What is a chatbot and how does it work?

Chatbots has no longer been perceived as a fancy technology. Today, these tools are fully operational for businesses, and their potential allows them to automate most processes that previously required human intervention.

What is a chatbot and how does it work?

Would we think that a significant part of human communication would take place online? Absolutely not. However, we haven’t even noticed how natively communication tools have integrated into our lives. And chatbots are largely responsible for this. Today, it is a powerful tool for building effective relationships with the audience and in this article, we will tell what business opportunities this assistant has prepared.

Chatbot Definition

A chatbot is a specialized software that uses artificial intelligence (AI) or preconfigured scripts to conduct a dialog with users via a text or voice interface. To create such a system, development on a framework, ready-made APIs or programming the bot core from scratch is used.

The main function of a chatbot is to automate communication and provide useful information or assistance without the need to involve a live operator. Thanks to the use of AI, bots are able not only to answer questions but also to understand the context of the request and provide more personalized or adapted answers. These tools literally learn based on interaction with users.

Chatbots can perform various functions:

1. Customer support. Chatbots automate answers to frequently asked questions, help with standard problems, such as order tracking and password recovery. They can also search for specific information on a website, which reduces the workload of the support team.
2. Sales and marketing. Bots can act as a personal consultant, helping users choose products or services by providing recommendations based on their preferences or purchase history. They can automate the checkout process or organize entire marketing campaigns.
3. Process automation. Bots are able to perform tasks that previously required human intervention, such as scheduling meetings, reminding of important events, generating reports or conducting surveys. This reduces the time and resources required to perform routine tasks.
4. Entertainment and social functions. Chatbots can be used for interactive training programs or as self-development assistants.

A great feature of bots is their ability to integrate with other systems. The system can be paired with various external services, such as payment aggregators, CRM, calendars and other programs. This allows them to perform more complex tasks, which turns the bot into a powerful business tool.

A modern chatbot has great potential for business. Due to the speed of response and the ability to work in a multi-channel mode, systems can significantly increase the efficiency of client interaction and reduce service costs. For example, in the banking sector, chatbots can help users with financial transactions and basic client services (card blocking, inquiries on balance).

The potential of these systems is truly unlimited, and the question of how to create a chatbot is among the top search engine results. With the development of machine learning and natural language processing (NLP) technologies, these tools are becoming more and more intelligent. Bots are blurring the boundaries of their use, their scope is far from being limited to business - today they can be found in education, medicine, science, and many other areas requiring fast and efficient communication.

History of chatbot development

The history of chatbot development dates back to the mid-20th century when AI was just a concept...

The main stages of bot technology development:

1. 1966 – ELIZA model. The first chatbot that can be considered the ancestor of modern systems. It was created by Joseph Weizenbaum at the Massachusetts Institute of Technology. The program, called ELIZA, imitated a psychotherapist, using simple rules to recognize and answer user queries. Although ELIZA was quite primitive, it showed the potential of machine communication for the first time.
2. 1970-1990: deepening research into machine learning technology. After ELIZA, new programs appeared, such as PARRY 1972. It was designed specifically to simulate the behavior of a person with a mental illness. The second important prototype is ALICE (1995). The system already used more complex rules to create realistic dialogues.
3. 2000s. The beginning of the Internet era and chatbots for business: With the development of the World Wide Web, bots began to be used to automate client support. This allowed companies to provide faster service, especially in terms of answering client questions. In the late 2000s, chatbots for social networks and messengers such as Facebook or Skype became popular.
4. 2010: the artificial intelligence revolution. Tangible progress in machine learning and neural networks gave chatbots deeper intelligence. Now the systems not only executed simple commands but also learned to interact with users. The creation of Siri (2011) by Apple and Google Assistant (2016) is a vivid example of the breakthrough of this technology.

Experts call the present day the era of AI and NLP. Today, advanced bots are able to conduct complex dialogues, analyze the context of queries and provide personalized answers. A well-known example of such a bot is ChatGPT, whose model is based on language algorithms.

Main technologies for chatbot development

The main technologies used in the development of chatbots.

NLP – Natural Language Processing

Natural language processing is one of the key technologies that allows chatbots to understand and interpret human speech. NLP helps bots. The system functions are:

• Intent Recognition: determining the user’s need (for example, a request to buy a product or receive information);
• Entity Recognition: highlighting accent words or phrases such as date, place, names;
• Context processing: maintaining a logical connection between the generated phrases within a single dialog.

