Chatbots are fascinating. They are available to answer questions 24/7. They can perform so many tasks. If you’ve interacted with a chatbot recently, you must’ve realized that they answer questions and provide insights with human efficiency.
Chatbots understand human language when we ask them questions. Even if the questions are vague or confusing, they search their database to give us the answer we’re looking for. This is due to artificial intelligence, natural language processing, and machine learning.
One thing is clear. Chatbots are clever, and more businesses are learning to count on them to speed up their operations, run their business efficiently, and let their teams focus on what matters. You can find chatbots on Facebook Messenger, WhatsApp, and other websites.
Let’s learn more about chatbot architecture, how chatbots work, how they are trained, and, more importantly, how they acquire language and their purpose.
What is a Chatbot?
A chatbot is a computer program or software trained to perform specific tasks. The purpose of chatbots is task automation. Developers train them to recognize human speech or text to respond appropriately or gather data to provide insights. Chatbots are also virtual assistants programmed to show human intelligence to help humans with mundane or repetitive tasks.
Technology makes chatbots today a reliable tool. AI chatbots are the most popular type of chatbots today. Unlike basic chatbots, they can help users way better than the basic chatbot that merely responds to questions saved on its database.
Examples of Chatbots
You have heard of Apple’s Siri or Google Assistant. You’ve probably also used one of them or both at one point in your life. Both are great examples of conversational AI chatbots or virtual assistants. Both assistants can engage in what is so similar to human conversation. They perform many tasks like scheduling appointments, setting alarm clocks, making calls for you when you’re driving, and sending texts.
Other examples of chatbots are those found on Facebook Messenger or WhatsApp. You can check a restaurant’s menu or place an order through them. Some of them are designed to answer queries by searching for answers from a business knowledge database.
You can also find floating chatbots on website pages, and those chatbots help visitors navigate the website. Online stores can guide visitors to find their favorite products and guide them to similar products they might be interested in.
Why the word Chatbot is Misleading?
The word chatbot gives the impression that AI-powered chatbots only engage in a human-like conversation to answer users’ questions.
While engaging in conversation with users is an integral part of chatbot technology, AI-powered chatbots can also gather information like email, and phone numbers from users, integrate with different services like CRM and offer insights and recommendations based on the data collected to help businesses with lead generation and conversion rate. A great example of this is IBM Watson Assistant.
What is the Purpose of a Chatbot?
Like any computer program, the purpose of a chatbot is to save time, help businesses run efficiently, automate the process to provide support 24/7, and analyze vast amounts of data to help businesses make better decisions. A chatbot only helps your sales team or customer support representatives focus on urgent matters. A chatbot also answers thousands of questions on Facebook pages. Let’s talk about the purpose of a chatbot in detail:
Chatbots never sleep. That’s their number one amazing feature. Chatbots are reliable assistants who work round the clock answering queries, scheduling appointments, offering product recommendations, and helping your business thrive. Real agents can’t work 24/7. An intelligent bot can help them by answering users’ questions and directing the conversation to a real agent when they become available to avoid user frustration.
A chatbot tells the users that they can count on you, that your business will support them, and provide service whenever they need support. This way, you’ll increase conversion rates and increase your customer satisfaction.
A customer support chatbot can answer many user queries simultaneously, unlike a real person who can only attend to one person at a time. Therefore, a chatbot can answer frequently asked questions, engage with users and provide relevant answers while directing urgent requests to a real agent to save time.
In addition to engaging in human conversation to provide support, chatbots collect data. This data could be anything from surveys, user emails, or phone numbers to providing insights about questions users ask all the time so that businesses address these questions about the business or the service.
Integrate with Different Applications
Chatbots are not just computer programs that you add to your website or messaging apps so they can interact with users. Instead, Chatbots integrate different applications, programs, and services to provide you with the best solutions. For example, Chatbots integrate with Customer Relationship Management software (CRM) to give insights based on your data.
A chatbot can also integrate with your calendar to book meetings efficiently on your behalf based on your schedule and alert you to all upcoming meetings.
Chatbots collect emails, phone numbers, and the questions users frequently ask, in addition to data from integrated computer programs, and based on the data, chatbots generate reports that are relevant to the business providing insights and recommendations that wouldn’t be possible without the amounts of data a chatbot can collect.
Personalize Chat Conversations and Recommendations
Chatbots are not human beings; they are programmed to engage in human conversations, understand natural language, and respond appropriately to user queries. Furthermore, bots are integrated with different applications or software and have a huge database, so they personalize conversations or interactions.
For example, they address users by name and can offer product recommendations based on the products a user bought for eCommerce businesses.
How Do Chatbots Work?
When you first add a chatbot to your business, you decide how it will interact with your site visitors or customers. Then, through templates and the drag-and-drop feature, you get to control the predefined flow.
A predefined flow is like thinking about possible scenarios and providing suitable outcomes so the bot doesn’t frustrate the users. An excellent conversation flow offers the users recommendations, choices, and possible answers to what they are looking for.
The more you work on your predefined flow, the more your chatbot helps your visitors find the answers or services they are looking for, and the more it can help your business.
Bots generally fall under two criteria: rule-based chatbots or AI chatbots.
Rule-based chatbots follow simple or intricate rules to answer users’ questions. If they encounter a new question not included in their programming or their set of rules, they can’t answer the questions.
