type, where the chatbot presents options, the user selects the item corresponding to the question from the options, and the chatbot finally presents an answer. is.

On the other hand, the automatic learning function type is also called machine learning type or artificial intelligence type, and is a chatbot that chooses answers that are statistically likely to be correct by artificial intelligence.

Voice chat

Another is voice chat.

As the name suggests, chatbots communicate in a chat format, so the input source is text, but voice chat uses voice as the input source.

The other mechanism is almost the same as the chatbot except the input source is different.

Conversational AI – How to make

I will explain the flow of creating a conversational AI like the one above. It is mainly divided into four steps.

  1. clarify the purpose of making
  2. load the data
  3. train the model
  4. Try it out

I will explain each.

① Clarify the purpose of making

The first step is to clarify the purpose of making.

By clarifying what you want to use AI for, you can naturally decide the amount and content of data required for machine learning. Therefore, it is good to have a specific goal in mind.

② Read data

The second step is to load the data.

The most important thing to do with any AI is to collect and read data.

For example, if you want AI to remember the answer to “How are you?”

Mr. A “How are you?” → Mr. B “I’m fine!”

Mr. A: “How are you?” → Mr. B: “It’s okay.”

Mr. A How are you?'' → Mr. BYou’re lacking sleep, aren’t you?”

Collect conversational data.

There are various ways to collect data, such as using datasets or collecting them yourself using the Internet.

(3) Let the model learn

The third step is to train the model.

After collecting the data, train the actual machine learning model ( algorithm ). The procedure for learning is as follows.

  • Input “what you want to identify” into the machine learning model
  • Let the machine learning model output “prediction labels”
  • “Compare with the actual label of what you want to identify” with reference to the training data
  • “Modify the machine learning model so that it can output the actual label”

If “input data”, “output value”, and “correct label” can be represented by numbers or combinations of numbers such as sequences and vectors, they can be handled by machine learning.

④ Try to use

The last thing is to actually use it.

By actually having a conversation with AI, you can find problems such as insufficient learning. In addition to simply increasing the learning time, you will be able to have a solid conversation by taking various methods such as increasing the amount of data, reviewing the data itself, and tuning the model.

Interactive AI that can be created with no code

Conventionally, when developing software, character strings written in a programming language, so-called “code” are used. However, if you use a no-code development tool, you don’t need to write source code, and you can easily complete it by simply dragging and dropping pre-prepared parts.

  1. Cognigy
  2. KUZEN
  3. hachidori

Therefore, here we will introduce three interactive AI that can be created with no code.

Cognigy _

Cognigy is a conversational AI platform that allows you to create and manage all your text and voice bot conversation flows on one platform.

Since it is a GUI tool, even non-technical people can use it.

KUZEN

KUZEN is a platform that allows you to build a chatbot with no code. It can also work with various chat interfaces.

KUZEN can respond to prospective customers who have not yet reached the point of inquiry or purchase. There are cases where the number of leads has increased by 6 times by introducing this.

hachidori

hachidori is a chatbot tool that can be used for various purposes from marketing to business efficiency.

Scenario type, free word type, manned chat support type, these three can be used in combination.

We have over 7,000 development achievements, including customer-oriented chatbots and in-house helpdesk-type chatbots for Sumitomo Life, Softbank, Recruit, Enoteca, Dentsu Digital, Tokyo Metropolitan Government, etc.

5 Case Studies of Conversational AI

Next, I would like to introduce five cases where conversational AI was actually introduced.

  1. Airline Lufthansa – 24/7 support
  2. Sawai Pharmaceutical Co., Ltd. – Improved search convenience
  3. Yamato Transport – helping with logistics problems
  4.  GEICO Virtual Assistant – Human Chatbot
  5. Add Value Co., Ltd. – Increased closing rate

I will explain each.

Airline Lufthansa – 24/7 support

Lufthansa Airlines

(Source: https://cognigy.tdse.jp/works/lufthansa/)

In the event of flight cancellations or missed connections, you can chat with the Lufthansa Group airline chatbots.

Our AI-powered chatbots provide 24/7 support and are trusted by 10,000 customers a day and more than 1 million conversations per year. Additionally, if the chatbot is not available, you can request a conversation with a human operator. There is no need to wait in line at this time either.

The chatbot has allowed the company’s customer service center to spend less time on common questions and more time on questions that the bot can’t answer.

Sawai Pharmaceutical Co., Ltd. – Improved search convenience

In August 2017, Sawai Pharmaceutical Co., Ltd. started a site renewal to improve access to information for medical professionals. Introduced a chatbot.

As a result, healthcare professionals can search faster and find information in about half the time.

Yamato Transport – helping with logistics problems

Yamato Transport has started using AI operators to respond to calls for pickup requests. By combining LINE CLOVA’s AI technologies “CLOVA Speech ( speech recognition )” and “CLOVA Voice (speech synthesis)” with a conversation control mechanism, the AI ​​operator realized natural dialogue responses using AI.

This reduces the waiting time for calls and aims to reduce the stress of waiting.

 GEICO Virtual Assistant – Human Chatbot

GEICO’s virtual assistant “Gabby” offers a human-like chatbot.

It quickly guides you to the exact page you’re looking for on a website or app every time, and it’s learning from you, so it’s getting smarter and smarter.

Add Value Co., Ltd. – Increased closing rate(Source: https://a-value.co.jp/)

Addid Value Co., Ltd. has introduced the AI ​​chatbot “FirstContact” in order to reduce the effort on the phone as there are many calls from customers who are close to closing a contract.

“FirstContact” uses IBM Watson and is used to help website and EC site users show interest in products and take action.

As a result of the introduction, the chatbot closing rate has also improved.

In conclusion

In this article, we introduced types, how to make, and case studies of interactive AI.

Recently, conversational AI has become familiar. Therefore, if you have knowledge about interactive AI, you will have the opportunity to use it at your company.

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