Popular NLP tools include spaCy from Python, NLTK, Dialogflow (Google) and Microsoft LUIS (Language Understanding).

Machine Learning

The technology allows chatbots to learn from the history of previous interactions. Main approaches in machine learning:

• text classification: to determine the category of input data (for example, if it is a support request or a purchase request);
• intentions classification: allows a bot to identify a specific task;
• sentiment analysis: helps to determine the emotional state of a user based on his/her request – positive, neutral or negative mood.

The main technologies and libraries for machine learning include: TensorFlow by Google, PyTorch by Facebook and Scikit-learn.

Text Generation

Chatbots use text generation technologies to create more natural and varied responses. They allow the bot to create unique responses that are not always limited to predictable scenarios.

Popular methods include:

• Transformer-based models (e.g., GPT, BERT);
• Seq2Seq (Sequence to Sequence).

The latter one is used to generate answers based on the input text.

ANN – artificial neural networks

Neural networks, especially deep neural networks (DNNs), are used for complex tasks such as context analysis, text generation and natural language processing. They are able to learn from large amounts of data and optimize their decisions based on history.

Chatbot frameworks

There are specialized frameworks that simplify the process of creating chatbots:

• Rasa: creation of intelligent systems based on machine learning and NLP.
• Botpress: development of complex business tools.
• Microsoft Bot Framework.

The latter is widely used in Microsoft products such as Skype, Teams and others.

Технології голосового розпізнавання (Speech Recognition & Text-to-Speech)

Speech Recognition & Text-to-Speech technologies

Popular models in this class are ASR (Automatic Speech Recognition) and the TTS synthesis algorithm. Examples of such technologies are:

• Google Speech-to-Text;
• IBM Watson Speech to Text;
• Amazon Polly.

Speech synthesis services are especially relevant in the business segment today, as they can significantly simplify client communication with company services.

Технології голосового розпізнавання (Speech Recognition & Text-to-Speech)

How a chatbot works: examples of scenarios

The way a chatbot works can be described as a sequence of steps:

• Initiation: the user starts interacting with the bot through one of the communication channels (website, phone, app);
• data collection: the system analyzes the user’s request and selects an interaction scenario;
• generation of output data – action, response or redirection to other resources;
• waiting – the bot enters this mode and after a repeated request, the whole cycle repeats.

It should be understood that the described scheme simplifies the communication between a bot and a real person. Between each of these steps, there are dozens of others, during which the system selects the right answer, learns, analyzes user feedback and performs other actions.

Some examples of scenarios are:

• client support;
• collecting user data (phone, questionnaires);
• sales automation scenario: recommendations, product selection;
• consultations: answers to business-related questions;
• surveys.

A typical example that is known to many users is the evaluation of company services. The bot offers to set metrics and automatically records it in the company’s database.

The role of artificial intelligence in chatbots

AI acts as the main mechanism for processing and analyzing user requests. The technology allows bots to communicate effectively while generating human-level queries. Conducting dialogues, recognizing intentions, and giving individualized advice are already commonplace for a modern bot.

AI algorithms, in particular natural language processing (NLP), help systems understand the context and generate meaningful responses. This makes it possible to improve interaction based on past experience.

AI also uses machine learning to improve the user experience. Chatbots can adapt to new queries, constantly improving their answers based on the history of interactions and feedback.

Яким способом можна створити свого чат бота

In which way to create the own chatbot

There are several main approaches to create a chatbot:

1. Ready-made constructors. ManyChat, Chatfuel, Tars, BotFather platforms allow to create a bot without writing code, using visual interfaces.
2. Software development. Here, programming knowledge is required. Typical environments are Python or Node.js with libraries such as ChatterBot, Rasa, Dialogflow (from Google), Microsoft Bot Framework.
3. Ready-made APIs. For example, Telegram, Facebook Messenger and WhatsApp platforms already have APIs, which greatly simplifies the development of a basic chatbot.

However, there is another approach to this task – to contact development specialists who, based on the task, implement a functional chatbot with the specified characteristics.

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Skylex: your trustworthy technical partner!

Skylex is a team of professionals who are ready for projects of any complexity. We know what modern business needs and are ready to offer the best technical solutions to accomplish your goals.

Our advantages:

• personalized approach to each project;
• we use modern technologies to develop chatbot systems;
• a clear structure of the task performing, where each team member performs his/her own work;
• clear pricing policy.

Contact us, we’ll be glad to help you out!