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How does a ChatBot works?

How does a ChatBot works?

By carolc

Nowadays, we all have heard about ChatBots and maybe we should have interacted with one without even noticing it. Due to Internet massification, ChatBots is an in vogue technology as a communication strategy seeking to maintain direct contact with users. In this article we will talk about what ChatBots are and how they work, among other things.

What is a ChatBot?

A ChatBot is an artificial intelligent program capable of answer predetermined questions automatically even have a coherent conversation with a person through a chat. ChatBot communication can be both via text or even via voice by using structured messages and preconceived responses. Some models have started to use text-speech converter programs making user interaction more realistic. It can be more or less complex and answer a greater or lesser number of questions even to execute an action depending on our needs. While some ChatBots just scan keywords in a database and generate responses related, others implement sophisticated algorithms developed with artificial intelligence and machine learning that allow them to be able to learn; they even can get to intuit habits and understand users tastes and preferences.

ChatBots not only have an improvement in their processing capabilities and understanding of conversations (that thing requires continuous tuning and testing). It also offers the possibility of analyzing conversation feelings, which makes it not only used to automate responses and pre-established answers, but to generate valuable reports on reputation, emotion analysis and engagement with brands.

How does a ChatBot works?

How does a ChatBot works is transparent and simple at user level. User writes a question in a chat window and the bot will answer based on its algorithms. Generally, a certain number of options are included in the software to deal with those incidents that occur commonly. The greater the complexity of the program, the greater number of interactions it can have with the user without needing other contact methods. Most of them are programmed following artificial intelligence and machine learning concepts. Which allows that beyond just giving stored answers they be able to interpret what the user says, analyze it, give a coherent answer and also learn from each of its interactions.

Generally speaking, conversation takes place via text and using a concise language is used for best results. In order for satisfactory results, it is also convenient that contents preparation be correct. For example, a good way to get a ChatBot to offer quality content and to generate credibility in clients is with content marketing, since it is a highly recommended technique for this type of action. ChatBots to be efficient need implementers must analyze their final user needs and their service processes and most common conversations that can be developed to build responses at the right way and offer them at the right time.

Like common applications ChatBots are made up of multiple layers. They have application layers, APIs, Conversational User Interfaces (CUIs) and databases. Today in production we can have a conversation with some of them through the most used platforms like WhatsApp, Facebook, Twitter, Telegram just to mention a few.

ChatBots use some principles of natural language techniques

Natural Language Processing (NLP)

Is a subset of artificial intelligence and linguistics related to interactions between human language and computers; particularly, how to process and analyze natural language data. It is used interpret user input into sentences and words and also expands the meaning of the text through a series of techniques including other factors such as user emotions.

Natural Language Understanding (NLU)

Also known as Natural Language Interpretation (NLI) is a subtopic of NLP relative to machine reading comprehension, it helps to understand what user has said. By using tools such as lexicons, synonyms and topics; those tools are used together as algorithms or rules to build dialogue that will guide the ChatBot how to respond in the best way possible.

Natural Language Generation (NLG)

Is a computing process focused on transforms structured data into natural language. By using NLG, a ChatBot is capable of query data on repositories and use it to create a response, delivering a personalized user experience, and going beyond providing ready-made responses. For example, it can be used to produce custom content for a web or mobile application.

Conversational AI technology takes natural language processing to the next level, allowing you to create advanced dialogue systems using memories and personal preference data and your own contextual understanding of chat to provide a realistic and engaging natural language interface.

ChatBots in business strategy

Now that we know what ChatBots are and how they work, we can take the next step and start thinking about how to implement them in our business strategy. The important thing is that we are clear about why we want to create it and the solutions that we are going to provide as added value, considering that the first thing we must do is design a conversational experience. ChatBot questions should not be general, open or ambiguous, in this way we will prevent the user from being distracted by other topics that do not interest us. There are many types of live chats, some of them offer such an authentic experience, in which it is very difficult to determine if the answering is a virtual robot or a human being. According to the needs of our business, we must select the best ChatBot tool that helps us meet our objectives.

ChatBots have come to stay and their use will grow in the coming years. There are several advantages that this artificial intelligence offers us as well as the customization possibilities based on different user profiles. In addition, with the great advance of artificial intelligence and in parallel with the analytical capacity and linguistic understanding that they can offer, it has gone from understanding only keywords to deciphering sarcasms or even the conversations and the tones used in them, through a better understanding of the context and a better ability to provide responses adapted to all kinds of needs and possible situations in the relationship between the machine and the human being.

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