On the other hand, AI chatbots are unique. They understand how users communicate and are clever enough to understand users’ intent. Intent recognition is one of the fascinating features of modern chatbots.
What Technology Do Chatbots Use?
Since artificial intelligence is the future, we’ll discuss the technologies that make these clever chatbots possible. Chatbots use NLP, machine learning, artificial neural networks, and other technologies.
We’ll walk you through how they understand user queries from past chat conversation patterns to improve future interactions. For example, before a chatbot responds to human users, many processes or complex systems take place in the background so that the bot gives you the reply you expect and find helpful.
Machine Learning, as explained by the IBM website, is “a branch of artificial intelligence (AI) and computer science that focuses on the use of data and algorithms to imitate how humans learn, gradually improving its accuracy.” In other words, AI is less about programming and more about teaching machines how to learn.
Some of the challenges that come with training bots are human language, natural language understanding, and natural language processing NLP.
What is NLP (Natural Language Processing)?
Understanding language is at the core of how AI chatbots work. If they don’t understand the customers, they can’t help them. So, a challenging prospect in training and getting chatbots to work efficiently is teaching them language and how to respond. So, we can’t think about chatbots without mentioning natural language processing NLP, natural language understanding NLU, and natural language generation.
Natural language understanding is when the bot identifies user needs through keywords and context. Natural language processing is when chatbots convert speech or text into structured data. And then, the structured data will be used to generate or figure out an answer.
For chatbots to work, they use the following three processes: pattern matching, machine learning algorithms, and artificial neural networks.
- Pattern Matching:
This is when the chatbot doesn’t make much effort to get the answer. The question and answer exist together in the database through a pattern “who invented so and so?” “This person invented so and so.” It is clear and found in the same place. Artificial Intelligence Markup Language (AIML) is a collection of rules that use these patterns, and several designs make a hierarchical structure.
This is a more complicated process where the chatbot works by classifying words and giving a score to understand language to provide an appropriate response. The words “Hi,” “Good,” “Morning,” and “How are you?” are all classified as greetings. The more similar words the chatbot finds in the input sentence, the more likely it is to understand the greeting and respond accordingly.
- Neural Networks
A neural network is “a subset of machine learning” and “at the heart of deep learning algorithms.” The human brain inspires the name. They are connected nodes of data resembling how the neurons are connected.
A neural network sends and receives data; in the end, we get the output layer. Neural networks allow us “to classify and cluster data at high velocity.” Google search algorithm is a famous example of a neural network.
How Does NLP Work in Chatbots?
Inside the mind of the chatbot, different processes take place to get the result we’re looking for.
- Sentiment Analysis. The chatbot can interpret and understand the user’s sentiment based on an analysis of the given text.
- Named Entity Recognition. Named entity recognition is when the chatbot looks for similar categories of words the user provides and tries to develop similar products.
- Dependency Parsing. This is when the chatbot looks at words, subjects, or verbs that a human uses and tries to understand what the user conveys.
How Do Chatbots Process Human Languages?
The human brain is amazing and human language is so unexpected. Therefore, training a bot in natural language understanding is not an easy feat. After all, sentences can lack structure, and words can be full of common spelling mistakes or typographical errors.
A bot has to understand that “acheive” is achieve. A bot must also realize that I need to check my bill is the same as where my bill is. Sentences are not straightforward, and there are thousands of ways to convey one meaning.
A user’s text or a user’s input has many meanings, and a clever bot is trained to understand what a user means. Chatbots, due to the technology today, have keyword recognition features. And instead of a pre-defined answer of a rule-based bot, they can search their database and provide relevant information.
Data is needed to train the bots to process human language. Developers use machine learning tools and models to train the bots and provide patterns about how clients form their questions so that the chatbots are ready to answer.
How Are Chatbots Trained?
So, how are chatbots trained? Chatbots are constantly provided with conversation logs to understand patterns, frequently asked questions, structure, and learn more about human interactions. So, chatbots benefit from past information.
Time is of paramount importance to chatbots. Over time, they learn the best way to reply to customers based on previous conversations. The more sentence structures, the more info they are exposed to, and the more they can generate accurate responses.
The Importance of Chatbots Today
Users can communicate with a bot via the chat interface or by voice. A bot can also communicate through text-to-speech, which gives your bot a human voice. Bots are not human beings, so if a conversation introduces questions and concepts a bot can’t understand, it will direct the customer to a human operator. Chatbots are convenient. That is why they are indispensable to many businesses.
Training bots are essential nowadays because they play a crucial role in different services and industries: instant messaging, customer portals, and smart speakers with chatbot functionality. In addition, they can help educational institutions, hospitals, sales teams, marketing teams, and restaurants.
They can help people place orders, find information about their favorite products, get recommendations, get their receipts, and provide feedback on the services they get through filling out online surveys provided by chatbots.
Chatbots can help students learn by repeating educational material several times, sending out quizzes, frequently testing students, and finding out if there are certain areas that they need to work on.
Most businesses don’t have to know about chatbot architecture, how chatbots work, machine learning chatbots, and how bots process language. It is a complex process that benefits from many technologies. Much work is beyond a chatbot’s ability to respond successfully to your query or collect data and provide insights.
Now, you have a good idea about the types of bots, how they process language, the technologies behind them, and, most importantly, how they can help your business. So, it’s time you take your business to the next level and use chatbots. Whether you add it to your website or messaging apps, you will benefit greatly from a chatbot.
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